Appl. Sci., Volume 10, Issue 10 (May-2 2020) – 324 articles

SARS-CoV-2 (COVID-19) has today multiplied globally and various governments are attempting to stop the outbreak of the disease escalation into a worldwide health crisis. At this juncture, readiness, candor, clarity, and partaking of data are of paramount importance to speed up factual evaluation and starting pattern control activities, including serendipitous findings. Owing to the involvement of COVID-19, many facts regarding virulence, pathogenesis, and the real viral infection source and/or transmission mode still need to be addressed. The infected patients often present clinical symptoms with fever, dyspnea, fatigue, diarrhea, vomiting, and dry cough, as well as pulmonary, infiltrates on imaging. Extensive measures to decrease person-to-person transmission of COVID-19 are being implemented to prevent, recognize, and control the current outbreak as it is very similar to SARS-CoV in its clinical spectrum, epidemiology, and pathogenicity. In response to this fatal disease and disruptive outbreak, it is extremely vital to expedite the drug development process to treat the disease and vaccines for the prevention of COVID-19 that would help us defeat this pandemic expeditiously. This paper sums up and unifies the study of virological aspects, disease transmission, clinically administered techniques, therapeutics options, managements, future directions, designing of vaccines, and news dissemination pertaining to COVID-19. Full article

This study aimed to compare the risk of chronic periodontitis (CP) between participants who underwent tonsillectomy and those who did not (control participants) using a national cohort dataset. Patients who underwent tonsillectomy were selected from a total of 514,866 participants. A control group was included if participants had not undergone tonsillectomy from 2002 to 2015. The number of CP treatments was counted from the date of the tonsillectomy treatment. Patients who underwent tonsillectomy were matched 1:4 with control participants who were categorized based on age, sex, income, and region of residence. Finally, 1044 patients who underwent tonsillectomy were matched 1:4 with 4176 control participants. The adjusted estimated value of the number of post-index date (ID) CP did not reach statistical significance in any post-ID year (each of p > 0.05). In another subgroup analysis according to the number of pre- ID CP, it did not show statistical significance. This study revealed that tonsillectomy was not strongly associated with reducing the risk of CP. Even though the tonsils and periodontium are located adjacently, and tonsillectomy and CP may be related to bacterial inflammation, there was no significant risk of CP in patients undergoing tonsillectomy. Full article

In addition to the traditional Quality of Service (QoS) metrics of latency, jitter and Packet Loss Ratio (PLR), Quality of Experience (QoE) is now widely accepted as a numerical proxy for the actual user experience. The literature has reported many mathematical mappings between QoE and QoS, where the QoS parameters are measured by the network providers using sampling. Previous research has focussed on sampling errors in QoS measurements. However, the propagation of these sampling errors in QoS through to the QoE values has not been evaluated before. This is important: without knowing how sampling errors propagate through to QoE estimates there is no understanding of the precision of the estimates of QoE, only of the average QoE value. In this paper, we used industrially acquired measurements of PLR and jitter to evaluate the sampling errors. Additionally, we evaluated the correlation between these QoS measurements, as this correlation affects errors propagating to the estimated QoE. Focusing on Video-on-Demand (VoD) applications, we use subjective testing and regression to map QoE metrics onto PLR and jitter. The resulting mathematical functions, and the theory of error propagation, were used to evaluate the error propagated to QoE. This error in estimated QoE was represented as confidence interval width. Using the guidelines of UK government for sampling in a busy hour, our results indicate that confidence intervals around estimated the Mean Opinion Score (MOS) rating of QoE can be between MOS = 1 to MOS = 4 at targeted operating points of the QoS parameters. These results are a new perspective on QoE evaluation and are of potentially great significance to all organisations that need to estimate the QoE of VoD applications precisely. Full article

Over the past decades, Unmanned Air Vehicles (UAVs) have achieved outstanding performance in military, commercial and civilian applications. UAVs are increasingly appearing in the form of swarms or formations to meet higher mission requirements. Communication plays an important role in UAV swarm control and coordination. The communication architecture defines how information is exchanged between UAVs or between UAVs and the central control center. Routing protocols help provide reliable end-to-end data transmission. Therefore, it is particularly important to design UAV swarm communication architectures and routing protocols with high performance and stability. This review article details four communication architectures including the advantages and disadvantages. Applicable scenarios are also discussed. In addition, a systematic overview and feasibility research of routing protocols are presented in this paper. To spur further research, the open research issues of UAV swarm communication architectures and routing protocols are also investigated. Full article

As organisations are vulnerable to cyberattacks, their protection becomes a significant issue. Capability Maturity Models can enable organisations to benchmark current maturity levels against best practices. Although many maturity models have been already proposed in the literature, a need for models that integrate several regulations exists. This article presents a light, web-based model that can be used as a cybersecurity assessment tool for Higher Education Institutes (HEIs) of the United Kingdom. The novel Holistic Cybersecurity Maturity Assessment Framework incorporates all security regulations, privacy regulations, and best practices that HEIs must be compliant to, and can be used as a self assessment or a cybersecurity audit tool. Full article

In the prognostics health management (PHM) of rotating machinery, the accurate identification of bearing fault is critical. In recent years, various deep learning methods can well identify bearing fault based on monitoring data. However, facing changing operating conditions and noise pollution, the accuracy of these algorithms decreases significantly, which makes the algorithms difficult in practical applications. To solve this problem, a novel capsule network based on wide convolution and multi-scale convolution (WMSCCN) is proposed for fault diagnosis. The proposed WMSCCN algorithm takes one-dimensional vibration signal as an input and no additional manual processing is required. In addition, the adaptive batch normalization (AdaBN) algorithm is introduced to further enhance the adaptability of WMSCCN under noise pollution and load changes. On generalization experiments under different loads, the proposed WMSCCN and WMSCCN-AdaBN algorithms achieve average accuracy rates of 96.44% and 97.44%, respectively, which is superior to other advanced algorithms. In the noise resistance experiment, the proposed WMSCCN-AdaBN can maintain a 92.3% diagnostic accuracy in a strong noise environment with a signal to noise ratio (SNR) = −4 dB, showing a very strong anti-noise ability. When the SNR exceeds 4 dB, the accuracy reaches 100%, indicating that the proposed algorithm has a very good accuracy at low noise levels. Two experiments have effectively verified the validity and generalizability of the proposed model. Full article

The early and accurate diagnosis of skin cancer is crucial for providing patients with advanced treatment by focusing medical personnel on specific parts of the skin. Networks based on encoder–decoder architectures have been effectively implemented for numerous computer-vision applications. U-Net, one of CNN architectures based on the encoder–decoder network, has achieved successful performance for skin-lesion segmentation. However, this network has several drawbacks caused by its upsampling method and activation function. In this paper, a fully convolutional network and its architecture are proposed with a modified U-Net, in which a bilinear interpolation method is used for upsampling with a block of convolution layers followed by parametric rectified linear-unit non-linearity. To avoid overfitting, a dropout is applied after each convolution block. The results demonstrate that our recommended technique achieves state-of-the-art performance for skin-lesion segmentation with 94% pixel accuracy and a 88% dice coefficient, respectively. Full article

We designed and fabricated a telecentric f-theta imaging lens (TFL) to improve the imaging performance of spectral domain optical coherence tomography (SD-OCT). By tailoring the field curvature aberration of the TFL, the flattened focal surface was well matched to the detector plane. Simulation results showed that the spot in the focal plane fitted well within a single pixel and the modulation transfer function at high spatial frequencies showed higher values compared with those of an achromatic doublet imaging lens, which are commonly used in SD-OCT spectrometers. The spectrometer using the TFL had an axial resolution of 7.8 μm, which was similar to the theoretical value of 6.2 μm. The spectrometer was constructed so that the achromatic doublet lens was replaced by the TFL. As a result, the SD-OCT imaging depth was improved by 13% (1.85 mm) on a 10 dB basis in the roll-off curve and showed better sensitivity at the same depth. The SD-OCT images of a multi-layered tape and a human palm proved that the TFL was able to achieve deeper imaging depth and better contrast. This feature was seen very clearly in the depth profile of the image. SD-OCT imaging performance can be improved simply by changing the spectrometer’s imaging lens. By optimizing the imaging lens, deeper SD-OCT imaging can be achieved with improved sensitivity. Full article

Under the fierce competition and budget constraints, most mobile apps are launched without sufficient tests. Thus, there exists a great demand for automated app testing. Recent developments in various machine learning techniques have made automated app testing a promising alternative to manual testing. This work proposes novel approaches for one of the core functionalities of automated app testing: the detection of changes in usage-phases of a mobile app. Because of the flexibility of app development languages and the lack of standards, each mobile app is very different from other apps. Furthermore, the graphical user interfaces for similar functionalities are rarely consistent or similar. Thus, we propose methods detecting usage-phase changes through object recognition and metrics utilizing graphs and generative models. Contrary to the existing change detection methods requiring learning models, the proposed methods eliminate the burden of training models. This elimination of training is suitable for mobile app testing whose typical usage-phase is composed of less than 10 screenshots. Our experimental results on commercial mobile apps show promising improvement over the state-of-the-practice method based on SIFT (scale-invariant feature transform). Full article

The use of gold nanorods (AuNRs) as surface-enhanced Raman scattering (SERS) substrates has gained much attraction due to their remarkably aspect-ratio-dependent plasmonic properties. In this report, we described the development of AuNRs with a high aspect ratio and longitudinal surface plasmon resonance (LSPR) >850 nm through a hydroquinone-based fabrication with minor modifications. The synthesis started with the reduction of chloroauric acid (HAuCl₄) by sodium borohydride (NaBH₄) to make gold nanoseeds from which AuNRs were grown with the aid of silver nitrate (AgNO₃), HAuCl₄, cetyltrimethylammonium bromide (CTAB), and hydroquinone (HQ). Scanning electron microscopy coupled with energy-dispersive X-ray (SEM-EDX), Transmission electron microscope (TEM), X-ray diffraction (XRD) and Ultra-violet-Visible spectroscopy (UV-Vis) were performed to study the shape, size, and structural and optical properties of AuNRs, respectively. The results showed that AuNRs with high aspect ratios (AR > 3) were single crystals with a heterogenous size distribution, and that the growth of Au nanoseeds into AuNRs took place along the [001] direction. AuNRs exhibited two plasmon resonance peaks at 520 nm and 903 nm, while gold nanoseeds had only a plasmon resonance peak at 521 nm. The as-synthesized AuNRs also showed SERS effects for thiophanate methyl, a broad-spectrum fungicide, with the limit of detection down to 5 mg/L of the fungicide. AuNR-coated glass can serve as a SERS-based sensing platform for rapid detection of thiophanate methyl with high sensitivity and reproducibility. Full article

This paper assesses pedestrian crossing behavior and critical gaps at a two-way midblock crossing location. A critical gap is the shortest gap that a pedestrian accepts when crossing a road. A dataset was collected in 2017 in Edinburgh (UK). The analysis was performed using the fuzzy logic system. The adopted membership function of the fuzzy logic system is of a triangular form since it has a simple and convenient structure. The input variables that are used in the analysis are the number and length of rejected gaps and length of accepted gaps at the crossing location. The output variables are the critical gaps. The results show that assessing critical gap estimation of pedestrians crossing using fuzzy logic is achievable and produces reasonable values that are comparable to values that are reported in the literature. This outcome improves the understanding of pedestrian crossing behavior and could therefore have implications for transport infrastructure design. Further analysis using additional parameters including waiting time and demographic characteristics and alternative forms for membership functions are strongly encouraged. Full article

A weighted constraint iterative algorithm is presented to calculate phase holograms with quality reconstruction. The image plane is partitioned into two regions where different constraint strategies are implemented during the iteration process. In the image plane, the signal region is constrained directly according to the amplitude distribution of the target image based on an adaptive strategy, whereas the non-signal region is constrained indirectly by total energy control of the hologram plane based on the energy conservation principle. The weighted constraint strategy can improve the reconstruction quality of the phase holograms by broadening the optimizing space of the iterative algorithm, leading to effective convergence of the iteration process. Finally, numerical and optical experiments have been performed to validate the feasibility of our method. Full article

This paper proposes a real-time chain and a novel embedded Markovian queueing model with variable bulk arrival (VBA) and variable bulk service (VBS) in order to establish and assure a theoretical foundation to design a blockchain-based real-time system with particular interest in Ethereum. Based on the proposed model, various performances are simulated in a numerical manner in order to validate the efficacy of the model by checking good agreements with the results against intuitive and typical expectations as a baseline. A demo of the proposed real-time chain is developed in this work by modifying the open source of Ethereum Geth 1.9.11. The work in this paper will provide both a theoretical foundation to design and optimize the performances of the proposed real-time chain, and ultimately address and resolve the performance bottleneck due to the conventional block-synchrony by employing an asynchrony by the real-time deadline to some extent. Full article

The impact of different photovoltaic models for a combined solar array and pumped hydro storage system was investigated. Al-Wehda dam located in Harta city in the northern of Jordan was used to validate the approach. The two-diode (TD), single-diode (SD), and ideal single-diode (ISD) solar models were evaluated in terms of the solar array size, reliability, and ecological effects. The impoundment of Al-Wehda dam was taken as the upper reservoir of the pumped hydro facility of the proposed renewable energy system. It was found that the PV power is more accurately modelled by considering the recombination loss in the TD solar model. This leads to a more realistic sizing and precise system evaluation. Results were obtained using the particle swarm optimization (PSO) algorithm and the whale optimization algorithm (WOA) for validation purposes. For instance, the PSO results showed that the realistic TD model is reliable, with an index of reliability of 98.558%. Further, it is the most ecological solution with an annual emissions reduction of 21.5198 Gg. The optimized values are 44,840 solar panels and 65.052 M.m³ of the lower reservoir volume for the TD model. The number of PV panels are reduced by 16.67% and 7.93%, respectively, with the ISD and SD relative to the TD model. Full article

Building information modeling (BIM) has been widely applied in conjunction with the industry foundation class (IFC) for buildings and infrastructure such as railways. However, a limitation of the BIM technology presents limitations that make designing the three-dimensional (3D) alignment-based information models difficult. Thus, the time and effort required to create a railway track model are increased, while the reliability of the model is reduced. In this study, we propose a methodology for developing an alignment-based independent railway track model and extended IFC models containing railway alignment information. The developed algorithm using BIM software tools allows for a discontinuous structure to be designed. The 3D alignment information connects different BIM software tools, and the classification system and IFC schema for expressing railway tracks are extended. Moreover, the classification system is fundamental for assigning IFC entities to railway components. Spatial and hierarchical entities were created through a developed user interface. The proposed methodology was implemented in an actual railway track test. The possibility of managing IFC-based railway track information, including its 3D alignment information, was confirmed. The proposed methodology can reduce the modeling time and can be extended to other alignment-based structures, such as roads. Full article

Technical historical heritage and/or industrial heritage are manifestations of heritage that acquire greater relevance every day, since their study and analysis provide a global vision of their impact on the development of the societies and, also, because they favor the understanding of the technological evolution of these societies. The fields of action are very broad, both from the point of view of engineering and its different disciplines as well as from architecture. This Special Issue shows the reader some of the tools currently available to value this heritage and promote its dissemination, such as geometric modeling, computer-aided design, computer-aided engineering, and the study of industrial heritage from a global perspective. Full article

In the European Union, soil erosion is identified as one of the main environmental threats, addressed with a variety of rules and regulations for soil and water conservation. The by far most often officially used tool to determine soil erosion is the Universal Soil Loss Equation (USLE) and its regional adaptions. The aim of this study is to use three different regional USLE-based approaches in three different test catchments in the Czech Republic, Germany, and Austria to determine differences in model results and compare these with the revised USLE-base European soil erosion map. The different regional model adaptations and implementation techniques result in substantial differences in test catchment specific mean erosion (up to 75% difference). Much more pronounced differences were modelled for individual fields. The comparison of the region-specific USLE approaches with the revised USLE-base European erosion map underlines the problems and limitations of harmonization procedures. The EU map limits the range of modelled erosion and overall shows a substantially lower mean erosion compared to all region-specific approaches. In general, the results indicate that even if many EU countries use USLE technology as basis for soil conservation planning, a truly consistent method does not exist, and more efforts are needed to homogenize the different methods without losing the USLE-specific knowledge developed in the different regions over the last decades. Full article

Cutting chatter is extremely harmful to the machining process, and it is of great significance to eliminate chatter through analyzing the stability of the machining process. In this work, the stability of the milling process with multiple delays is investigated. Considering the regeneration effect, the dynamics of the milling process with variable pitch cutter is modeled as periodic coefficients delayed differential equations (DDEs) with multiple delays. An adaptive variable-step numerical integration method (AVSNIM) considering the effect of the helix angle is developed firstly, which can discretize the cutting period accurately, thereby improving the calculation accuracy of the stability limit of the milling process. The accuracy and efficiency of the AVSNIM are verified through a benchmark milling model. Subsequently, a novel spindle speed-dependent discretization algorithm is proposed, which is combined with the AVSNIM to further reduce the calculation time of the stability lobes diagram (SLD). The simulation experiment results demonstrate that the proposed algorithm can effectively reduce the calculation time. Full article

Measurement of beach heights in the intertidal zone has great importance for dynamic geomorphology research, coastal zone management, and the protection of ecological resources. Based on satellite images, the waterline method based on satellite images is one of the most effective methods for constructing digital elevation models (DEMs) for large-scale tidal flats. However, for fast-changing areas, such as Tiaozini in the Jiangsu coast, timely and detailed topographical data are difficult to obtain due to the insufficient images over a short period of time. In this study, as a supplement to the waterline method, an artificial neural network (ANN) model with the multi-layer feed-forward back propagation algorithm was developed to simulate the topography of variable Tiaozini tidal flats. The “7-15-15-1” double hidden layers with optimized training structures were confirmed via continuous training and comparisons. The input parameters included spectral bands (HJ-1 images B1~B4), geographical coordinates (X, Y), and the distance (D) to waterlines, and the output parameter was the elevation. The model training data were the HJ-1 image for 21 March 2014, and the corresponding topographic data obtained from the waterline method. Then, this ANN model was used to simulate synchronous DEMs corresponding to remote sensing images on 11 February 2012, and 11 July 2013, under low tide conditions. The height accuracy (root mean square error) of the two DEMs was about 0.3–0.4 m based on three transects of the in-situ measured data, and the horizontal accuracy was 30 m—the same as the spatial resolution of the HJ-1 image. Although its vertical accuracy is not very high, this ANN model can quickly provide the basic geomorphological framework for tidal flats based on only one image. This model, therefore, provides an effective way to monitor rapidly changing tidal flats. Full article

The agro-food industry generates large amounts of waste that contribute to environmental contamination. Animal fat waste constitutes some of the most relevant waste and the treatment of such waste is quite costly because environmental regulations are quite strict. Part of such costs might be reduced through the generation of bioenergy. Biodiesel constitutes a valid renewable source of energy because it is biodegradable, non-toxic and has a good combustion emission profile and can be blended up to 20% with fossil diesel for its use in many countries. Furthermore, up to 70% of the total cost of biodiesel majorly depends on the cost of the raw materials used, which can be reduced using animal fat waste because they are cheaper than vegetable oil waste. In fact, 6% of total feedstock corresponded to animal fat in 2019. Transesterification with alkaline catalysis is still preferred at industrial plants producing biodiesel. Recent developments in heterogeneous catalysts that can be easily recovered, regenerated and reused, as well as immobilized lipases with increased stability and resistance to alcohol denaturation, are promising for future industrial use. This manuscript reviews the available processes and recent advances for biodiesel generation from animal fat waste. Full article

The main disadvantage of windowless beam expansion systems is that they cannot achieve a good sealing effect. Turbulence and impurities in the environment can easily affect the imaging and primary mirror. Thus, in this study, a matrix of small holes was introduced for inflation to form a stable and smooth flow inside the system to avoid these disadvantages. In order to study the layout of the matrix, the flow state of the model was analysed, and the Lorentz–Lorenz formula and Barron gradient operator were used for ray tracing. Simulation results show that when the matrix of small holes is arranged in 16 rows with 360 holes in each row, inflation has a lesser effect on the wavefront aberration of the system. Moreover, the root mean square (RMS) of wavefront aberration was only 0.077 μm, which was superior to the other layouts considered. Experimental results show that the RMS was 0.08 μm in this state, which is consistent with the analysis. This indicates that this analysis method can meet actual work needs. The calculation methods and calculation results have high reliability and, thus, can be also used in similar situations. Full article

Ultrabright pulses produced in X-ray free-electron lasers (XFELs) offer new possibilities for industry and research, particularly for biochemistry and pharmaceuticals. The unprecedented brilliance of these next-generation sources enables structure determination from sub-micron crystals as well as radiation-sensitive proteins. The European X-Ray Free-Electron Laser (EuXFEL), with its first light in 2017, ushered in a new era for ultrabright X-ray sources by providing an unparalleled megahertz-pulse repetition rate, with orders of magnitude more pulses per second than previous XFEL sources. This rapid pulse frequency has significant implications for structure determination; not only will data collection be faster (resulting in more structures per unit time), but experiments requiring large quantities of data, such as time-resolved structures, become feasible in a reasonable amount of experimental time. Early experiments at the SPB/SFX instrument of the EuXFEL demonstrate how such closely-spaced pulses can be successfully implemented in otherwise challenging experiments, such as time-resolved studies. Full article

With the explosive growth of space debris, collisions among space debris and spacecrafts seem to be inevitable, which may greatly threaten the structure of on-orbit spacecrafts as well as astronauts’ safety. It is of crucial importance to locate the leak source and evaluate the corresponding damage quickly and accurately to ensure the safety of astronauts and spacecraft equipment. It is widely accepted that acoustic emission method can be used to detect on-orbit leak for space station; however, accurate prediction of vacuum leak noise in space station is difficult as jet and jet noise in vacuum environments are different from those in terrestrial environment. Therefore, this paper tries to investigate sound generations of vacuum leak jet by numerically analyzing dynamics of unsteady vacuum jet flow. Specifically, numerical simulation based on realizable k-ε model is adopted to study the aerodynamic properties and the aeroacoustic characteristics. Results show that RANS turbulent model can capture the pressure fluctuation with high computation efficiency and acceptable accuracy. Secondly, leak from 1 atm to vacuum forms a supersonic flow with Mach number ranging from 2 to 3, accompanied by obvious gradients of steady density, pressure, and temperature. However, the terrestrial leak from 2 atm to 1 atm forms subsonic jet flow with gradually varying gradients of density, pressure, and temperature. Thirdly, obvious reflections of pressure perturbations at the surface, with the mean free path of air molecule being 0.6 mm, can be found and form cavity-like acoustic resonance. Such resonant mechanism contributes to harmonic acoustic properties of the vacuum jet noises besides the broadband turbulent mixing noises. Full article

The shear buckling of web plates and lateral–torsional buckling are among the major failure modes of plate girders. The importance of the lateral–torsional buckling capacity of plate girders was further evidenced when several plate girders of a bridge in Edmonton, Alberta, Canada failed in 2015, because insufficient bracing led to the lateral buckling of the plate girders. In this study, we focus on the optimisation of the cross-sections of plate girders using a well-known and extremely efficient meta-heuristic optimisation algorithm called the harmony search algorithm. The objective of this optimisation is to design the cross-sections of the plate girders with the minimum area that satisfies requirements, such as the lateral–torsional buckling load and ultimate shear stress. The base geometry, material properties, applied load and boundary conditions were taken from an experimental study and optimised. It was revealed that the same amount of load-carrying capacity demonstrated by this model can be achieved with a cross-sectional area 16% smaller than that of the original specimen. Furthermore, the slenderness of the web plate was found to have a decisive effect on the cost-efficiency of the plate girder design. Full article

There are many beneficial medical device ideas based on clinical needs and laboratory research, but medical device development is an expensive, time-consuming and complex challenge. Research and quality management, which are both needed to develop a medical device, are two distinct fields, initiated by a researcher or a clinician having a concept for a medical device, and it is often challenging to find and achieve the proper steps to create a licensed product. Thus, in this paper, we demonstrate the required mindset and main steps of the medical device development procedure through an existing example, a Class IIa medical device, called hypACT Inject Auto. HypACT is a specific syringe, which is capable of blood drawing and serum from platelet-rich fibrin (SPRF) isolation in one step in a closed system. SPRF is intended to be used to improve joint functions in the case of musculoskeletal diseases, specifically osteoarthritis. Full article

Large oil and gas pipelines are prone to corrosion and leakage, so in-pipe inspection is necessary. In this article, we show a novel robot mechanism for long-distance pipeline inspection. The robot consists of three crawlers and electric putters, which can adjust their speed and radius independently. Independent adjustment and system self-checking of the robot are achieved through multiple sensors. To make the robot operate efficiently, we studied the influence of size parameters on the forces between the central body and crawler. Moreover, we investigated how to adjust the attitude of the robot through the differential speed of the three crawlers. Static and dynamic simulations of internal forces are presented. The primary experiments indicate that our robot can operate stably in a large steel pipe. Full article

Quercus aquifolioides is one of the most representative broad-leaved plants in Qinghai-Tibet Plateau with important ecological status. So far, understanding how to quickly estimate the chlorophyll content of plants in plateau areas is still an urgent problem. Field Spec 3 spectrometer was used to measure hyperspectral reflectance data of Quercus aquifolioides leaves at different altitudes, and CCI (chlorophyll relative content) of corresponding leaves was measured by a chlorophyll meter. The correlation and univariate linear fitting analysis techniques were used to establish their relationship models. The results showed that: (1) Chlorophyll relative content of Quercus aquifolioides, under different altitude gradients, were significantly different. From 2905 m to 3500 m, chlorophyll relative content increased first and then decreased. Altitude 3300 m was the most suitable growth area. (2) In 350~550 nm, the spectral reflectance was 3500 m > 3300 m > 2905 m. In 750~1100 nm, the spectral reflectivity was 2905 m > 3500 m > 3300 m. (3) There were 4 main reflection peaks and 5 main absorption valleys in the leaf surface spectral reflection curve. While, 750~1400 nm was the sensitive range of leaf spectral response of Quercus aquifolioides. (4) The red edge position and red valley position moved to short wave direction with the increase of altitude, while the yellow edge position and green peak position moved to long wave direction first and then to short wave direction. (5) The correlation curve between the original spectrum and the CCI value was the best between the wavelengths 509~650 nm. The correlation between the first derivative spectrum and CCI value was the best and most stable at 450~500 nm. The green peak reflectance was most sensitive to the relative chlorophyll content of Quercus aquifolioides. The estimation model R² of green peak reflectance was the highest (y = 206.98e^−10.85x, R² = 0.8523), and the prediction accuracy was 95.85%. The research results can provide some technical and theoretical support for the protection of natural Quercus aquifolioides forests in Tibet. Full article

Many important parts of tool machines all have the important smaller-the-better (STB) quality characteristics. The important STB quality characteristics will impact on the quality of the end-product. At the same time, supplier quality influences the quality and functionality of the end-product, so suppliers must be selected with caution. The six sigma quality index for the STB quality characteristics can directly reflect process quality levels. Besides, this index possesses a mathematical relationship with process yield. Nevertheless, the point estimation will cause the risk of misjudgment, due to sampling errors. As a result, this study applies the confidence interval of the index to a two-tailed fuzzy testing method, in order to select appropriate suppliers. Now that this method is on the basis of the confidence interval, the possibility of misjudgment caused by sampling errors will be reduced, while the precision of the selection will be enhanced. The method can help companies increase product quality, as well as the competitiveness of the industry chain as a whole. Finally, a numerical example is presented to show how to approach this method and its efficacy. Full article

Recently, simultaneous wireless information and power transfer (SWIPT) systems, which can supply efficiently throughput and energy, have emerged as a potential research area in fifth-generation (5G) system. In this paper, we study SWIPT with multi-user, single-input single-output (SISO) system. First, we solve the transmit power optimization problem, which provides the optimal strategy for getting minimum power while satisfying sufficient signal-to-noise ratio (SINR) and harvested energy requirements to ensure receiver circuits work in SWIPT systems where receivers are equipped with a power-splitting structure. Although optimization algorithms are able to achieve relatively high performance, they often entail a significant number of iterations, which raises many issues in computation costs and time for real-time applications. Therefore, we aim at providing a deep learning-based approach, which is a promising solution to address this challenging issue. Deep learning architectures used in this paper include a type of Deep Neural Network (DNN): the Feed-Forward Neural Network (FFNN) and three types of Recurrent Neural Network (RNN): the Layer Recurrent Network (LRN), the Nonlinear AutoRegressive network with eXogenous inputs (NARX), and Long Short-Term Memory (LSTM). Through simulations, we show that the deep learning approaches can approximate a complex optimization algorithm that optimizes transmit power in SWIPT systems with much less computation time. Full article