Technologies, Volume 7, Issue 3 (September 2019) – 21 articles

Video transmission over wireless computer networks is increasingly popular as new applications emerge and wireless networks become more widespread and reliable. An ability to quantify the quality of a video transmitted using a wireless computer network is important for determining network performance and its improvement. The process requires analysing the images making up the video from the point of view of noise and associated distortion as well as traffic parameters represented by packet delay, jitter and loss. In this study a modular fuzzy logic based system was developed to quantify the quality of video transmission over a wireless computer network. Peak signal to noise ratio, structural similarity index and image difference were used to represent the user’s quality of experience (QoE) while packet delay, jitter and percentage packet loss ratio were used to represent traffic related quality of service (QoS). An overall measure of the video quality was obtained by combining QoE and QoS values. Systematic sampling was used to reduce the number of images processed and a novel scheme was devised whereby the images were partitioned to more sensitively localize distortions. To further validate the developed system, a subjective test involving 25 participants graded the quality of the received video. The image partitioning significantly improved the video quality evaluation. The subjective test results correlated with the developed fuzzy logic approach. The video quality assessment developed in this study was compared against a method that uses spatial efficient entropic differencing and consistent results were observed. The study indicated that the developed fuzzy logic approaches could accurately determine the quality of a wirelessly transmitted video. Full article

Comorbidities can have a cumulative effect on hospital outcomes of care, such as the length of stay (LOS), and hospital mortality. This study examines patients hospitalized with congestive heart failure (CHF), a life-threatening condition, which, when it coexists with a burdened disease profile, the risk for negative hospital outcomes increases. Since coexisting conditions co-interact, with a variable effect on outcomes, clinicians should be able to recognize these joint effects. In order to study CHF comorbidities, we used medical claims data from the Centers for Medicare and Medicaid Services (CMS). After extracting the most frequent cluster of CHF comorbidities, we: (i) Calculated, step-by-step, the conditional probabilities for each disease combination inside this cluster; (ii) estimated the cumulative effect of each comorbidity combination on the LOS and hospital mortality; and (iii) constructed (a) Bayesian, scenario-based graphs, and (b) Bayes-networks to visualize results. Results show that, for CHF patients, different comorbidity constructs have a variable effect on the LOS and hospital mortality. Therefore, dynamic comorbidity risk assessment methods should be implemented for informed clinical decision making in an ongoing effort for quality of care improvements. Full article

In the age of digitalization, the collection and analysis of large amounts of data is becoming increasingly important for enterprises to improve their businesses and processes, such as the introduction of new services or the realization of resource-efficient production. Enterprises concentrate strongly on the integration, analysis and processing of their data. Unfortunately, the majority of data analysis focuses on structured and semi-structured data, although unstructured data such as text documents or images account for the largest share of all available enterprise data. One reason for this is that most of this data is not machine-readable and requires dedicated analysis methods, such as natural language processing for analyzing textual documents or object recognition for recognizing objects in images. Especially in the latter case, the analysis methods depend strongly on the application. However, there are also data formats, such as PDF documents, which are not machine-readable and consist of many different document elements such as tables, figures or text sections. Although the analysis of PDF documents is a major challenge, they are used in all enterprises and contain various information that may contribute to analysis use cases. In order to enable their efficient retrievability and analysis, it is necessary to identify the different types of document elements so that we are able to process them with tailor-made approaches. In this paper, we propose a system that forms the basis for structuring unstructured PDF documents, so that the identified document elements can subsequently be retrieved and analyzed with tailor-made approaches. Due to the high diversity of possible document elements and analysis methods, this paper focuses on the automatic identification and extraction of data visualizations, algorithms, other diagram-like objects and tables from a mixed document body. For that, we present two different approaches. The first approach uses methods from the area of deep learning and rule-based image processing whereas the second approach is purely based on deep learning. To train our neural networks, we manually annotated a large corpus of PDF documents with our own annotation tool, of which both are being published together with this paper. The results of our extraction pipeline show that we are able to automatically extract graphical items with a precision of 0.73 and a recall of 0.8. For tables, we reach a precision of 0.78 and a recall of 0.94. Full article

Active filter design is a mature topic that provides good solutions that can be implemented using discrete devices or integrated circuit technology. For instance, when the filter topologies are implemented using commercially available operational amplifiers (opamps), one can explore varying circuit parameters to tune the central frequency or enhance the quality (Q) factor. We show the addition of a feedback loop in the signal flow graph of a biquadratic filter topology, which enhances Q and highlights that a sensitivity analysis can be performed to identify which circuit elements influence central frequency, Q, or both. In this manner, we show the opamp-based implementation of a biquadratic bandpass filter, in which Q is enhanced through performing a sensitivity analysis for each circuit element. Equations for the central frequency and Q are provided to observe that there is not a direct parameter that enhances them, but we show that from sensitivity analysis one can identify the circuit elements that better enhance Q-factor. Full article

Cryogenic machining is a relatively new technique in machining. This concept was applied on various machining processes such as turning, milling, drilling etc. Cryogenic turning technique is generally applied on three major groups of workpiece materials—superalloys, ferrous metals, and viscoelastic polymers/elastomers. The roles of cryogen in machining different materials are unique and are summarised in this review article. Finally, the challenges in using cryogenic machining in industries are also highlighted. Full article

A process vacuum chamber is filled with a homogeneous plasma of glow discharge with electrostatic electron confinement, which is used for surface hardening of massive products. At the current of 2–20 A and the gas pressure ranging from 0.1 to 1 Pa the discharge voltage amounts to 350–500 V. When a bias voltage of 2 kV is applied to an immersed in the plasma hollow cylinder with a mass of 15 kg, electrical power spent on heating it by accelerated ions exceeds by an order of magnitude the power spent on the discharge maintenance. The massive cylinder is heated up to 700 °C for 15 min. When argon mixture with nitrogen (30%) is used, the nitriding for 3h results in an increase in the surface hardness from 400 up to 1000 HV50 and the nitrided layer thickness grows to ~100 μm. The nitriding rate is enhanced by a high degree of nitrogen dissociation due to decomposition by fast electrons and surface structural defects due to bombardment by high-energy ions. Full article

GVNS, which stands for General Variable Neighborhood Search, is an established and commonly used metaheuristic for the expeditious solution of optimization problems that belong to the NP-hard class. This paper introduces an expansion of the standard GVNS that borrows principles from quantum computing during the shaking stage. The Traveling Salesman Problem with Time Windows (TSP-TW) is a characteristic NP-hard variation in the standard Traveling Salesman Problem. One can utilize TSP-TW as the basis of Global Positioning System (GPS) modeling and routing. The focus of this work is the study of the possible advantages that the proposed unconventional GVNS may offer to the case of garbage collector trucks GPS. We provide an in-depth presentation of our method accompanied with comprehensive experimental results. The experimental information gathered on a multitude of TSP-TW cases, which are contained in a series of tables, enable us to deduce that the novel GVNS approached introduced here can serve as an effective solution for this sort of geographical problems. Full article

The design and implementation of an asymmetrical Doherty power amplifier are discussed, where two Cree GaN High Electron Mobility Transistors (HEMTs) devices are used for designing an asymmetrical Doherty power amplifier to achieve saturated power of 48 dBm and optimal back-off efficiency of 8 dB in the frequency band of 3.3–3.5 GHz. Rogers RO4350B material is used as a substrate material, a back-off of 8 dB was achieved with an average gain of 10 dB. Load-pull data are an important tool for determining the optimum load impedance that the transistor needs to see. Additionally, the measured efficiency was 50% when the designed amplifier was tested by a modulated signal of 8 dB peak-to-average-power ratio when the average output power was 40 dBm. At the same time, the linearity of the designed amplifier was measured and found 31.8 dB which can be improved using a digital pre-distorter. The gain phase measurement can be used as an indicator for compensating the phase difference between the two cells. Full article

Ageing is a global phenomenon which is pushing the scientific community forward the development of innovative solutions in the context of Active and Assisted Living (AAL). Among functionality to be implemented, a major role is covered by falls and human activities monitoring. In this paper, main technological solutions to cope with the aforementioned needs are briefly introduced. A specific focus is given on solutions for Falls recognition and classification. A case of study is presented, where a classification methodology based on an event-driven correlation paradigm and an advanced threshold-based classifier is addressed. The receiver operating characteristic (ROC) theory is used to properly define thresholds’ values while, in order to properly assess performances of the classification methodology proposed, dedicated metrics are suggested, such as sensitivity and specificity. The solution proposed shows an average Sensitivity of 0.97 and an average Specificity of 0.99. Full article

Objectives: The study reported in this article aimed to identify: (i) the most relevant applications supported by smart city infrastructure with an impact on the provision of healthcare; (ii) the types of technologies being used; (iii) the maturity levels of the applications being reported; and (iv) major barriers for their dissemination. Methods: A systematic review was performed based on a literature search. Results: A total of 44 articles were retrieved. These studies reported on smart city applications to support population surveillance, active ageing, healthy lifestyles, disabled people, response to emergencies, care services organization, and socialization. Conclusions: Most of the included articles were either of a descriptive and conceptual nature or in an early stage of development, which means that a major barrier for their dissemination is their lack of concreteness. Full article

Additive manufacturing of polymer products over the past decade has become widespread in various areas of industry. Using the fused filament fabrication (FFF) method, one of the most technologically simple methods of additive manufacturing, it is possible to produce parts from a large number of different materials, including wear-resistant nylon. The novelty of the work is properties investigation of ±45° filling configuration with different filling degree for nylon, as well as calculating the effect of infill on the strength characteristics, excluding the shell. This article reflects the process of manufacturing samples from nylon using FFF technology with various internal topologies, as well as tensile tests. The analysis of the obtained results is performed and the relationship between the structure of the sample and the limit of its strength is established. To calculate real filling degree and the effect of internal filling on the strength characteristics of the specimen, it is proposed to use a method based on the geometric and mass parameters. The FFF method is promising for developing methods for producing a composite material. The results of this article can be useful in choosing the necessary manufacturing parameters. Full article

The convention for the safeguarding of Intangible Cultural Heritage (ICH) by UNESCO highlights the equal importance of intangible elements of cultural heritage to tangible ones. One of the most important domains of ICH is folkloric dances. A dance choreography is a time-varying 3D process (4D modelling), which includes dynamic co-interactions among different actors, emotional and style attributes, and supplementary elements, such as music tempo and costumes. Presently, research focuses on the use of depth acquisition sensors, to handle kinesiology issues. The extraction of skeleton data, in real time, contains a significant amount of information (data and metadata), allowing for various choreography-based analytics. In this paper, a trajectory interpretation method for Greek folkloric dances is presented. We focus on matching trajectories’ patterns, existing in a choreographic database, to new ones originating from different sensor types such as VICON and Kinect II. Then, a Dynamic Time Warping (DTW) algorithm is proposed to find out similarities/dissimilarities among the choreographic trajectories. The goal is to evaluate the performance of the low-cost Kinect II sensor for dance choreography compared to the accurate but of high-cost VICON-based choreographies. Experimental results on real-life dances are carried out to show the effectiveness of the proposed DTW methodology and the ability of Kinect II to localize dances in 3D space. Full article

The inability of ceramic and nanoceramic processing without expensive diamond tools and with a high-material-removal rate hampers the scope of its potential applications and does not allow humanity to make a full shift to the sixth technological paradigm associated with Kuhn scientific revolutions and Kondratieff’s waves and restrains the growth of the economy. The authors completed a review on the research state of ceramic and nanoceramic processing by electrical discharge machining, which is possibly solved by two principal approaches associated with the usage of standard commercially available machine tools. The first approach is related to the introduction of expensive secondary phase; the second approach proposes initiate processing by adding auxiliary electrodes in the form of coating, suspension, aerosol, or 3D-printed layer based on the components of silver, copper, or graphite in combination with an improved dielectric oil environment by introducing graphite or carbon nanoparticles, which is hugely relevant today. Full article

This study presents a cellular automata (CA) model to assist decision-makers in understanding the effects of infrastructure development projects on adverse events in an active war theater. The adverse events are caused by terrorist activities that primarily target the civilian population in countries such as Afghanistan. In the CA-based model, cells in the same neighborhood synchronously interact with one another to determine their next states, and small changes in iteration yield to complex formations of adverse event risks. The results demonstrate that the proposed model can help in the evaluation of infrastructure development projects in relation to changes in the reported adverse events, as well as in the identification of the geographical locations, times, and impacts of such developments. The results also show that infrastructure development projects have different impacts on the reported adverse events. The CA modeling approach can be used to support decision-makers in allocating infrastructure development funds to stabilize active war regions with higher adverse event risks. Such models can also improve the understanding of the complex interactions between infrastructure development projects and adverse events. Full article

For stress-strain response simulations and damage prediction of cyclically loaded mechanical components, it is crucial to determine both the stress-strain and durability curves of the materials sued. Round and flat specimens can be used for this purpose, either following standard recommendations for their geometry or by designing a special geometry which enables special requirements, such as initial cracks of various shapes, attachment of an extensometer, special grips for raised temperatures, and so on. However, especially in the case of flat specimens having a slender shape, buckling can occur before the stress or strain values reach a sufficient magnitude in compression. To avoid this, an anti-buckling support can be attached to the specimen, which prevents the occurrence of buckling. In turn, friction occurs between the specimen and the anti-buckling support, which affects the measurement of the stress. If a special sensor is attached under the anti-buckling support, the friction force can be measured and subtracted from the stress signal, leaving only the stress-strain response of the material under investigation. In this study, two materials were investigated during incremental step and variable loading tests: The aluminium alloy AlMgSi0.5 and a biodegradable polylactide. Full article

Electrowetting on dielectric (EWOD) devices were fabricated using two hydrophobic organic fluoropolymers, comprising CYTOP (a product name) having different chemical structures only at the terminal functional groups. These devices were subsequently characterized by applying a range of direct current (DC) voltages. The data demonstrated that the EWOD performance was dramatically improved upon incorporating a CYTOP polymer having highly polar terminal functional groups, as compared to a polymer having terminal groups with lower polarity. The new finding about the positive effect of highly polar terminal functional groups on the enhancement of EWOD was exhibited through various careful experiments, changing only the quantitative amount of polar terminal functional groups while keeping other factors constant (thickness, substrate, etc.). Full article

With robots becoming closer to humans in recent years, human-friendly robots made of soft materials provide a new line of research interests. We designed and developed a soft robot that can move via self-deformation toward the practical application of monitoring children and the elderly on a daily basis. The robot’s structure was built out of flexible frames, which are bending-type pneumatic artificial muscles (BPAMs). We first provide a description and discussion on the nature of BPAM, followed by static characteristics experiment. Although the BPAM theoretical model shares a similar tendency with the experimental results, the actual BPAMs moved along the depth direction. We then proposed and demonstrated an effective locomotion method for the robot and calculated its locomotion speed by measuring its drive time and movement distance. Our results confirmed the reasonability of the robot’s speed for monitoring children and the elderly. Nevertheless, during the demonstration, some BPAMs were bent sharply by other activated BPAMs as the robot was driving, leaving a little damage on these BPAMs. This will be addressed in our future work. Full article

Seamless location awareness is considered a cornerstone in the successful deployment of the Internet of Things (IoT). Support for IoT devices in indoor positioning platforms and, vice versa, availability of indoor positioning functions in IoT platforms, are however still in their early stages, posing a significant challenge in the study and research of the interaction of indoor positioning and IoT. This paper proposes a new indoor positioning platform, called ThingsLocate, that fills this gap by building upon the popular and flexible ThingSpeak cloud service for IoT, leveraging its data input and data processing capabilities and, most importantly, its native support for cloud execution of Matlab code. ThingsLocate provides a flexible, user-friendly WiFi fingerprinting indoor positioning service for IoT devices, based on Received Signal Strength Indicator (RSSI) information. The key components of ThingsLocate are introduced and described: RSSI channels used by IoT devices to provide WiFi RSSI data, an Analysis app estimating the position of the device, and a Location channel to publish such estimate. A proof-of-concept implementation of ThingsLocate is then introduced, and used to show the possibilities offered by the platform in the context of graduate studies and academic research on indoor positioning for IoT. Results of an experiment enabled by ThingsLocate with limited setup and no coding effort are presented, focusing on the impact of using different devices and different positioning algorithms on positioning accuracy. Full article

The development of magnetic photonic crystals (MPC) has been a rapidly evolving research area since the late 1990s. Magneto-optic (MO) materials and the techniques for their characterization have also continually undergone functional and property-related improvements. MPC optimization is a feature-rich Windows software application designed to enable researchers to analyze the optical and magneto-optical spectral properties of multilayers containing gyrotropic constituents. We report on a set of computational algorithms which aim to optimize the design and the optical or magneto-optical spectral analysis of 1D MPC, together with a Windows software implementation. Relevant material property datasets (e.g., the spectral dispersion data for the refractive index, absorption, and gyration) of several important optical and MO materials are included, enabling easy reproduction of the previously published results from the field of MPC-based Faraday rotator development, and an effective demonstration-quality introduction of future users to the multiple features of this package. We also report on the methods and algorithms used to obtain the absorption coefficient spectral dispersion datasets for new materials, where the film thickness, transmission spectrum, and refractive index dispersion function are known. Full article

Formaldehyde is utilized for the preservation of materials due to its strong bactericidal effects. As formaldehyde is also a harmful substance that causes health hazards, the quantitative monitoring of formaldehyde in natural and living environments is desirable. For the rapid and easy detection of formaldehyde, in this study we applied an organic field-effect transistor (OFET)-based sensor that can function as a potentiometric device for electrochemical measurements. A polyion-complex gel of formaldehyde dehydrogenase (FDH) and chitosan (CT) was constructed on a gold electrode. When the FDH/CT gel-coated electrode was connected to an OFET device it could detect formaldehyde in an aqueous solution, in which the amino groups of chitosan would protonate during the enzymatic reaction. The limit of detection was calculated to be 3.1 µM (93 ppb), demonstrating the applicability of the film-type OFET sensor to environmental monitoring. Full article

In this paper, a new learning tool is proposed to train professional figures, such as entrepreneurs, engineers, and technicians, who need to improve their skills in the field of Internet of Energy. The proposed tool aims to cover the lack of experimental knowledge on new energy systems and to layer proper skills, which are useful to deal with challenges required by smart energy management in the new complex distributed configuration of the electric power systems, characterized by demand response services. This tool is based on a small-scale laboratory demonstrator, representative of a smart rural house, equipped with a measurement and control system. This demonstrator can be remotely accessed, through web server applications based on a low cost single-board computer. Trainers can have direct experience on the main concepts related to smart grids, renewable energy sources, electrochemical storage systems, and electric vehicles, through the use of the proposed tool managed by the web software interface. Full article