Editor’s Choice Articles

A fall of an elderly person often leads to serious injuries or even death. Many falls occur in the home environment and remain unrecognized. Therefore, a reliable fall detection is absolutely necessary for a fast help. Wrist-worn accelerometer based fall detection systems are developed, but the accuracy and precision are not standardized, comparable, or sometimes even known. In this work, we present an overview about existing public databases with sensor based fall datasets and harmonize existing wrist-worn datasets for a broader and robust evaluation. Furthermore, we are analyzing the current possible recognition rate of fall detection using deep learning algorithms for mobile and embedded systems. The presented results and databases can be used for further research and optimizations in order to increase the recognition rate to enhance the independent life of the elderly. Furthermore, we give an outlook for a convenient application and wrist device. Full article

This paper scrutinized hydraulic fracturing applications mainly in the United States with regard to both groundwater and surface water contamination with the purpose of bringing forth objective analysis of research findings. Results from previous studies are often unconvincing due to the incomplete database of chemical additives; after and before well-founded water samples to define the change in parameters; and specific sources of water pollution in a particular region. Nonetheless, there is a superior chance of both surface and groundwater contamination induced by improper and less monitored wastewater disposal and management practices. This report has documented systematic evidence for total dissolved solids, salinity, and methane contamination regarding drinking water correlated with hydraulic fracturing. Methane concentrations were found on an average rate of 19.2 mg/L, which is 17 times higher than the acceptance rate and the maximum value was recorded as 64.2 mg/L near the active hydraulic fracturing drilling and extraction zones than that of the nonactive sites (1.1 mg/L). The concentration of total dissolved solids (350 g/L) was characterized as a voluminous amount of saline wastewater, which was quite unexpectedly high. The paper concludes with plausible solutions that should be implemented to avoid further contamination. Full article

Steady State Visual Evoked Potential (SSVEP) methods for brain–computer interfaces (BCI) are popular due to higher information transfer rate and easier setup with minimal training, compared to alternative methods. With precisely generated visual stimulus frequency, it is possible to translate brain signals into external actions or signals. Traditionally, SSVEP data is collected from the occipital region using electrodes with or without gel, normally mounted on a head cap. In this experimental study, we develop an in-ear electrode to collect SSVEP data for four different flicker frequencies and compare against occipital scalp electrode data. Data from five participants demonstrates the feasibility of in-ear electrode based SSVEP, significantly enhancing the practicability of wearable BCI applications. Full article

An environmental chamber is a specialistic device used for testing effects of given controlled conditions on a variety of objects. In case of plant growth chambers, the conditions are controlled usually for plant cultivation and propagation or botanical examination undertaken on living plant material. The aim of the project was to design and build a prototype of a desktop device with a control system capable of being used as a chamber supporting plant cultivation and propagation processes by the means of partial automation of environment control. The conditions controlled in the chamber are based on the environmental requirements of plant genera, such as Heliamphora, Drosera, Orectanthe, Cyrilla, Stegolepis, Maguireothamnus, or Utricularia. These plants occur naturally in the Guiana Highlands region of Venezuela, Brazil, and Guyana, especially around the upper parts of table-shaped mountain massifs called tepuis. The chamber was designed to simulate some of the peculiar natural factors and phenomena occurring in the high-tepui and surrounding mid-elevation wetland habitats, being the most significant for amateur-level plant cultivation, keeping the design as simple and low cost as possible. It was proven on the basis of the results of several tests made during the evaluation phase that the designed prototype of the chamber operates in a satisfying way, providing basic functionality matching the base assumptions. Full article

This work compares two design methodologies, emulating both AgCl electrode and skin tissue Cole models for testing and verification of electrical bio-impedance circuits and systems. The models are based on fractional-order elements, are implemented with active components, and capture bio-impedance behaviors up to 10 kHz. Contrary to passive-elements realizations, both architectures using analog filters coupled with adjustable transconductors offer tunability of the fractional capacitors’ parameters. The main objective is to build a tunable active integrated circuitry block that is able to approximate the models’ behavior and can be utilized as a Subject Under Test (SUT) and electrode equivalent in bio-impedance measurement applications. A tetrapolar impedance setup, typical in bio-impedance measurements, is used to demonstrate the performance and accuracy of the presented architectures via Spectre Monte-Carlo simulation. Circuit and post-layout simulations are carried out in 90-nm CMOS process, using the Cadence IC suite. Full article

An equilibrium problem of the Kirchhoff–Love plate containing a nonhomogeneous inclusion is considered. It is assumed that elastic properties of the inclusion depend on a small parameter characterizing the width of the inclusion $\epsilon$ as ${\epsilon }^N$ with $N<1$. The passage to the limit as the parameter $\epsilon$ tends to zero is justified, and an asymptotic model of a plate containing a thin inhomogeneous hard inclusion is constructed. It is shown that there exists two types of thin inclusions: rigid inclusion ($N<-1$) and elastic inclusion ($N=-1$). The inhomogeneity disappears in the case of $N\in (-1,1)$. Full article

Nonlinear free vibrations of functionally graded porous Bernoulli–Euler nano-beams resting on an elastic foundation through a stress-driven nonlocal elasticity model are studied taking into account von Kármán type nonlinearity and initial geometric imperfection. By using the Galerkin method, the governing equations are reduced to a nonlinear ordinary differential equation. The closed form analytical solution of the nonlinear natural flexural frequency is then established using the Hamiltonian approach to nonlinear oscillators. Several comparisons with existing models in the literature are performed to validate the accuracy and reliability of the proposed approach. Finally, a numerical investigation is developed in order to analyze the effects of the gradient index coefficient, porosity volume fraction, initial geometric imperfection, and the Winkler elastic foundation coefficient, on the nonlinear flexural vibrations of metal–ceramic FG porous Bernoulli–Euler nano-beams. Full article

Braking conditions are a fundamental issue for the railway and have been a limiting factor in network capacity and timetabling. Leaf fall, especially during the autumn season, creates low-adhesion problems on railways, causing braking problems for trains. To address the requirements of the novel plasma industrial applications towards environmental applications, this work developed and tested a 2.45 GHz microwave atmospheric pressure plasma system for in situ removal of the third body layer deposited onto the railway so as to improve braking. The plasma reactor consisted of a 15 kW, 2.45 GHz magnetron-based microwave generator and a plasma reactor (dielectric tube placed in a TE01 monomode microwave cavity); the atmospheric plasma ignited and sustained at different power levels (2–15 kW) in different gases (nitrogen, argon) as well as mixtures of these gases with reactive molecules (water, oxygen) was jetted directly onto the railhead as to change the conditions for the wheel–rail interface. This technology is hoped to be a game-changer in enabling predictable and optimized braking on the railway network. Challenges encountered during the demonstration phase are discussed. Subsequent work should validate the results on a working railway line during the autumn season. Full article

Three-dimensional printing (3DP) is at the forefront of the disruptive innovations adding a new dimension in the material fabrication process with numerous design flexibilities. Especially, the ability to reinforce the plastic matrix with nanofiber, microfiber, chopped fiber and continuous fiber has put the technology beyond imagination in terms of multidimensional applications. In this technical paper, fiber and polymer filaments used by the commercial 3D printers to develop fiber-reinforced composites are characterized to discover the unknown manufacturing specifications such as fiber–polymer distribution and fiber volume fraction that have direct practical implications in determining and tuning composites’ properties and their applications. Additionally, the capabilities and limitations of 3D printing software to process materials and control print parameters in relation to print quality, structural integrity and properties of printed composites are discussed. The work in this paper aims to present constructive evaluation and criticism of the current technology along with its pros and cons in order to guide prospective users and 3D printing equipment manufacturers on improvements, as well as identify the potential avenues of development of the next generation 3D printed fiber-reinforced composites. Full article

This work is devoted to researching the tool electrode behavior and wear under discharge pulses at electrical discharge machining. The experiments were conducted on the workpieces of 12Kh18N10T (AISI 321) chrome-nickel anti-corrosion steel and D16 (AA 2024) duralumin by a 0.25-mm-diameter CuZn35 brass tool in a deionized water medium. The developed diagnostic and monitoring mean based on acoustic emission registered the oscillations accompanying machining at 4–8 kHz. The obtained workpiece and non-profiled tool surfaces were investigated by optical and scanning electron microscopy. Calculated volumetric and mass removal rates showed the difference in the character of wear at roughing and finishing. It was shown that interaction between material components in anti-corrosion steel machining had an explosive character between Zn of brass and Ni of steel at a micron level and formed multiple craters of 30–100 µm. The secondary structure and topology of worn tool surfaces were caused by material sublimation, chemical interaction between material components at high heat (10,000 °C), explosive deposition of the secondary structure. Acoustic diagnostics adequately registered the character of interaction. The observed phenomena at the submicron level and microstructure of the obtained surfaces provide grounding on the nature of material interactions and electrical erosion wear fundamentals. Full article

Hydrogels, swellable hydrophilic polymer networks fabricated through chemical cross-linking or physical entanglement are increasingly utilized in various biomedical applications over the past few decades. Hydrogel-based microparticles, dressings and microneedle patches have been explored to achieve safe, sustained and on-demand therapeutic purposes toward numerous skin pathologies, through incorporation of stimuli-responsive moieties and therapeutic agents. More recently, these platforms are expanded to fulfill the diagnostic and monitoring role. Herein, the development of hydrogel technology to achieve diagnosis and monitoring of pathological skin conditions are highlighted, with proteins, nucleic acids, metabolites, and reactive species employed as target biomarkers, among others. The scope of this review includes the characteristics of hydrogel materials, its fabrication procedures, examples of diagnostic studies, as well as discussion pertaining clinical translation of hydrogel systems. Full article

In this paper a simplified hardware implementation of a CNN softmax-like layer is proposed. Initially the softmax activation function is analyzed in terms of required numerical accuracy and certain optimizations are proposed. A proposed adaptable hardware architecture is evaluated in terms of the introduced error due to the proposed softmax-like function. The proposed architecture can be adopted to the accuracy required by the application by retaining or eliminating certain terms of the approximation thus allowing to explore accuracy for complexity trade-offs. Furthermore, the proposed circuits are synthesized in a 90 nm 1.0 V CMOS standard-cell library using Synopsys Design Compiler. Comparisons reveal that significant reduction is achieved in area × delay and power × delay products for certain cases, respectively, over prior art. Area and power savings are achieved with respect to performance and accuracy. Full article

This article reports a study aiming to determine the perceptions of older adults needing formal care about the usefulness, satisfaction, and ease of use of CaMeLi, a virtual companion based on an embodied conversational agent, and the perceptions of formal caregivers about the potential of virtual companions to support care provision. An observational study involving older adults needing formal care was conducted to assess CaMeLi using a multi-method approach (i.e., an auto-reported questionnaire—the Usefulness, Satisfaction, and Ease of use questionnaire; a scale for the usability assessment based on the opinion of observers—the International Classification of Functioning Disability and Health-based Usability Scale; and critical incident registration). Moreover, a focus group was conducted to collect data regarding the perceived utility of virtual companions to support care provision. The observational study was conducted with 46 participants with an average age of 63.6 years, and the results were associated with a high level of usefulness, satisfaction, and ease of use of CaMeLi. Furthermore, the focus group composed of four care providers considered virtual companions a promising solution to support care provision and to prevent loneliness and social isolation. The results of both the observational study and the focus group revealed good perceptions regarding the role of virtual companions to support the care provision for older adults. Full article

This paper presents a statistical model for maximum ratio combining (MRC) receivers in Rayleigh fading channels enabled with a temporal combining process. This means that the receiver effectively combines spatial and temporal branch components. Therefore, the signals that will be processed by the MRC receiver are collected not only across different antennas (space), but also at different instants of time. This suggests the use of a retransmission, repetition or space-time coding algorithm that forces the receiver to store signals in memory at different instants of time. Eventually, these stored signals are combined after a predefined or dynamically optimized number of time-slots or retransmissions. The model includes temporal correlation features in addition to the space correlation between the signals of the different components or branches of the MRC receiver. The derivation uses a frequency domain approach (using the characteristic function of the random variables) to obtain closed-form expressions of the statistics of the post-processing signal-to-noise ratio (SNR) under the assumption of equivalent correlation in time and equivalent correlation in space. The described methodology paves the way for the reformulation of other statistical functions as a frequency-domain polynomial root analysis problem. This is opposed to the infinite series approach that is used in the conventional methodology using directly the probability density function (PDF). The results suggest that temporal diversity is a good complement to receivers with limited spatial diversity capabilities. It is also shown that this additional operation could be maximized when the temporal diversity is adaptive (i.e., activated by thresholds of SNR), thus leading to a better resource utilization. Full article

Work is part of our wellbeing and a key driver of a person’s health. Pilots need to be fit for duty and aware of risks that compromise their health/wellbeing. Recent studies suggest that work-related stress (WRS) impacts on pilot health and wellbeing, performance, and flight safety. This paper reports on the advancement of new tools for pilots and airlines to support the management of WRS and wellbeing. This follows from five phases of stakeholder evaluation research and analysis. Existing pre-flight checklists should be extended to enable the crew to evaluate their health and wellbeing. New checklists might be developed for use by pilots while off duty supporting an assessment of (1) their biopsychosocial health status and (2) how they are coping. This involves the advancement of phone apps with different wellness functions. Pending pilot consent, data captured in these tools might be shared in a de-identified format with the pilot’s airline. Existing airline safety management systems (SMS) and flight rostering/planning systems might be augmented to make use of this data from an operational and risk/safety management perspective. Fatigue risk management systems (and by implication airline rostering/flight planning systems) need to be extended to consider the relationship between fatigue risk and the other dimensions of a pilot’s wellbeing. Further, pending permission, pilot data might be shared with airline employee assistance program (EAP) personnel and aeromedical examiners. In addition, new training formats should be devised to support pilot coping skills. The proposed tools can support the management of WRS and wellbeing. In turn, this will support performance and safety. The pilot specific tools will enable the practice of healthy behaviors, which in turn strengthens a pilot’s resistance to stress. Healthy work relates to the creation of positive wellbeing within workplaces and workforces and has significant societal implications. Pilots face many occupational hazards that are part of their jobs. Pilots, the aviation industry, and society should recognize and support the many activities that contribute to positive wellbeing for pilots. Social justice is a basic premise for quality of employment and quality of life. Full article

The work was devoted to the study of the effectiveness of the application of multi-component coatings, TiN–Al/TiN, TiN–AlTiN/SiN, and CrTiN–AlTiN–AlTiCrN/SiN, obtained by cathodic arc deposition to increase the wear resistance of 6WH10F carbide end mills in trochoidal milling of titanium alloy. The surface morphology of the tool with coatings was studied using scanning electron microscopy, and surface roughness texture was estimated. Microhardness and elastic modulus of the coated carbide tool surface layer were determined by nanoindentation. The process of sticking titanium to the working surface of the tool and quantitative evaluation of end mill wear with multi-component coatings at the trochoidal strategy of milling titanium alloy was studied. The CrTiN–AlTiN–AlTiCrN/SiN coating showed the maximum value of the plasticity index at the level of 0.12. The maximum effect of reducing the wear rate was achieved when using a tool with a CrTiN –AlTiN–AlTiCrN/SiN coating when the operating time to failure of end mills was increased by 4.6 times compared to samples without coating, by 1.4 times compared with TiN–Al/TiN coating and 1.15 times compared with TiN–AlTiN/SiN coating. Full article

Information dissemination is an integral part of modern networking environments, such as Wireless Sensor Networks (WSNs). Probabilistic flooding, a common epidemic-based approach, is used as an efficient alternative to traditional blind flooding as it minimizes redundant transmissions and energy consumption. It shares some similarities with the Susceptible-Infected-Recovered (SIR) epidemic model, in the sense that the dissemination process and the epidemic thresholds, which achieve maximum coverage with the minimum required transmissions, have been found to be common in certain cases. In this paper, some of these similarities between probabilistic flooding and the SIR epidemic model are identified, particularly with respect to the epidemic thresholds. Both of these epidemic algorithms are experimentally evaluated on a university campus testbed, where a low-cost WSN, consisting of 25 nodes, is deployed. Both algorithm implementations are shown to be efficient at covering a large portion of the network’s nodes, with probabilistic flooding behaving largely in accordance with the considered epidemic thresholds. On the other hand, the implementation of the SIR epidemic model behaves quite unexpectedly, as the epidemic thresholds underestimate sufficient network coverage, a fact that can be attributed to implementation limitations. Full article

The aim of this paper is to give an overview of the recent advancements in the Unsupervised Domain Adaptation (UDA) of deep networks for semantic segmentation. This task is attracting a wide interest since semantic segmentation models require a huge amount of labeled data and the lack of data fitting specific requirements is the main limitation in the deployment of these techniques. This field has been recently explored and has rapidly grown with a large number of ad-hoc approaches. This motivates us to build a comprehensive overview of the proposed methodologies and to provide a clear categorization. In this paper, we start by introducing the problem, its formulation and the various scenarios that can be considered. Then, we introduce the different levels at which adaptation strategies may be applied: namely, at the input (image) level, at the internal features representation and at the output level. Furthermore, we present a detailed overview of the literature in the field, dividing previous methods based on the following (non mutually exclusive) categories: adversarial learning, generative-based, analysis of the classifier discrepancies, self-teaching, entropy minimization, curriculum learning and multi-task learning. Novel research directions are also briefly introduced to give a hint of interesting open problems in the field. Finally, a comparison of the performance of the various methods in the widely used autonomous driving scenario is presented. Full article

Monitoring of fetal electrocardiogram (fECG) would provide useful information about fetal wellbeing as well as any abnormal development during pregnancy. Recent advances in flexible electronics and wearable technologies have enabled compact devices to acquire personal physiological signals in the home setting, including those of expectant mothers. However, the high noise level in the daily life renders long-entrenched challenges to extract fECG from the combined fetal/maternal ECG signal recorded in the abdominal area of the mother. Thus, an efficient fECG extraction scheme is a dire need. In this work, we intensively explored various extraction algorithms, including template subtraction (TS), independent component analysis (ICA), and extended Kalman filter (EKF) using the data from the PhysioNet 2013 Challenge. Furthermore, the modified data with Gaussian and motion noise added, mimicking a practical scenario, were utilized to examine the performance of algorithms. Finally, we combined different algorithms together, yielding promising results, with the best performance in the F1 score of 92.61% achieved by an algorithm combining ICA and TS. With the data modified by adding different types of noise, the combination of ICA–TS–ICA showed the highest F1 score of 85.4%. It should be noted that these combined approaches required higher computational complexity, including execution time and allocated memory compared with other methods. Owing to comprehensive examination through various evaluation metrics in different extraction algorithms, this study provides insights into the implementation and operation of state-of-the-art fetal and maternal monitoring systems in the era of mobile health. Full article

One of the promising processing methods for non-conductive structural and functional ceramics based on ZrO₂, Al₂O₃, and Si₃N₄ systems is electrical discharge machining with the assistance of an auxiliary electrode that can be presented in the form of conductive films with a thickness up to 4–10 µm or nanoparticles - granules, tubes, platelets, multidimensional particles added in the working zone as a free poured powder the proper concentration of which can be provided by ultrasound emission or by dielectric flows or as conductive additives in the structure of nanocomposites. However, the described experimental approaches did not reach the production market and industry. It is related mostly to the chaotic development of the knowledge and non-systematized data in the field when researchers often cannot ground their choice of the material for auxiliary electrodes, assisting powders, or nano additives or they cannot explain the nature of processes that were observed in the working tank during experiments when their results are not correlated to the measured specific electrical conductivity of the electrodes, particles, ceramic workpieces or nanocomposites but depends on something else. The proposed review includes data on the main electrophysical and chemical properties of the components in the presence of heat when the temperature in the interelectrode gap reaches 10,000 °C, and the systematization of data on ceramic pressing methods, including spark plasma sintering, the chemical reactions that occur in the interelectrode gap during sublimation of primary (brass and copper) and auxiliary electrodes made of transition metals Ti, Cr, Co, and carbon, auxiliary electrodes made of metals with low melting point Zn, Ag, Au, Al, assisting powder of oxide ceramics TiO₂, CeO₂, SnO₂, ITO, conductive additives Cu, W, TiC, WC, and components of Al₂O₃ and Zr₂O workpieces in interaction with the dielectric fluid - water and oil/kerosene medium. Full article

Today, the current trends of manufacturing are towards the adaptation and implementation of smart manufacturing, which is a new initiative to turn the traditional factories into profitable innovation facilities. However, the concept and technologies are still in a state of infancy, since many manufacturers around the world are not fully knowledgeable about the benefits of smart manufacturing compared to their current practices. This article reviews several aspects of smart manufacturing and introduces its advantages in terms of energy-saving and production efficiency. This article also points out that some areas need further research so that smart manufacturing can be shaped better. Full article

Juvenile idiopathic arthritis (JIA) causes inflammation of the joints, and it is frequently associated with their pain and stiffness. Its timely diagnosis is important to avoid its progressive damage to the bones and cartilage. Increases in the joint’s temperature and redness could be indicators of active JIA, hence their accurate quantification could assist with diagnosis. Thermal and visual images of the knees in 20 JIA participants (age: mean = 11.2 years, standard deviation = 2.3 years) were studied. The median temperature of knees with active inflammation was 3.198% higher than that of inactive knees. This difference, examined by a Wilcoxon signed-rank test, was statistically significant (p = 0.0078). In six out of the eight participants who had one active inflamed knee, thermal imaging identified the corresponding knee as warmer. In 16 out of 20 participants, the knee identified as warmer by thermal imaging was also identified as having a greater colour change by visual imaging as compared to their respective reference regions. The devised methods could accurately quantify the colour and temperature of the knees. It was concluded that thermal and visual imaging methods can be valuable in examining JIA. Further studies involving a larger number of participants and more detailed explorations would be needed prior to clinical application. Full article

Controlling the evaporation process of a droplet is of the utmost importance for a number of technologies. Also, along with the advances of microfabrication, micropatterned surfaces have emerged as an important technology platform to tune the wettability and other surface properties of various fundamental and applied applications. Among the geometrical parameters of these micropatterns, it is of great interest to investigate whether the arrangement of the patterns would affect the evaporation process of a sessile liquid droplet. To address this question, we fabricated four microhole arrays with different arrangements, quantified by the parameter of “eccentricity”. The results suggested that, compared to smooth substrates, the evaporation mode was not only affected by engineering the microhole arrays, but also by the eccentricity of these micropatterns. The values of contact angle hysteresis (CAH) were used to quantify and test this hypothesis. The CAH could partially explain the different evaporation modes observed on the microhole arrays with zero and non-zero values of eccentricity. That is, on microhole arrays with zero eccentricity, CAH of water droplets was comparatively low (less than 20 $°$ ). Consistently, during the evaporation, around 60% of the life span of the droplet was in the mixed evaporation mode. Increasing the eccentricity of the microhole arrays increases the values of CAH to above 20 $°$ . Unlike the increasing trend of CAH, the evaporation modes of sessile droplets on the microhole array with non-zero values of eccentricity were almost similar. Over 75% of the life span of droplets on these surfaces was in constant contact line (CCL) mode. Our findings play a significant role in any technology platform containing micropatterned surfaces, where controlling the evaporation mode is desirable. Full article

The rapid evolution of smart assisted living operations in combination with the blooming of commercial robots calls for the use of robotic based systems. Specifically, certain circumstances such as the handling of critical, contagious virus outbreaks like the recent novel Coronavirus epidemic can be benefited by an assisting mobile robot system controlled remotely, complementing measures like the isolation of patients from medical stuff. Within this context, the robotic-based solution to be employed needs to be easy to deploy, able to manufacture with low cost, and able to operate with ease by non-trained personnel. Also, to address the needs of existing hospitals, traditional or smart ones, as well as the temporary risk management facilities in, for example, quarantined cities, ease of integration in terms of size and infrastructure requirements is a must. In this work, the design and implementation of a robotic chassis bearing an arm manipulator is presented, addressing all these needs efficiently. Special attention has been given to the ease of teleoperation with minimal need for equipment and expertise, utilizing a Leap Motion virtual reality sensor which outweighs Microsoft’s Kinect capabilities. Furthermore, a reconfigurable hardware and software integrated system has been used to control the communication, algorithm processing and motion control utilizing a Xilinx Zynq system on chip (SoC). Full article

The present study aimed to investigate the psychosocial impacts of large-scale solar (LSS) power projects. There were 225 participants (n = 109 women, n = 3 did not indicate gender) participated in our study by completing a series of questionnaires. We found that participants who lived farther from the LSS power project location and those who viewed the project as being impactful were optimistic about the benefits LSS power projects could bring. Our participants also demonstrated support for renewable energy development in Malaysia. These findings may provide important implications for the implementation and execution of LSS power projects and policies. Full article

The impact of process variations on circuit performance has become more critical with the technological scaling, and the increasing level of integration of integrated circuits. The degradation of the performance of the circuit means economic losses. In this paper, we propose an efficient statistical gate-sizing methodology for improving circuit speed in the presence of independent intra-die process variations. A path selection method, a heuristic, two coarse selection metrics, and one fine selection metric are part of the new proposed methodology. The fine metric includes essential concepts like the derivative of the standard deviation of delay, a path segment analysis, the criticality, the slack-time, and area. The proposed new methodology is applied to ISCAS Benchmark circuits. The average percentage of optimization in the delay is 12%, the average percentage of optimization in the delay standard deviation is 27.8%, the average percentage in the area increase is less than 5%, and computing time is up to ten times less than using analytical methods like Lagrange Multipliers. Full article

This work describes a Mixed Reality application useful to modify and cut virtual objects. A digital simulation of surgical operations is presented. Following this approach, surgeons can test all the designed solutions of the preoperative stage in a Mixed Reality environment. High precision in surgery applications can be achieved thanks to the new methodology. The presented solution is hands free and does not need the use of a mouse or computer’s keyboard: it is based on HoloLens, Leap Motion device and Unity. A new cutting algorithm has been developed in order to handle multiple objects and speed up the cut with complex meshes and preserve geometry quality. A case study presents the cut of several bones in order to simulate surgeon’s operations. A reduction in cut time compared to the original method is noticed, together with a high flexibility of the tool and a good fidelity of the geometry. Moreover, all the object fragments generated from the algorithm are available for manipulation and new cuts. Full article

The convolutional neural network (CNN) algorithm is one of the efficient techniques to recognize hand gestures. In human–computer interaction, a human gesture is a non-verbal communication mode, as users communicate with a computer via input devices. In this article, 3D micro hand gesture recognition disparity experiments are proposed using CNN. This study includes twelve 3D micro hand motions recorded for three different subjects. The system is validated by an experiment that is implemented on twenty different subjects of different ages. The results are analysed and evaluated based on execution time, training, testing, sensitivity, specificity, positive and negative predictive value, and likelihood. The CNN training results show an accuracy as high as 100%, which present superior performance in all factors. On the other hand, the validation results average about 99% accuracy. The CNN algorithm has proven to be the most accurate classification tool for micro gesture recognition. Full article

Internet-related electricity consumption is rising rapidly as global Internet users spend more than 6.5 h per day online. Open source ad blockers have the potential to reduce the time and thus electricity spent using computers by eliminating ads during Internet browsing and video streaming. In this study, three open source ad blockers are tested against a no-ad blocker control. Page load time is recorded for browsing a representative selection of the globally most-accessed websites, and the time spent watching ads on videos is quantified for both trending and non-trending content. The results show that page load time dropped 11% with AdBlock+, 22.2% with Privacy Badger, and 28.5% with uBlock Origin. Thus, uBlock Origin has the potential to save the average global Internet user more than 100 h annually. The energy conserved if everyone in the United States used the open source ad blocker would save over 36 Americans lives per year if it were to offset coal-fired electricity generated-based pollution. In the United States, if all Internet users enabled Privacy Badger on their computers, Americans would save more than $91 million annually. Globally, uBlock Origin could save consumers more than $1.8 billion/year. Open source ad blockers are a potentially effective technology for energy conservation. Full article

The concept of the quantified self has gained popularity in recent years with the hype of miniaturized gadgets to monitor vital fitness levels. Smartwatches or smartphone apps and other fitness trackers are overwhelming the market. Most aerobic exercises such as walking, running, or cycling can be accurately recognized using wearable devices. However whole-body exercises such as push-ups, bridges, and sit-ups are performed on the ground and thus cannot be precisely recognized by wearing only one accelerometer. Thus, a floor-based approach is preferred for recognizing whole-body activities. Computer vision techniques on image data also report high recognition accuracy; however, the presence of a camera tends to raise privacy issues in public areas. Therefore, we focus on combining the advantages of ubiquitous proximity-sensing with non-optical sensors to preserve privacy in public areas and maintain low computation cost with a sparse sensor implementation. Our solution is the ExerTrack, an off-the-shelf sports mat equipped with eight sparsely distributed capacitive proximity sensors to recognize eight whole-body fitness exercises with a user-independent recognition accuracy of 93.5% and a user-dependent recognition accuracy of 95.1% based on a test study with 9 participants each performing 2 full sessions. We adopt a template-based approach to count repetitions and reach a user-independent counting accuracy of 93.6%. The final model can run on a Raspberry Pi 3 in real time. This work includes data-processing of our proposed system and model selection to improve the recognition accuracy and data augmentation technique to regularize the network. Full article

The purpose of this paper was to propose a complete analysis and parameter estimations of a new simplified and highly nonlinear hafnium dioxide memristor model that is appropriate for high-frequency signals. For the simulations; a nonlinear window function previously offered by the author together with a highly nonlinear memristor model was used. This model was tuned according to an experimentally recorded current–voltage relationship of a HfO₂ memristor. This study offered an estimation of the optimal model parameters using a least squares algorithm in SIMULINK and a methodology for adjusting the model by varying its parameters overbroad ranges. The optimal values of the memristor model parameters were obtained after minimizing the error between the experimental and simulated current–voltage characteristics. A comparison of the obtained errors between the simulated and experimental current–voltage relationships was made. The error derived by the optimization algorithm was a little bit lower than that obtained by the used methodology. To avoid convergence problems; the step function in the considered model was replaced by a differentiable tangent hyperbolic function. A PSpice library model of the HfO₂ memristor based on its mathematical model was created. The considered model was successfully applied and tested in a multilayer memristor neural network with bridge memristor–resistor synapses Full article

Presently, cryptographic hash functions play a critical role in many applications, such as digital signature systems, security communications, protocols, and network security infrastructures. The new standard cryptographic hash function is Secure Hash Algorithm 3 (SHA-3), which is not vulnerable to attacks. The Keccak algorithm is the winner of the NIST competition for the adoption of the new standard SHA-3 hash algorithm. In this work, we present hardware throughput optimization techniques for the SHA-3 algorithm using the Very High Speed Integrated Circuit Hardware Description Language (VHDL) programming language for all output lengths in the Keccak hash function (224, 256, 384 and 512). Our experiments were performed with the Nios II processor on the FPGA Arria 10 GX (10AX115N2P45E1SG). We applied two architectures, one without custom instruction and one with floating point hardware 2. Finally, we compare the results with other existing similar designs and found that the proposed design with floating point 2 optimizes throughput (Gbps) compared to existing FPGA implementations. Full article

In this paper, two implementations of reconfigurable bandwidth bandpass filters (BPFs) are demonstrated both operating at a fixed center frequency of 2.4 GHz. The proposed reconfigurable bandwidth filters are based on a square ring resonator loaded with λ_g/4 open-ended stubs that are permanently connected to the ring and converted to either 3λ_g/4 open-ended stubs or λ_g/2 short-ended stubs by means of positive-intrinsic-negative(PIN) diodes to implement two reconfigurable bandwidth states for each case. Due to the symmetrical nature of the design, even- and odd-mode analysis is used to derive the closed-form to describe the reconfigurable filters’ behavior. The switching between narrowband and wideband is achieved using PIN diodes. In the first implementation (λ_g/4 open-ended stubs to 3λ_g/4 open-ended stubs), a reconfigurable bandwidth bandpass filter is proposed where additional out-of-band transmission zeros are generated by integrating a λ_g/2 open-ended stub at the input port. In the second implementation (λ_g/4 open-ended stubs to λ_g/2 short-ended stubs), further improvement in the upper stopband is achieved by utilizing a pair of parallel coupled lines (PCLs) as feeding lines and a pair of λ_g/4 high impedance short-ended stubs implemented at the input and output ports. To verify the validity of the simulated results, the prototypes of the proposed reconfigurable filters were fabricated. For the first case, measured insertion loss is less than 1.8 dB with a switchable 3-dB fractional bandwidth (FBW) range from 28% to 54%. The measured results for the second case exhibit a low insertion loss of less than 1 dB and a 3-dB fractional bandwidth that can be switched from 34% to 75%, while the center frequency is kept constant at 2.4 GHz in both cases. Full article

In this paper a number of LT Spice simulations have been carried out on an Electrical Impedance Tomography (EIT) system, which includes the whole analog and digital circuitry as well as the subject to be examined (phantom model). The aim of this study is to show how the analog and digital parts, the electrodes and the subject’s physical properties may impact the measurements and the quality of the reconstructed image. This could provide a useful tool for designing an EIT system. Special attention has been given to the current source’s output impedance and swing, to the noise produced by the circuits and to the Analog to Digital Converters (ADCs) resolution and sampling rate. Furthermore, some 3D phantom subjects have been modeled and simulated as equivalent circuits, merged with the EIT simulated hardware, in order to observe how changes on their properties interact with the whole circuitry and affect the final result. Observations show that mirrored current sources with $z_{out}$ > 350 k $\Omega$ and sufficiently high ADC acquisition sampling rate ( $f_{sample}\ge 16f_{in}$ ) can result to accurate impedance measurements and therefore quality image reconstruction within a frequency span of at least 10 to 100 kHz. Moreover, possible hardware failures (electrode disconnections and imbalanced contact impedances) can be detected with a simple examination of the first extracted image and measurement set, so that by direct modification of the reconstruction process, a corrected result can be obtained. Full article

In this work, we propose an algorithm for joint calibration and axes alignment of a 3-axis accelerometer and a 3-axis magnetometer. The proposed algorithm applies when the two sensors are fixed on the same rigid platform. It achieves accurate calibration without requiring any external piece of equipment like a turntable for the accelerometer or Gauss magnetic chamber and Maxwell coils setup for the magnetometer. The efficiency and accuracy of the proposed algorithm are evaluated using experimental data. Full article

Concrete and asphalt are the primary materials used to construct roadways for motor vehicles, paths for pedestrians and bicyclists, and runways for aircraft. Solar Roadways^®, Inc. (SR) proposed a novel solar pavement technology (i.e., solar road panels (SRP)) as an alternative material and energy source. SR performed load, traction, and impact testing to use SRPs in non-critical applications like parking lots. To use SRP in public roads, engineering tests including freeze/thaw, moisture absorption, heavy vehicle, and shear testing were accomplished on “SR3” prototypes. Testing was performed at Marquette University in the Engineering Materials and Structural Testing Laboratory and the SR Pilot Project area. Moisture absorption and freeze/thaw tests showed “SR3” resistant to extreme weather and moisture environments. Heavy vehicle testing revealed no physical damage to the “SR3” after approximately 989,457 equivalent single axle loads were continuously rolled over a prototype pavement. Shear testing was conducted to investigate “SR3” laminate structure properties. In all cases, electrical failure was defined when “SR3” photovoltaic voltage dropped to zero volts. The maximum shear stress and applied torque for “SR3”’ (S/N’s Paver 1, 002B, 007C, and 004B) were 1756 kPa, 1835 kPa, 1643 kPa, 2023 kPa; and 121.2 kN·m, 131.3 kN·m, 117.6 kN·m, 144.8 kN·m, respectively. In addition, the “SR3” “heartbeat” light emitting diode (LED) remained operational (i.e., indicates computer bus traffic) in all phases of shear testing. Overall, the results show “SR3” prototypes to be robust, resilient, and functional when subjected to “real-world” test conditions. Full article

The workloads of Convolutional Neural Networks (CNNs) exhibit a streaming nature that makes them attractive for reconfigurable architectures such as the Field-Programmable Gate Arrays (FPGAs), while their increased need for low-power and speed has established Application-Specific Integrated Circuit (ASIC)-based accelerators as alternative efficient solutions. During the last five years, the development of Hardware Description Language (HDL)-based CNN accelerators, either for FPGA or ASIC, has seen huge academic interest due to their high-performance and room for optimizations. Towards this direction, we propose a library-based framework, which extends TensorFlow, the well-established machine learning framework, and automatically generates high-throughput CNN inference engines for FPGAs and ASICs. The framework allows software developers to exploit the benefits of FPGA/ASIC acceleration without requiring any expertise on HDL development and low-level design. Moreover, it provides a set of optimization knobs concerning the model architecture and the inference engine generation, allowing the developer to tune the accelerator according to the requirements of the respective use case. Our framework is evaluated by optimizing the LeNet CNN model on the MNIST dataset, and implementing FPGA- and ASIC-based accelerators using the generated inference engine. The optimal FPGA-based accelerator on Zynq-7000 delivers 93% less memory footprint and 54% less Look-Up Table (LUT) utilization, and up to 10× speedup on the inference execution vs. different Graphics Processing Unit (GPU) and Central Processing Unit (CPU) implementations of the same model, in exchange for a negligible accuracy loss, i.e., 0.89%. For the same accuracy drop, the 45 nm standard-cell-based ASIC accelerator provides an implementation which operates at 520 MHz and occupies an area of 0.059 mm ${}^2$ , while the power consumption is ∼7.5 mW. Full article

Integrated circuit susceptibility to radiation-induced faults remains a major reliability concern. The continuous downscaling of device feature size and the reduction in supply voltage in CMOS technology tend to worsen the problem. Thus, the evaluation of Soft Error Rate (SER) in the presence of multiple transient faults is necessary, since it remains an open research field. In this work, a Monte-Carlo simulation-based methodology is presented taking into consideration the masking mechanisms and placement information. The proposed SER estimation tool exploits the results of a Single Event Transient (SET) pulse characterization process with HSPICE to obtain an accurate assessment of circuit vulnerability to radiation. A new metric, called Glitch Latching Probability, which represents the impact of the masking effects on a SET, is introduced to identify gate sensitivity and, finally, experimental results on a set of ISCAS’ 89 benchmarks are presented. Full article

In advanced society, the existing building stock has a high demand for stock renovation, which gives existing buildings new lives, rather than building new ones. During the renovation process, it is necessary to simultaneously achieve architectural, facilities, structural, and environmental design in order to accomplish a healthy, comfortable, and energy-saving indoor environment, prevent delays in problem-solving, and achieve a timely feedback process. This study tackled the development of an integrated system for stock renovation by considering computational fluid dynamics (CFD) and mixed reality (MR) in order to allow the simultaneous design of a building plan and thermal environment. The CFD analysis enables simulation of the indoor thermal environment, including the entire thermal change process. The MR system, which can be operated by voice command and operated on head-mounted display (HMD), enables intuitive visualization of the thermal change process and, in a very efficient manner, shows how different renovation projects perform for various stakeholders. A prototype system is developed with Unity3D engine and HoloLens HMD. In the integrated system, a new CFD visualization method generating 3D CFD animation sequence for the MR system is proposed that allows stakeholders to consider the entirety of changes in the thermal environment. Full article

The performance of an underwater optical wireless communication link is investigated by taking into account—for the first time and to the best of our knowledge—the simultaneous influence of the chromatic dispersion, the time jitter and the turbulence effects, by assuming chirped longitudinal Gaussian pulse propagation as information carriers. The estimation procedure is presented and a novel probability density function is extracted in order to describe the irradiance fluctuations at the receiver side. Furthermore, the availability of the link is investigated by means of its probability of fade and various numerical results are presented using typical parameters for the underwater optical wireless communication systems. Full article

The biological activity of chitosan determines its broad application as a biopolymer for non-woven wound dressings fabricated by electrospinning. The electrospinning process is affected by a large number of different factors that complicate its optimization. In the present work, the electrospinning of chitosan lactate was carried out using a needleless technique from water solutions of different compositions. Surface response methodology was used to evaluate the effects of the concentration of chitosan, polyethylene oxide, and ethanol on solution properties, such as viscosity, surface tension, and conductivity, as well as the process characteristics and fiber quality. The viscosity of the spinning solution is determined by the polymer concentration as well as by the interpolymer interactions. The addition of ethanol to the spinning solutions effectively decreases the solution surface tension and conductivity, while increasing the volatility of the solvent, to provide more intense fiber spinning. Atomic force microscopy revealed that the chitosan lactate fibers were obtained without defects and with a narrow thickness distribution. The spinning parameters, voltage, distance between electrodes, and rotation speed of the spinning electrode had insignificant influences on the fiber diameter during needleless electrospinning. Full article

The semantic understanding of a scene is a key problem in the computer vision field. In this work, we address the multi-level semantic segmentation task where a deep neural network is first trained to recognize an initial, coarse, set of a few classes. Then, in an incremental-like approach, it is adapted to segment and label new objects’ categories hierarchically derived from subdividing the classes of the initial set. We propose a set of strategies where the output of coarse classifiers is fed to the architectures performing the finer classification. Furthermore, we investigate the possibility to predict the different levels of semantic understanding together, which also helps achieve higher accuracy. Experimental results on the New York University Depth v2 (NYUDv2) dataset show promising insights on the multi-level scene understanding. Full article

One major topic in the research of path planning of autonomous mobile robots is the fast and efficient coverage of a given terrain. For this purpose, an efficient method for covering a given workspace is proposed, based on chaotic path planning. The method is based on a chaotic pseudo random bit generator that is generated using a modified logistic map, which is used to generate a chaotic motion pattern. This is then combined with an inverse pheromone approach in order to reduce the number of revisits in each cell. The simulated robot under study has the capability to move in four or eight directions. From extensive simulations performed in Matlab, it is derived that motion in eight directions gives superior results. Especially, with the inclusion of pheromone, the coverage percentage can significantly be increased, leading to better performance. Full article

The design of additive manufacturing processes, especially for batch production in industrial practice, is of high importance for the propagation of new additive manufacturing technology. Manual redesign procedures of the additive manufactured parts based on discrete measurement data or numerical meshes are error prone and hardly automatable. To achieve the required final accuracy of the parts, often, various iterations are necessary. To address these issues, a data-driven geometrical compensation approach is proposed that adapts concepts from forming technology. The measurement information of a first calibration cycle of manufactured parts is the basis of the approach. Through non-rigid transformations of the part geometry, a new shape for the subsequent additive manufacturing process was derived in a systematic way. Based on a purely geometrical approach, the systematic portion of part deviations can be compensated. The proposed concept is presented first and was applied to a sample fin-shaped part. The deviation data of three manufacturing cycles was utilised for validation and verification. Full article

Machine learning, especially the GAN (Generative Adversarial Network) model, has been developed tremendously in recent years. Since the NVIDIA Machine Learning group presented the StyleGAN in December 2018, it has become a new way for designers to make machines learn different or similar types of architectural photos, drawings, and renderings, then generate (a) similar fake images, (b) style-mixing images, and (c) truncation trick images. The author both collected and created input image data, and specially made architectural plan and section drawing inputs with a clear design purpose, then applied StyleGAN to train specific networks on these datasets. With the training process, we could look into the deep relationship between these input architectural plans or sections, then generate serialized transformation images (truncation trick images) to form the 3D (three-dimensional) model with a decent resolution (up to 1024 × 1024 × 1024 pixels). Though the results of the 3D model generation are difficult to use directly in 3D spatial modeling, these unexpected 3D forms still could inspire new design methods and greater possibilities of architectural plan and section design. Full article

Bobbin Friction Stir Welding (BFSW) is a thermomechanical process containing severe plastic deformation by mechanical stirring and Dynamic Recrystallization (DRX) during recooling. Here we report the three-dimensional characteristics of the micro-flow patterns within the aluminium weld structure. The Surface topography observations by Atomic Force Microscopy (AFM) show the stirred-induced microstructural evolution where the rearrangement of dislocations at the sub-grain scale, and the subsequent High- and Low-Angle Grain Boundaries (HAGBs, LAGBs) exhibit specific alterations in grain size and morphology of the weld texture. The dislocations interaction in different regions of the weld structure also was observed in correlation to the thermomechanical behaviour of the BFSW process. These micro-flow observations within the weld breadth give a new insight into the thermomechanical characteristics of the FSW process during the stirring action where the plastic flow has a key role in the formation of the weld region distinct from the base metal. Full article

Coatings are pivotal in combating problems of premature component degradation in aggressive industrial environments and constitute a strategic area for continued development. Thermal spray (TS) coatings offer distinct advantages by combining versatility, cost-effectiveness, and the ability to coat complex geometries without constraints of other in-chamber processes. Consequently, TS techniques like high-velocity oxy-fuel (HVOF) and atmospheric plasma spray (APS) are industrially well-accepted. However, they have reached limits of their capabilities while expectations from coatings progressively increase in pursuit of enhanced efficiency and productivity. Two emerging TS variants, namely high-velocity air-fuel (HVAF) and liquid feedstock thermal spraying, offer attractive pathways to realize high-performance surfaces superior to those hitherto achievable. Supersonic HVAF spraying provides highly adherent coatings with negligible porosity and its low processing temperature also ensures insignificant thermal ‘damage’ (oxidation, decarburization, etc.) to the starting material. On the other hand, liquid feedstock derived TS coatings, deposited using suspensions of fine particles (100 nm–5 µm) or solution precursors, permits the production of coatings with novel microstructures and diverse application-specific architectures. The possibility of hybrid processing, combining liquid and powder feedstock, provides further opportunities to fine tune the properties of functional surfaces. These new approaches are discussed along with some illustrative examples. Full article

To connect terminals in a cyber–physical system, large quantities of electrical contacts are used. In order to guarantee a high reliability of the system, the lifetime of the electrical contacts should be very long. Thus, it is of great importance to understand the failure mechanism and then to predict the lifetime of the electrical contacts. For the applications under high thermal and/or mechanical loads, noble plating is a good choice, considering its inertness to oxidation. For noble plating, one of the most critical failure mechanisms is the fretting wear. Wear debris generated in the contact area, acting as the third bodies, will greatly influence the further wear behavior and electrical performance. In this study, the state of the art regarding third bodies is firstly reviewed, and then the influence of the third bodies on the wear and electrical performance is investigated, from the aspects of lifetime and the element distributions in contact area. Finally, an example of prediction of the wear of noble plating is shown with the consideration of the third bodies. Based on this study, by involving the third bodies, the wear of noble plating can be predicted with a higher accuracy. Full article

Until recently, digital fabrication research in architecture has aimed to eliminate manufacturing errors. However, a novel notion has just been established—intentional computational infidelity. Inspired by this notion, we set out to develop means than can transform the errors in fabrication from an undesired complication to a creative opportunity. We carried out design experiment-based investigations, which culminated in the construction of a framework enabling fundamental artistic explorations of erroneous geometric features of robotically formed molds. The framework consists of digital processes, assisting in the explorations of mold errors, and physical processes, enabling the inclusion of physical feedback in digital explorations. Other complementary elements embrace an implementation workflow, an enabling digital toolset and a visual script demonstrating how imprecise artistic explorations can be included within the computational environment. Our framework application suggests that the exploration of geometrical errors aids the emergence of unprecedented design features that would not have arisen if error elimination were the ultimate design goal. Our conclusion is that welcoming error into the design process can reinstate the role of art, craft, and material agency therein. This can guide the practice and research of architectural computing onto a new territory of esthetic and material innovation. Full article

In this work a novel chaotic system with a line equilibrium is presented. First, a dynamical analysis on the system is performed, by computing its bifurcation diagram, continuation diagram, phase portraits and Lyapunov exponents. Then, the system is applied to the problem of secure communication. We assume that the transmitted signal is an additional state. For this reason, the nonlinear system is rewritten in a rectangular descriptor form and then an observer is constructed for achieving synchronization and input reconstruction. If we assume some rank conditions (on the nonlinearities and the solvability of a linear matrix inequality (LMI)) on the system matrices then the observer synchronization can be feasible. We evaluate and demonstrate our approach with specific numerical results. Full article