bluuebunny/crossref_metadata_2025 huggingface dataset:
Smartphone Biosensor System with Multi-Testing Unit Based on Localized Surface Plasmon Resonance Integrated with Microfluidics Chip
Authors: Fan Zhiyuan , Geng Zhaoxin , Fang Weihao , Lv Xiaoqing , Su Yue , Wang Shicai , Chen Hongda
Published: January 2020

Detecting biomarkers is an efficient method to diagnose and monitor patients’ stages. For more accurate diagnoses, continuously detecting and monitoring multiple biomarkers are needed. To achieve point-of-care testing (POCT) of multiple biomarkers, a smartphone biosensor system with the multi-testing-unit (SBSM) based on localized surface plasmon resonance (LSPR) integrated multi-channel microfluidics was presented. The SBSM could simultaneously record nine sensor units to achieve the detection of multiple biomarkers. Additional 72 sensor units were fabricated for further verification. Well-designed modularized attachments consist of a light source, lenses, a grating, a case, and a smartphone shell. The attachments can be well assembled and attached to a smartphone. The sensitivity of the SBSM was 161.0 nm/RIU, and the limit of detection (LoD) reached 4.2 U/mL for CA125 and 0.87 U/mL for CA15-3 through several clinical serum specimens testing on the SBSM. The testing results indicated that the SBSM was a useful tool for detecting multi-biomarkers. Comparing with the enzyme-linked immunosorbent assays (ELISA) results, the results from the SBSM were correlated and reliable. Meanwhile, the SBSM was convenient to operate without much professional skill. Therefore, the SBSM could become useful equipment for point-of-care testing due to its small size, multi-testing unit, usability, and customizable design.
Automatic Hierarchical Classification of Kelps Using Deep Residual Features
Authors: Mahmood Ammar , Ospina Ana Giraldo , Bennamoun Mohammed , An Senjian , Sohel Ferdous , Boussaid Farid , Hovey Renae , Fisher Robert B. , Kendrick Gary A.
Published: January 2020

Across the globe, remote image data is rapidly being collected for the assessment of benthic communities from shallow to extremely deep waters on continental slopes to the abyssal seas. Exploiting this data is presently limited by the time it takes for experts to identify organisms found in these images. With this limitation in mind, a large effort has been made globally to introduce automation and machine learning algorithms to accelerate both classification and assessment of marine benthic biota. One major issue lies with organisms that move with swell and currents, such as kelps. This paper presents an automatic hierarchical classification method local binary classification as opposed to the conventional flat classification to classify kelps in images collected by autonomous underwater vehicles. The proposed kelp classification approach exploits learned feature representations extracted from deep residual networks. We show that these generic features outperform the traditional off-the-shelf CNN features and the conventional hand-crafted features. Experiments also demonstrate that the hierarchical classification method outperforms the traditional parallel multi-class classifications by a significant margin (90.0% vs. 57.6% and 77.2% vs. 59.0%) on Benthoz15 and Rottnest datasets respectively. Furthermore, we compare different hierarchical classification approaches and experimentally show that the sibling hierarchical training approach outperforms the inclusive hierarchical approach by a significant margin. We also report an application of our proposed method to study the change in kelp cover over time for annually repeated AUV surveys.
A New Stitching Method for Dark-Field Surface Defects Inspection Based on Simplified Target-Tracking and Path Correction
Authors: Chen Xue , Li Jiaqi , Sui Yongxin
Published: January 2020

A camera-based dark-field imaging system can effectively detect defects of microns on large optics by scanning and stitching sub-apertures with a small field of view. However, conventional stitching methods encounter problems of mismatches and location deviations, since few defects exist on the tested fine surface. In this paper, a highly efficient stitching method is proposed, based on a simplified target-tracking and adaptive scanning path correction. By increasing the number of sub-apertures and switching to camera perspective, the defects can be regarded as moving targets. A target-tracking procedure is firstly performed to obtain the marked targets. Then, the scanning path is corrected by minimizing the sum of deviations. The final stitching results are updated by re-using the target-tracking method. An experiment was carried out on an inspection of our specially designed testing sample. Subsequently, 118 defects were identified out of 120 truly existing defects, without stitching mismatches. The experiment results show that this method can help to reduce mismatches and location deviations of defects, and it was also effective in increasing the detectability for weak defects.
Fiber Optic Train Monitoring with Distributed Acoustic Sensing: Conventional and Neural Network Data Analysis
Authors: Kowarik Stefan , Hussels Maria-Teresa , Chruscicki Sebastian , Münzenberger Sven , Lämmerhirt Andy , Pohl Patrick , Schubert Max
Published: January 2020

Distributed acoustic sensing (DAS) over tens of kilometers of fiber optic cables is well-suited for monitoring extended railway infrastructures. As DAS produces large, noisy datasets, it is important to optimize algorithms for precise tracking of train position, speed, and the number of train cars. The purpose of this study is to compare different data analysis strategies and the resulting parameter uncertainties. We present data of an ICE 4 train of the Deutsche Bahn AG, which was recorded with a commercial DAS system. We localize the train signal in the data either along the temporal or spatial direction, and a similar velocity standard deviation of less than 5 km/h for a train moving at 160 km/h is found for both analysis methods. The data can be further enhanced by peak finding as well as faster and more flexible neural network algorithms. Then, individual noise peaks due to bogie clusters become visible and individual train cars can be counted. From the time between bogie signals, the velocity can also be determined with a lower standard deviation of 0.8 km/h. The analysis methods presented here will help to establish routines for near real-time train tracking and train integrity analysis.
Abnormal Road Surface Recognition Based on Smartphone Acceleration Sensor
Authors: Du Ronghua , Qiu Gang , Gao Kai , Hu Lin , Liu Li
Published: January 2020

In order to identify the abnormal road surface condition efficiently and at low cost, a road surface condition recognition method is proposed based on the vibration acceleration generated by a smartphone when the vehicle passes through the abnormal road surface. The improved Gaussian background model is used to extract the features of the abnormal pavement, and the k-nearest neighbor (kNN) algorithm is used to distinguish the abnormal pavement types, including pothole and bump. Comparing with the existing works, the influence of vehicles with different suspension characteristics on the detection threshold is studied in this paper, and an adaptive adjustment mechanism based on vehicle speed is proposed. After comparing the field investigation results with the algorithm recognition results, the accuracy of the proposed algorithm is rigorously evaluated. The test results show that the vehicle vibration acceleration contains the road surface condition information, which can be used to identify the abnormal road conditions. The test result shows that the accuracy of the recognition of the road surface pothole is 96.03%, and the accuracy of the road surface bump is 94.12%. The proposed road surface recognition method can be utilized to replace the special patrol vehicle for timely and low-cost road maintenance.
An Improved Calibration Technique for MEMS Accelerometer-Based Inclinometers
Authors: Zhu Jiaxin , Wang Weifeng , Huang Shiping , Ding Wei
Published: January 2020

Micro-electro-mechanical system (MEMS) accelerometer-based inclinometers are widely used to measure deformations of civil structures. To further improve the measurement accuracy, a new calibration technique was proposed in this paper. First, a single-parameter calibration model was constructed to obtain accurate angles. Then, an image-processing-based method was designed to obtain the key parameter for the calibration model. An ADXL355 accelerometer-based inclinometer was calibrated to evaluate the feasibility of the technique. In this validation experiment, the technique was proven to be reliable and robust. Finally, to evaluate the performance of the technique, the calibrated MEMS inclinometer was used to measure the deflections of a scale beam model. The experimental results demonstrate that the proposed technique can yield accurate deformation measurements for MEMS inclinometers.
Low-Finesse Fabry–Pérot Interferometers Applied in the Study of the Relation between the Optical Path Difference and Poles Location
Authors: Guillen Bonilla José Trinidad , Guillen Bonilla Héctor , Rodríguez Betancourtt Verónica María , Sánchez Morales María Eugenia , Reyes Gómez Juan , Casillas Zamora Antonio , Guillen Bonilla Alex
Published: January 2020

Interferometry sensors are frequently analyzed by applying the Fourier transform because the transformation separates all frequency components of its signal, making its study on a complex plane feasible. In this work, we study the relation between the optical path difference (OPD) and poles location theoretically and experimentally, using the Laplace transform and a pole-zero map. Theory and experiments are in concordance. For our study, only the cosine function was considered, which is filtered from the interference pattern. In experimental work, two unperturbed low-finesse Fabry–Pérot interferometers were used. First, a Fabry–Pérot interferometer that has a cavity length of ~ 1.6 mm was used. Its optical path difference was 2.33 mm and the poles were localized at points ± i 12 . rad/nm. Secondly, a Fabry–Pérot interferometer with a cavity length of ~ 5.2 mm was used, and its optical path difference was 7.59 mm and the poles were localized at points ± i 40.4 rad/nm. Experimental results confirmed the theoretical analysis. Our proposal finds practical application for interferometer analysis, signal processing of optical fiber sensors, communication system analysis, and multiplexing systems based on interferometers.
Cavity Ring-Down Methane Sensor for Small Unmanned Aerial Systems
Authors: Martinez Benjamin , Miller Thomas W. , Yalin Azer P.
Published: January 2020

We present the development, integration, and testing of an open-path cavity ring-down spectroscopy (CRDS) methane sensor for deployment on small unmanned aerial systems (sUAS). The open-path configuration used here (without pump or flow-cell) enables a low mass (4 kg) and low power (12 W) instrument that can be readily integrated to sUAS, defined here as having all-up mass of <25 kg. The instrument uses a compact telecom style laser at 1651 nm (near-infrared) and a linear 2-mirror high-finesse cavity. We show test results of flying the sensor on a DJI Matrice 600 hexacopter sUAS. The high sensitivity of the CRDS method allows sensitive methane detection with a precision of ~10–30 ppb demonstrated for actual flight conditions. A controlled release setup, where known mass flows are delivered, was used to simulate point-source methane emissions. Examples of methane plume detection from flight tests suggest that isolated plumes from sources with a mass flow as low as ~0.005 g/s can be detected. The sUAS sensor should have utility for emissions monitoring and quantification from natural gas infrastructure. To the best of our knowledge, it is also the first CRDS sensor directly deployed onboard an sUAS.
High Speed Crop and Weed Identification in Lettuce Fields for Precision Weeding
Authors: Elstone Lydia , How Kin Yau , Brodie Samuel , Ghazali Muhammad Zulfahmi , Heath William P. , Grieve Bruce
Published: January 2020

Precision weeding can significantly reduce or even eliminate the use of herbicides in farming. To achieve high-precision, individual targeting of weeds, high-speed, low-cost plant identification is essential. Our system using the red, green, and near-infrared reflectance, combined with a size differentiation method, is used to identify crops and weeds in lettuce fields. Illumination is provided by LED arrays at 525, 650, and 850 nm, and images are captured in a single-shot using a modified RGB camera. A kinematic stereo method is utilised to compensate for parallax error in images and provide accurate location data of plants. The system was verified in field trials across three lettuce fields at varying growth stages from 0.5 to 10 km/h. In-field results showed weed and crop identification rates of 56% and 69%, respectively. Post-trial processing resulted in average weed and crop identifications of 81% and 88%, respectively.
Sensors for Ultrasonic Nondestructive Testing (NDT) in Harsh Environments
Authors: Sinclair Anthony N. , Malkin Robert
Published: January 2020

In this special issue of Sensors, seven peer-reviewed manuscripts appear on the topic of ultrasonic transducer design and operation in harsh environments: elevated temperature, high gamma and neutron fields, or the presence of chemically aggressive species. Motivations for these research and development projects are strongly focused on nuclear power plant inspections (particularly liquid-sodium cooled reactors), and nondestructive testing of high-temperature piping installations. It is anticipated that we may eventually see extensive use of permanently mounted robust transducers for in-service monitoring of petrochemical plants and power generations stations; quality control in manufacturing plants; and primary and secondary process monitoring in the fabrication of engineering materials.
Wearable Device Oriented Flexible and Stretchable Energy Harvester Based on Embedded Liquid-Metal Electrodes and FEP Electret Film
Authors: Xie Jianbing , Wang Yiwei , Dong Rong , Tao Kai
Published: January 2020

In this paper, a flexible and stretchable energy harvester based on liquid-metal and fluorinated ethylene propylene (FEP) electret films is proposed and implemented for the application of wearable devices. A gallium liquid-metal alloy with a melting point of 25.0 °C is used to form the stretchable electrode; therefore, the inducted energy harvester will have excellent flexibility and stretchability. The solid-state electrode is wrapped in a dragon-skin silicone rubber shell and then bonded with FEP electret film and conductive film to form a flexible and stretchable energy harvester. Then, the open-circuit voltage of the designed energy harvester is tested and analyzed. Finally, the fabricated energy harvester is mounted on the elbow of a human body to harvest the energy produced by the bending of the elbow. The experimental results show that the flexible and stretchable energy harvester can adapt well to elbow bending and convert elbow motion into electric energy to light the LED in a wearable watch.
Research on an Infrared Multi-Target Saliency Detection Algorithm under Sky Background Conditions
Authors: Dai Shaosheng , Li Dongyang
Published: January 2020

Aiming at solving the problem of incomplete saliency detection and unclear boundaries in infrared multi-target images with different target sizes and low signal-to-noise ratio under sky background conditions, this paper proposes a saliency detection method for multiple targets based on multi-saliency detection. The multiple target areas of the infrared image are mainly bright and the background areas are dark. Combining with the multi-scale top hat (Top-hat) transformation, the image is firstly corroded and expanded to extract the subtraction of light and shade parts and reconstruct the image to reduce the interference of sky blurred background noise. Then the image obtained by a multi-scale Top-hat transformation is transformed from the time domain to the frequency domain, and the spectral residuals and phase spectrum are extracted directly to obtain two kinds of image saliency maps by multi-scale Gauss filtering reconstruction, respectively. On the other hand, the quaternion features are extracted directly to transform the phase spectrum, and then the phase spectrum is reconstructed to obtain one kind of image saliency map by the Gauss filtering. Finally, the above three saliency maps are fused to complete the saliency detection of infrared images. The test results show that after the experimental analysis of infrared video photographs and the comparative analysis of Receiver Operating Characteristic (ROC) curve and Area Under the Curve (AUC) index, the infrared image saliency map generated by this method has clear target details and good background suppression effect, and the AUC index performance is good, reaching over 99%. It effectively improves the multi-target saliency detection effect of the infrared image under the sky background and is beneficial to subsequent detection and tracking of image targets.
Circumferential SH Wave Piezoelectric Transducer System for Monitoring Corrosion-Like Defect in Large-Diameter Pipes
Authors: Zhang Hao , Du Yuehao , Tang Jihua , Kang Guozheng , Miao Hongchen
Published: January 2020

The fundamental circumferential shear horizontal (CSH0) wave is of practical importance in monitoring corrosion defects in large-diameter pipes due to its virtually non-dispersive characteristics. However, so far, there have been limited CSH0 wave transducers which can be used to constitute a structural health monitoring (SHM) system for pipes. Moreover, the CSH0 wave’s capability of sizing the corrosion-like defect has not yet been confirmed by experiments. In this work, firstly, the mechanism of exciting CSH waves was analyzed. A method based on our previously developed bidirectional SH wave piezoelectric transducers was then proposed to excite the pure CSH0 mode and first order circumferential shear horizontal (CSH1) mode. Both finite element simulations and experiments show that the bidirectional transducer is capable of exciting pure CSH0 mode traveling in both circumferential directions of a 1-mm thick steel pipe from 100 to 300 kHz. Moreover, this transducer can also serve a sensor to detect CSH0 mode only by filtering circumferential Lamb waves over a wide frequency range from 100 to 450 kHz. After that, a method of sizing a rectangular notch defect by using CSH0 wave was proposed. Experiments on an 11-mm thick steel pipe show that the depth and circumferential extent of a notch can be accurately determined by using the proposed method. Finally, experiments were performed to investigate the reflection and transmission characteristics of CSH0 and CSH1 waves from notches with different depths. It was found that transmission coefficients of CSH0 mode decrease with the increasing of notch depth, which indicates that it is possible to monitor the depth change of corrosion defects by using CSH0 wave.
A Machine Learning Based Intrusion Detection System for Mobile Internet of Things
Authors: Amouri Amar , Alaparthy Vishwa T. , Morgera Salvatore D.
Published: January 2020

Intrusion detection systems plays a pivotal role in detecting malicious activities that denigrate the performance of the network. Mobile adhoc networks (MANETs) and wireless sensor networks (WSNs) are a form of wireless network that can transfer data without any need of infrastructure for their operation. A more novel paradigm of networking, namely Internet of Things (IoT) has emerged recently which can be considered as a superset to the afore mentioned paradigms. Their distributed nature and the limited resources available, present a considerable challenge for providing security to these networks. The need for an intrusion detection system (IDS) that can acclimate with such challenges is of extreme significance. Previously, we proposed a cross layer-based IDS with two layers of detection. It uses a heuristic approach which is based on the variability of the correctly classified instances (CCIs), which we refer to as the accumulated measure of fluctuation (AMoF). The current, proposed IDS is composed of two stages; stage one collects data through dedicated sniffers (DSs) and generates the CCI which is sent in a periodic fashion to the super node (SN), and in stage two the SN performs the linear regression process for the collected CCIs from different DSs in order to differentiate the benign from the malicious nodes. In this work, the detection characterization is presented for different extreme scenarios in the network, pertaining to the power level and node velocity for two different mobility models: Random way point (RWP), and Gauss Markov (GM). Malicious activity used in the work are the blackhole and the distributed denial of service (DDoS) attacks. Detection rates are in excess of 98% for high power/node velocity scenarios while they drop to around 90% for low power/node velocity scenarios.
Characterization of Back-Scattering and Multipath in a Suburban Area after the Calibration of an X-Band Commercial Radar
Authors: Galati Gaspare , Pavan Gabriele , Wasserzier Christoph
Published: January 2020

The increasing interest in the radar detection of low-elevation and small-size targets in complicated ground environments (such as urban, suburban, and mixed country areas) calls for a precise quantification of the radar detection capabilities in those areas. Hence, a set of procedures is devised and tested, both theoretically and experimentally, using a commercial X-band radar, to (i) calibrate the radar sensor (with an online evaluation of its losses) using standard scatterers, (ii) measure the multipath effect and compensate for it, and (iii) create “true radar cross section” maps of the area of interest for both point and distributed clutter. The above methods and the related field results are aimed at future qualification procedures and practical usage of small, cheap, and easily moveable radars for the detection of low-observable air targets, such as unmanned air vehicles/systems (UAV/UAS), in difficult ground areas. A significant set of experimental results as discussed in the paper confirms the great relevance of multipath in ground-based radar detection, with the need for correcting measures.
Comparison of AlN vs. SIO2/LiNbO3 Membranes as Sensitive Elements for the SAW-Based Acceleration Measurement: Overcoming the Anisotropy Effects
Authors: Yu. Shevchenko Sergey , A. Mikhailenko Denis , Markelov Oleg A.
Published: January 2020

We propose the use of aluminum nitride (AlN) membranes acting as sensitive elements for the surface acoustic wave (SAW)-based acceleration measurement. The proposed solution is compared against existing prototypes based on the use of quartz (SiO2)/lithium niobate (LiNbO3) membranes that are characterized by extensive anisotropic properties. Using COMSOL Multiphysics 5.4 computer simulations we show explicitly that sensitive elements based on less anisotropic AlN membranes overcome both the low sensitivity limitations of SiO2 and low temperature stability of LiNbO3. Moreover, AlN membranes exhibit nearly double the robustness against irreversible mechanical deformations when compared against SiO2, which in turn allows for further 1.5-fold sensitivity enhancement over LiNbO3 based sensors. Taking into account their acceptable frequency characteristics, we thus believe that the AlN membranes are a good candidate forsensitive elements especially for high acceleration measurements.
A Novel Cooperative Localization Method Based on IMU and UWB
Authors: Han Yongqiang , Wei Chenchen , Li Rong , Wang Jingzhe , Yu Huan
Published: January 2020

In this paper, a range-based cooperative localization method is proposed for multiple platforms of various structures. The localization system of an independent platform might degrade or fail due to various reasons such as GPS signal-loss, inertial measurement unit (IMU) accumulative errors, or emergency reboot. It is a promising approach to solve this problem by using information from neighboring platforms, thus forming a cooperative localization network that can improve the navigational robustness of each platform. Typical ranging-based ultra-wideband (UWB) cooperative localization systems require at least three auxiliary nodes to estimate the pose of the target node, which is often hard to meet especially in outdoor environment. In this work, we propose a novel IMU/UWB-based cooperative localization solution, which requires a minimum number of auxiliary nodes that is down to 1. An Adaptive Ant Colony Optimization Particle Filter (AACOPF) algorithm is customized to integrate the dead reckoning (DR) system and auxiliary nodes information with no prior information required, resulting in accurate pose estimation, while to our knowledge the azimuth have not been estimated in cooperative localization for the insufficient observation of the system. We have given the condition when azimuth and localization are solvable by analysis and by experiment. The feasibility of the proposed approach is evaluated through two filed experiments: car-to-trolley and car-to-pedestrian cooperative localization. The comparison results also demonstrate that ACOPF-based integration is better than other filter-based methods such as Extended Kalman Filter (EKF) and traditional Particle Filter (PF).
Fused-Deposition-Material 3D-Printing Procedure and Algorithm Avoiding Use of Any Supports
Authors: Barile Gianluca , Leoni Alfiero , Muttillo Mirco , Paolucci Romina , Fazzini Gianfranco , Pantoli Leonardo
Published: January 2020

The three-dimensional printing of complex shapes without using supporting structures is the most attractive factor of merit in current additive manufacturing because it allows to drastically reduce printing time, and ideally nullify postprocessing and waste material. In this work, we present an innovative procedure and algorithm (Print on Air, PoA) for additive manufacturing that, relying on sensing systems embedded into the three-dimensional (3D) printer (e.g., temperature and speed sensors), aims at generating a printing sequence capable of a self-sustaining bridge and overhang structures. This feature was achieved by splitting the actual floating area of the layer where the aforementioned structures are in many subsections. Each is generated with a negligible floating surface and printed in a well-determined sequence with accurate temperature and speed profiles. Therefore, each subsection is formed without the need for scaffolding, simultaneously acting as a supporting structure for the following subsection. The array of subsections constitutes the actual bridge or overhang structure. The proposed method can be used for any object, including very long bridges or convex surfaces. The revolutionary method is here reported and evaluated in order to show its applicability in any condition. Although the study was conducted in a Fused Deposition Material (FDM) environment, it can certainly be adapted to other manufacturing environments with adequate modifications.
Development of an Open-Source Thermal Image Processing Software for Improving Irrigation Management in Potato Crops (Solanum tuberosum L.)
Authors: Cucho-Padin Gonzalo , Rinza Javier , Ninanya Johan , Loayza Hildo , Quiroz Roberto , Ramírez David A.
Published: January 2020

Accurate determination of plant water status is mandatory to optimize irrigation scheduling and thus maximize yield. Infrared thermography (IRT) can be used as a proxy for detecting stomatal closure as a measure of plant water stress. In this study, an open-source software (Thermal Image Processor (TIPCIP)) that includes image processing techniques such as thermal-visible image segmentation and morphological operations was developed to estimate the crop water stress index (CWSI) in potato crops. Results were compared to the CWSI derived from thermocouples where a high correlation was found ( r P e a r s o n = 0.84). To evaluate the effectiveness of the software, two experiments were implemented. TIPCIP-based canopy temperature was used to estimate CWSI throughout the growing season, in a humid environment. Two treatments with different irrigation timings were established based on CWSI thresholds: 0.4 (T2) and 0.7 (T3), and compared against a control (T1, irrigated when soil moisture achieved 70% of field capacity). As a result, T2 showed no significant reduction in fresh tuber yield (34.5 ± 3.72 and 44.3 ± 2.66 t ha - 1 ), allowing a total water saving of 341.6 ± 63.65 and 515.7 ± 37.73 m 3 ha - 1 in the first and second experiment, respectively. The findings have encouraged the initiation of experiments to automate the use of the CWSI for precision irrigation using either UAVs in large settings or by adapting TIPCIP to process data from smartphone-based IRT sensors for applications in smallholder settings.
Predictions of Cu, Zn, and Cd Concentrations in Soil Using Portable X-Ray Fluorescence Measurements
Authors: Adler Karl , Piikki Kristin , Söderström Mats , Eriksson Jan , Alshihabi Omran
Published: January 2020

Portable X-ray fluorescence (PXRF) measurements on 1520 soil samples were used to create national prediction models for copper (Cu), zinc (Zn), and cadmium (Cd) concentrations in agricultural soil. The models were validated at both national and farm scales. Multiple linear regression (MLR), random forest (RF), and multivariate adaptive regression spline (MARS) models were created and compared. National scale cross-validation of the models gave the following R2 values for predictions of Cu (R2 = 0.63), Zn (R2 = 0.92), and Cd (R2 = 0.70) concentrations. Independent validation at the farm scale revealed that Zn predictions were relatively successful regardless of the model used (R2 > 0.90), showing that a simple MLR model can be sufficient for certain predictions. However, predictions at the farm scale revealed that the non-linear models, especially MARS, were more accurate than MLR for Cu (R2 = 0.94) and Cd (R2 = 0.80). These results show that multivariate modelling can compensate for some of the shortcomings of the PXRF device (e.g., high limits of detection for certain elements and some elements not being directly measurable), making PXRF sensors capable of predicting elemental concentrations in soil at comparable levels of accuracy to conventional laboratory analyses.
Void Fraction Measurement of Oil–Gas–Water Three-Phase Flow Using Mutually Perpendicular Ultrasonic Sensor
Authors: Ren Weikai , Zhao An , Jin Ningde
Published: January 2020

The complex flow structure and interfacial effect in oil–gas–water three-phase flow have made the void fraction measurement a challenging problem. This paper reports on the void fraction measurement of oil–gas–water three-phase flow using a mutually perpendicular ultrasonic sensor (MPUS). Two pairs of ultrasonic probes are installed on the same pipe section to measure the void fraction. With the aid of the finite element method, we first optimize the emission frequency and geometry parameters of MPUS through examining its sensitivity field distribution. Afterward, the oil–gas–water three-phase flow experiment was carried out in a vertical upward pipe with a diameter of 20 mm to investigate the responses of MPUS. Then, the void fraction prediction models associated with flow patterns (bubble flow, slug flow, and churn flow) were established. Compared to the quick closing valves, MPUS obtained a favorable accuracy for void fraction measurement with absolute average percentage error equaling 8.983%, which indicates that MPUS can satisfactorily measure the void fraction of oil–gas–water three-phase flow.
To Be Happy: A Case Study of Entrepreneurial Motivation and Entrepreneurial Process from the Perspective of Positive Psychology
Authors: Su Xiaohua , Liu Shengmei , Zhang Shujun , Liu Lingling
Published: January 2020

The pursuit of wealth maximization is considered to be the greatest driving force of entrepreneurship. However, this economic rational perspective cannot sufficiently answer why potential or continuous entrepreneurs still choose entrepreneurship or even continuous entrepreneurship in the face of high failure rate and tremendous uncertainty. On the basis of the dynamic process of entrepreneurship and the perspective of positive psychology, this study attempts to interpret the sustained motivation mechanism of entrepreneurs. This study uses multiple cases to investigate the emotion, cognition, and behavior of entrepreneurial process. Through NVivo software and emotion dictionary, more than 27,000 micro blogs (Weibo) of six entrepreneurs were analyzed, and the model of positive emotion in entrepreneurial process was constructed. The findings are as follows. (1) In the process of establishing a business, entrepreneurs can persist in a highly uncertain environment by acquiring positive emotions. That is, the motivation of sustainable entrepreneurship originates from the emotion of happiness and satisfaction that entrepreneurs obtain. (2) Positive emotions affect the formation and expansion of key activities of entrepreneurship through cognition and then persist with entrepreneurship. Specifically, positive emotion promotes the formation of entrepreneurial intention by expanding cognitive structure, intuitive processing, and analytical processing to promote the acquisition of entrepreneurial resources and the expansion of entrepreneurial ability. (3) In the process of entrepreneurship, emotional return is a performance dimension parallel to economic return. This conclusion provides a new perspective towards revealing the entrepreneurial motivation of entrepreneurs in highly ambiguous environments.
Integration, Application and Importance of Collaboration in Sustainable Project Management
Authors: Larsson Johan , Larsson Lisa
Published: January 2020

The need to consider sustainability has substantially increased the complexity of implementing construction and infrastructure projects and new management practices have emerged during the past decade to tackle the global sustainability challenges, where the engagement and coordination of broader competences from stakeholders throughout the supply chain is required. This new project management paradigm has been accompanied by greater attention to the concept of collaborative business arrangements, often called partnering, that has emerged in construction and infrastructure projects to improve project deliveries. However, there are uncertainties about the optimal strategy to foster, integrate and maintain the required collaboration, particularly in sustainable management practices in infrastructure maintenance projects. This paper addresses these uncertainties, based on a single case study of an infrastructure maintenance contract involving an extensive collaborative business arrangement. The findings reveal that different collaborative practices affect diverse aspects of sustainable project management. Further, the extensive collaborative business arrangement has promoted sustainable deliveries based upon organizational learning and continuous improvements. Thus, this study offers an encouraging example of how extensive collaboration can be fostered and play a key role in sustainable project management practices.
Climate Change and Livelihood Vulnerability in Mixed Crop–Livestock Areas: The Case of Province Punjab, Pakistan
Authors: Ahmad Muhammad Irshad , Ma Hengyun
Published: January 2020

The mixed crop–livestock system is a primary source of livelihood in developing countries. Erratic climate changes are severely affecting the livelihoods of people who depend upon mixed crop–livestock production. By employing the livelihood vulnerability index (LVI), the Intergovernmental Panel on Climate Change LVI (LVIIPCC), and the livelihood effect index (LEI), this study evaluated livelihood vulnerability in southern Punjab, Pakistan. The study provides a range of indicators for national and local policy makers to improve resilience in the face of livelihood vulnerability. By incorporating more major components and subcomponents, this study identifies more specific challenges of livelihood vulnerability for future policy directions. It is interesting to find that credit and cash used for crop inputs are critical financial constraints for farmers. From the estimated indicators, this study also provides some specific policy recommendations for the four study districts of Punjab Province. These results are helpful in identifying and highlighting vulnerability determinants and indicators. Initiating and promoting better adaptive capacity and starting resilience projects for households are urgent actions required by donors and governments to reduce the livelihood vulnerability of mixed crop–livestock households in arid and semiarid areas.
Modeling Impacts of Speed Reduction on Traffic Efficiency on Expressway Uphill Sections
Authors: Zhang Xiaodong , Xu Jinliang , Liang Qianqian , Ma Fangchen
Published: January 2020

Road geometric design is a key factor impacting driving safety and efficiency. In highway profile design, speed reduction is used to determine critical length of grade. Previous research generally concentrated on the relationship between speed reduction and crash involvement rate to establish the recommended value. Limited research results have been reported at this point concerning speed reduction and traffic efficiency. This study aims to fill the gap by investigating tolerable speed reduction with different vertical slopes considering traffic efficiency. Firstly, appropriate experimental sections were determined after field survey. Traffic data including vehicle count, timely speed, vehicle type, and headway time were then collected on an expressway in Shaanxi Province. The associated traffic efficiency was derived from traffic volume and average speed. After this, the modeling between speed reduction and traffic efficiency was processed with different slopes. The correlation between speed reduction and traffic efficiency was therefore verified. Finally, the prediction model of optimum speed reduction concerning traffic efficiency under different vertical slopes was introduced. It was found that the critical length of grade can be longer with traffic efficiency as the major design control incorporated with slopes of 3–3.5%. The existing regulation in critical length of grade at 3.5–5% can benefit both safety and efficiency. The findings can provide a reference for vertical alignment design, leading to high-efficiency road systems.
Effect of the Parking Lane Configuration on Vehicle Speeds in Home Zones in Poland
Authors: Sołowczuk Alicja , Gardas Przemysław
Published: January 2020

Nowadays, traffic calming measures that are designed to influence the drivers’ behaviour in the first place and thus make them slow down (and increase the safety of traffic as a result) are used increasingly often in traffic engineering. As a rule of thumb, carefully planned street geometry and street furniture should advise the drivers of the traffic calmed area ahead of them, which makes them reduce the vehicle speed by influencing their perception. One of the most common treatments are road narrowings and horizontal deflections of the route of travel. The reduction of the vehicle speed increases the driver’s central visual area, which results in earlier and easier spotting of pedestrians that are about to cross the roadway. A reduction of noise and exhaust emissions is an additional benefit. However, the current sustainable design guidelines are not specific regarding how often the route should be deflected by alternate parking lanes and how frequently they should be placed in the home zones (woonerven in Dutch) in order to achieve the desired reduction of vehicle speed, noise, pollution, and exhaust emissions. This being so, the authors carried out a speed survey research on a chosen street that includes woonerf design features, as typically used in Poland, with carriageway narrowings being created by parking lanes differently sited along its length. Several speed measuring devices were deployed to automatically and simultaneously measure and record the vehicle speeds and volume of traffic at different test locations. The measurement data were subjected to statistical analyses, including conventional statistical tests. The alternative hypothesis, proposing that the vehicle speeds depend on the configuration of parking lanes and carriageway narrowings was confirmed in almost all cases. The results have confirmed that the siting of parking lanes is a relevant factor as far as speed reduction is concerned, with the degree of this reduction depending on the remaining travel lane width.
Assessing the Impact of ICT Sector on Sustainable Development in the European Union: An Empirical Analysis Using Panel Data
Authors: Cioacă Sorin-Iulian , Cristache Silvia-Elena , Vuță Mariana , Marin Erika , Vuță Mihai
Published: January 2020

Information and communication technologies (ICT) play a central role at the European level because it fosters innovation and increases productivity through an enlarged access to information. As such, the main objective of this work was to assess the impact of various ICT core indicators at the European Union level on two of their sustainable development goals: economic growth and reduction of inequality. To this purpose, we used panel data models based on data collected from the Eurostat database. We proposed two panel data regression models, according to which we found a positive statistically significant relationship between the variable measuring level of internet access and change in GDP per capita. We also found a negative relationship between the transition towards a digital society and the dependent variable INEQ_INC, namely an increase of 1% of ICT sector share in GDP will lead to a decrease of 0.27% of income inequality distribution. This result showed that the progress made in implementing a digital society may decrease societal income inequality.
Neighborhood Walkability and Housing Prices: A Correlation Study
Authors: Kim Eun Jung , Kim Hyunjung
Published: January 2020

This study aims to examine the relationship between the level of walkability and housing prices in Seoul, Korea. The average transaction price per square meter for each apartment complex was set as a dependent variable and the walkability score was used as an independent variable. This study divided a total of 5986 apartment complexes into areas with high and low housing prices for analysis. Based on the strong spatial autocorrelations of housing prices, this study employed spatial regression models in addition to the Ordinary Least Squares (OLS) model. Results showed that housing prices positively correlated with the walkability score in areas with low housing prices, whereas no significant association was observed in areas with high housing prices. Additional findings showed that housing prices were associated with building age (−), number of households in the complex (+), slope (−), and greenness (+) in both subsamples. Results also showed that high school quality had a different association with housing prices depending on the subsample (e.g., the sign was positive in areas with high housing prices and no significance in areas with low housing prices). The results herein support public policy proposals relevant to urban planning, environmental design, and housing policies.
Organic Food Consumption: The Relevance of the Health Attribute
Authors: Rizzo Giuseppina , Borrello Massimiliano , Dara Guccione Giovanni , Schifani Giorgio , Cembalo Luigi
Published: January 2020

During the last decades, organic food products have become the main sustainable alternative to conventional food consumption. Among the several organic food attributes that consumers recognize in organic food, healthiness has been reported as the primary motivation to buy products certified as organic. The objective of the current study is to assess the relative weight of the health attribute among other recognized organic food attributes. To achieve this aim, a multiple price list (MPL) methodology is adopted to elicit consumers’ Willingness to Pay (WTP) for organic extra virgin olive oil (EVOO). Findings show that the contribution of the health attribute to determine the average premium price for organic EVOO is 78.9% of its total premium price. The study generates managerial implications to promote further expansion of the organic food market.
Fostering Resident Pro-Environmental Behavior: The Roles of Destination Image and Confucian Culture
Authors: Zhang Jiangchi , Xie Chaowu , Morrison Alastair M. , Zhang Kun
Published: January 2020

Residents are important participants and stakeholders in destination development. Identifying factors that assist in predicting resident pro-environmental behavior (PEB) may contribute to enhanced sustainability. Based on a traditional Chinese culture, this research constructed a model of resident PEB by introducing pro-environmental destination image (PEDI) and Confucianism as the independent and moderating variables, respectively. The structural equation modeling for 402 residents indicated the model had a satisfactory level of predictive power for PEB. The results showed that: (1) PEDI positively affected residents’ environmental identity, pro-environmental attitudes, and PEB; (2) environmental identity and pro-environmental attitudes completely mediated the impact of PEDI on residents’ PEB; and (3) Confucian culture had a positive U-shaped moderating effect in the relationships among these four variables. Overall, these findings advance the understanding of the formation of PEB in Confucian culture and provide theoretical and practical implications for fostering residents’ PEB.
Factors Influencing Usability of Rehabilitation Robotic Devices for Lower Limbs
Authors: Kim Taesun
Published: January 2020

In recent years, there has been a sharp increase in the number of elderly people in South Korea; this has led to rising costs and concerns on the quality of physical therapy treatment involving rehabilitation robotic devices. Therefore, the government has asked academia to expand its research scope to evaluate the usability of these devices. Hence, this study aimed to identify the major factors influencing the usability of a rehabilitation robotic device for lower limbs and the reasons for involving several diverse user groups for a more comprehensive evaluation. To measure usability as perceived by three primary user groups of user experience (UX) professionals, rehab professionals, and lay people, this study collected 196 survey. The results of an EFA showed that among three general quality factors and five device specific factors, visual pertinence, use confidence, and safety were the critical factors influencing usability, and the results of ANOVA offered that there was discrepancy in the influential factors, namely visual pertinence, transferring, and holding the body. These findings indicate that the necessity of employing a posture-centered approach and multiple user groups in assessing the usability of rehabilitation devices. Given these findings, it is suggested that the industry and design community should move toward implementing a more explorative perspective to enable a more human-centered and posture-concerned approach to provide better usability to the diverse users of medical devices.