bluuebunny/crossref_metadata_2025 huggingface dataset:
Accuracy Assessment of RANS Predictions of Active Flow Control for Hydrofoil Cavitation
Authors: Pant Chandra Shekhar , Delorme Yann , Frankel Steven
Published: June 2020

In this work, we numerically investigate the cavitating flow on the scaled-down 2D model of guided vanes. Furthermore, the effects of wall injection on both the cavitation and on the hydrodynamic performance of the guided vane are studied. The numerical simulations are performed using OpenFOAM v1906. We used a 2D k- ω SST model for modeling the turbulence in the present set of simulations. We studied the flow for two angles of attack, viz. 3 ∘ and 9 ∘ . For the 3 ∘ angle of attack, the present numerical work is in good agreement with the previous experimental work, but for the larger angle of attack, because of flow separation, the present simulations do not capture the flow correctly.
Utilization of Waste Cooking Oil via Recycling as Biofuel for Diesel Engines
Authors: Nguyen Xa Hoi , Nguyen Viet Thanh , Nguyen Duc Khanh , Nguyen Duy Vinh
Published: June 2020

In this study, waste cooking oil (WCO) was used to successfully manufacture catalyst cracking biodiesel in the laboratory. This study aims to evaluate and compare the influence of waste cooking oil synthetic diesel (WCOSD) with that of commercial diesel (CD) fuel on an engine’s operating characteristics. The second goal of this study is to compare the engine performance and temperature characteristics of cooling water and lubricant oil under various engine operating conditions of a test engine fueled by waste cooking oil and CD. The results indicated that the engine torque of the engine running with WCOSD dropped from 1.9 Nm to 5.4 Nm at all speeds, and its brake specific fuel consumption (BSFC) dropped at almost every speed. Thus, the thermal brake efficiency (BTE) of the engine fueled by WCOSD was higher at all engine speeds. Also, the engine torque of the WCOSD-fueled engine was lower than the engine torque of the CD-fueled engine at all engine speeds. The engine’s power dropped sequentially through 0.3 kW, 0.4 kW, 0.6 kW, 0.9 kW, 0.8 kW, 0.9 kW, 1.0 kW and 1.9 kW.
Christmas in the Room: Gender, Conflict, and Compromise in Multi-Religious Domestic Space
Authors: Mehta Samira K.
Published: June 2020

Interfaith relationships offer particular potential for creating religious coexistence; they also play out very differently in domestic space than in public and civic spaces, with the result that interfaith marriage becomes an important, yet unique, site of religious cooperation, co-existence, and conflict. The article argues that examinations of interfaith families must take three factors into account, each of which involves careful attention to the particular power dynamics of the family in question. First, scholars must think about the broader context in which the interfaith family has come to exist. Second, scholars must consider that the emotional and power dynamics of domestic space often have little in common with the compromises and power dynamics of public space. Lastly, while gender is not generally a key category of analysis for thinking about interfaith encounters in public space, gender, both as it shapes power dynamics and as it drives assumptions about childrearing and domestic labor, shapes interfaith family life and requires attendant scholarly attention.
Effects of Novel Inverted Rocker Orthoses for First Metatarsophalangeal Joint on Gastrocnemius Muscle Electromyographic Activity during Running: A Cross-Sectional Pilot Study
Authors: Sánchez-Gómez Rubén , Romero-Morales Carlos , Gómez-Carrión Álvaro , De-la-Cruz-Torres Blanca , Zaragoza-García Ignacio , Anttila Pekka , Kantola Matti , Ortuño-Soriano Ismael
Published: June 2020

Background: The mobility of the first metatarsophalangeal joint (I MPTJ) has been related to the proper windlass mechanism and the triceps surae during the heel-off phase of running gait; the orthopedic treatment of the I MPTJ restriction has been made with typical Morton extension orthoses (TMEO). Nowadays it is unclear what effects TMEO or the novel inverted rocker orthoses (NIRO) have on the EMG activity of triceps surae during running. Objective: To compare the TMEO effects versus NIRO on EMG triceps surae on medialis and lateralis gastrocnemius activity during running. Study design: A cross-sectional pilot study. Methods: 21 healthy, recreational runners were enrolled in the present research (mean age 31.41 ± 4.33) to run on a treadmill at 9 km/h using aleatory NIRO of 6 mm, NIRO of 8 mm, TMEO of 6 mm, TMEO of 8 mm, and sports shoes only (SO), while the muscular EMG of medial and lateral gastrocnemius activity during 30 s was recorded. Statistical intraclass correlation coefficient (ICC) to test reliability was calculated and the Wilcoxon test of all five different situations were tested. Results: The reliability of values was almost perfect. Data showed that the gastrocnemius lateralis increased its EMG activity between SO vs. NIRO-8 mm (22.27 ± 2.51 vs. 25.96 ± 4.68 mV, p < 0.05) and SO vs. TMEO-6mm (22.27 ± 2.51 vs. 24.72 ± 5.08 mV, p < 0.05). Regarding gastrocnemius medialis, values showed an EMG notable increase in activity between SO vs. NIRO-6mm (22.93 ± 2.1 vs. 26.44 ± 3.63, p < 0.001), vs. NIRO-8mm (28.89 ± 3.6, p < 0.001), and vs. TMEO-6mm (25.12 ± 3.51, p < 0.05). Conclusions: Both TMEO and NIRO have shown an increased EMG of the lateralis and medialis gastrocnemius muscles activity during a full running cycle gait. Clinicians should take into account the present evidence when they want to treat I MTPJ restriction with orthoses, and consider the inherent triceps surae muscular cost relative to running economy.
Sparse Regularization-Based Approach for Point Cloud Denoising and Sharp Features Enhancement
Authors: Leal Esmeide , Sanchez-Torres German , Branch John W.
Published: June 2020

Denoising the point cloud is fundamental for reconstructing high quality surfaces with details in order to eliminate noise and outliers in the 3D scanning process. The challenges for a denoising algorithm are noise reduction and sharp features preservation. In this paper, we present a new model to reconstruct and smooth point clouds that combine L1-median filtering with sparse L1 regularization for both denoising the normal vectors and updating the position of the points to preserve sharp features in the point cloud. The L1-median filter is robust to outliers and noise compared to the mean. The L1 norm is a way to measure the sparsity of a solution, and applying an L1 optimization to the point cloud can measure the sparsity of sharp features, producing clean point set surfaces with sharp features. We optimize the L1 minimization problem by using the proximal gradient descent algorithm. Experimental results show that our approach is comparable to the state-of-the-art methods, as it filters out 3D models with a high level of noise, but keeps their geometric features.
Incremental Interval Type-2 Fuzzy Clustering of Data Streams using Single Pass Method
Authors: Qaiyum Sana , Aziz Izzatdin , Hasan Mohd Hilmi , Khan Asif Irshad , Almalawi Abdulmohsen
Published: June 2020

Data Streams create new challenges for fuzzy clustering algorithms, specifically Interval Type-2 Fuzzy C-Means (IT2FCM). One problem associated with IT2FCM is that it tends to be sensitive to initialization conditions and therefore, fails to return global optima. This problem has been addressed by optimizing IT2FCM using Ant Colony Optimization approach. However, IT2FCM-ACO obtain clusters for the whole dataset which is not suitable for clustering large streaming datasets that may be coming continuously and evolves with time. Thus, the clusters generated will also evolve with time. Additionally, the incoming data may not be available in memory all at once because of its size. Therefore, to encounter the challenges of a large data stream environment we propose improvising IT2FCM-ACO to generate clusters incrementally. The proposed algorithm produces clusters by determining appropriate cluster centers on a certain percentage of available datasets and then the obtained cluster centroids are combined with new incoming data points to generate another set of cluster centers. The process continues until all the data are scanned. The previous data points are released from memory which reduces time and space complexity. Thus, the proposed incremental method produces data partitions comparable to IT2FCM-ACO. The performance of the proposed method is evaluated on large real-life datasets. The results obtained from several fuzzy cluster validity index measures show the enhanced performance of the proposed method over other clustering algorithms. The proposed algorithm also improves upon the run time and produces excellent speed-ups for all datasets.
Imprinted Polymer-Based Guided Mode Resonance Grating Strain Sensors
Authors: Mattelin Marie-Aline , Missinne Jeroen , De Coensel Bert , Van Steenberge Geert
Published: June 2020

Optical sensors based on guided mode resonance (GMR) realized in polymers are promising candidates for sensitive and cost effective strain sensors. The benefit of GMR grating sensors is the non-contact, easy optical read-out with large working distance, avoiding costly alignment and packaging procedures. The GMR gratings with resonance around 850–900 nm are fabricated using electron beam lithography and replicated using a soft stamp based imprinting technique on 175 μ m-thick foils to make them suitable for optical strain sensing. For the strain measurements, foils are realized with both GMR gratings and waveguides with Bragg gratings. The latter are used as reference sensors and allow extracting the absolute strain sensitivity of the GMR sensor foils. Following this method, it is shown that GMR gratings have an absolute strain sensitivity of 1.02 ± 0.05 pm / μ ε at 870 nm.
A Comparative Study in Real-Time Scene Sonification for Visually Impaired People
Authors: Hu Weijian , Wang Kaiwei , Yang Kailun , Cheng Ruiqi , Ye Yaozu , Sun Lei , Xu Zhijie
Published: June 2020

In recent years, with the development of depth cameras and scene detection algorithms, a wide variety of electronic travel aids for visually impaired people have been proposed. However, it is still challenging to convey scene information to visually impaired people efficiently. In this paper, we propose three different auditory-based interaction methods, i.e., depth image sonification, obstacle sonification as well as path sonification, which convey raw depth images, obstacle information and path information respectively to visually impaired people. Three sonification methods are compared comprehensively through a field experiment attended by twelve visually impaired participants. The results show that the sonification of high-level scene information, such as the direction of pathway, is easier to learn and adapt, and is more suitable for point-to-point navigation. In contrast, through the sonification of low-level scene information, such as raw depth images, visually impaired people can understand the surrounding environment more comprehensively. Furthermore, there is no interaction method that is best suited for all participants in the experiment, and visually impaired individuals need a period of time to find the most suitable interaction method. Our findings highlight the features and the differences of three scene detection algorithms and the corresponding sonification methods. The results provide insights into the design of electronic travel aids, and the conclusions can also be applied in other fields, such as the sound feedback of virtual reality applications.
Multipath Map Method for TDOA Based Indoor Reverse Positioning System with Improved Chan-Taylor Algorithm
Authors: Hua Cheng , Zhao Kun , Dong Danan , Zheng Zhengqi , Yu Chao , Zhang Yu , Zhao Tiantian
Published: June 2020

We study wireless indoor positioning systems where multiple synchronized infrastructure devices simultaneously receive signals from an object of interest whose arrival times are measured. The positioning performance is degraded by unresolvable channel multipath and non-line-of-sight (NLOS) reflctions which cause a bias in the time difference of arrival (TDOA) measurements. In order to reduce the negative effect of multi-path, a Multi-Path Map (MPM) method based on spatial domain modeling principle in the reverse positioning framework with good robustness is proposed. Meanwhile, an improved non-linear iterative algorithm with height component constrained which reduces the complexity is introduced to calculate the coordinates so that the performance of the MPM can be verified. By using the MPM measurements as pre-calibration information to compensate the TDOA observed value, the accuracy of the cooperative location based on a UWB device is 6.45 cm, which achieves 63% improvement than that of none MPM used.
Electrical Resistance Sensing of Epoxy Curing Using an Embedded Carbon Nanotube Yarn
Authors: Rodríguez-Uicab Omar , Abot Jandro L. , Avilés Francis
Published: June 2020

Curing effects were investigated by using the electrical response of a single carbon nanotube yarn (CNTY) embedded in an epoxy resin during the polymerization process. Two epoxy resins of different viscosities and curing temperatures were investigated, varying also the concentration of the curing agent. It is shown that the kinetics of resin curing can be followed by using the electrical response of an individual CNTY embedded in the resin. The electrical resistance of an embedded CNTY increased (~9%) after resin curing for an epoxy resin cured at 130 °C with viscosity of ~59 cP at the pouring/curing temperature (“Epon 862”), while it decreased (~ −9%) for a different epoxy cured at 60 °C, whose viscosity is about double at the corresponding curing temperature. Lowering the curing temperature from 60 °C to room temperature caused slower and smoother changes of electrical resistance over time and smaller (positive) residual resistance. Increasing the concentration of the curing agent caused a faster curing kinetics and, consequently, more abrupt changes of electrical resistance over time, with negative residual electrical resistance. Therefore, the resin viscosity and curing kinetics play a paramount role in the CNTY wicking, wetting and resin infiltration processes, which ultimately govern the electrical response of the CNTY immersed into epoxy.
All Single-Mode-Fiber Supercontinuum Source Setup for Monitoring of Multiple Gases Applications
Authors: Martin-Vela Javier A. , Gallegos-Arellano Eloisa , Sierra-Hernández Juan M. , Estudillo-Ayala Julián M. , Jauregui-Vázquez Daniel , Avila-Garcia Maria S. , Ramírez-Gasca Humberto , Rojas-Laguna Roberto
Published: June 2020

In this paper, a gas sensing system based on a conventional absorption technique using a single-mode-fiber supercontinuum source (SMF-SC) is presented. The SC source was implemented by channeling pulses from a microchip laser into a one kilometer long single-mode fiber (SMF), obtaining a flat high-spectrum with a bandwidth of up to 350 nm in the region from 1350 to 1700 nm, and high stability in power and wavelength. The supercontinuum radiation was used for simultaneously sensing water vapor and acetylene gas in the regions from 1350 to 1420 nm and 1510 to 1540 nm, respectively. The experimental results show that the absorption peaks of acetylene have a maximum depth of approximately 30 dB and contain about 60 strong lines in the R and P branches, demonstrating a high sensitivity of the sensing setup to acetylene. Finally, to verify the experimental results, the experimental spectra are compared to simulations obtained from the Hitran database. This shows that the implemented system can be used to develop sensors for applications in broadband absorption spectroscopy and as a low-cost absorption spectrophotometer of multiple gases.
Correcting Decalibration of Stereo Cameras in Self-Driving Vehicles
Authors: Muhovič Jon , Perš Janez
Published: June 2020

Camera systems in autonomous vehicles are subject to various sources of anticipated and unanticipated mechanical stress (vibration, rough handling, collisions) in real-world conditions. Even moderate changes in camera geometry due to mechanical stress decalibrate multi-camera systems and corrupt downstream applications like depth perception. We propose an on-the-fly stereo recalibration method applicable in real-world autonomous vehicles. The method is comprised of two parts. First, in optimization step, external camera parameters are optimized with the goal to maximise the amount of recovered depth pixels. In the second step, external sensor is used to adjust the scaling of the optimized camera model. The method is lightweight and fast enough to run in parallel with stereo estimation, thus allowing an on-the-fly recalibration. Our extensive experimental analysis shows that our method achieves stereo reconstruction better or on par with manual calibration. If our method is used on a sequence of images, the quality of calibration can be improved even further.
Robust Distributed Kalman Filtering: On the Choice of the Local Tolerance
Authors: Emanuele Alessandro , Gasparotto Francesco , Guerra Giacomo , Zorzi Mattia
Published: June 2020

We propose a distributed Kalman filter for a sensor network under model uncertainty. The distributed scheme is characterized by two communication stages in each time step: in the first stage, the local units exchange their observations and then they can compute their local estimate; in the final stage, the local units exchange their local estimate and compute the final estimate using a diffusion scheme. Each local estimate is computed in order to be optimal according to the least favorable model belonging to a prescribed local ambiguity set. The latter is a ball, in the Kullback–Liebler topology, about the corresponding nominal local model. We propose a strategy to compute the radius, called local tolerance, for each local ambiguity set in the sensor network, rather than keep it constant across the network. Finally, some numerical examples show the effectiveness of the proposed scheme.
A Machine Learning Method for Vision-Based Unmanned Aerial Vehicle Systems to Understand Unknown Environments
Authors: Zhang Tianyao , Hu Xiaoguang , Xiao Jin , Zhang Guofeng
Published: June 2020

What makes unmanned aerial vehicles (UAVs) intelligent is their capability of sensing and understanding new unknown environments. Some studies utilize computer vision algorithms like Visual Simultaneous Localization and Mapping (VSLAM) and Visual Odometry (VO) to sense the environment for pose estimation, obstacles avoidance and visual servoing. However, understanding the new environment (i.e., make the UAV recognize generic objects) is still an essential scientific problem that lacks a solution. Therefore, this paper takes a step to understand the items in an unknown environment. The aim of this research is to enable the UAV with basic understanding capability for a high-level UAV flock application in the future. Specially, firstly, the proposed understanding method combines machine learning and traditional algorithm to understand the unknown environment through RGB images; secondly, the You Only Look Once (YOLO) object detection system is integrated (based on TensorFlow) in a smartphone to perceive the position and category of 80 classes of objects in the images; thirdly, the method makes the UAV more intelligent and liberates the operator from labor; fourthly, detection accuracy and latency in working condition are quantitatively evaluated, and properties of generality (can be used in various platforms), transportability (easily deployed from one platform to another) and scalability (easily updated and maintained) for UAV flocks are qualitatively discussed. The experiments suggest that the method has enough accuracy to recognize various objects with high computational speed, and excellent properties of generality, transportability and scalability.
Fast CNN Stereo Depth Estimation through Embedded GPU Devices
Authors: Aguilera Cristhian A. , Aguilera Cristhian , Navarro Cristóbal A. , Sappa Angel D.
Published: June 2020

Current CNN-based stereo depth estimation models can barely run under real-time constraints on embedded graphic processing unit (GPU) devices. Moreover, state-of-the-art evaluations usually do not consider model optimization techniques, being that it is unknown what is the current potential on embedded GPU devices. In this work, we evaluate two state-of-the-art models on three different embedded GPU devices, with and without optimization methods, presenting performance results that illustrate the actual capabilities of embedded GPU devices for stereo depth estimation. More importantly, based on our evaluation, we propose the use of a U-Net like architecture for postprocessing the cost-volume, instead of a typical sequence of 3D convolutions, drastically augmenting the runtime speed of current models. In our experiments, we achieve real-time inference speed, in the range of 5–32 ms, for 1216 × 368 input stereo images on the Jetson TX2, Jetson Xavier, and Jetson Nano embedded devices.
A New Method for the Measurement of the Diffusion Coefficient of Adsorbed Vapors in Thin Zeolite Films, Based on Magnetoelastic Sensors
Authors: Kouzoudis Dimitris , Baimpos Theodoros , Samourgkanidis Georgios
Published: June 2020

In the current work an experimental method is used in order to calculate the diffusivity D (diffusion coefficient) of various vapors in thin zeolite films. The method is based on adsorption data from magnetoelastic sensors on top of which a zeolite layer was synthesized, and the diffusivity is extracted by fitting the data to Fick’s laws of diffusion. In particular, the method is demonstrated for two volatile organic compound (VOC) vapors on two different zeolites, the p-Xylene adsorption in Faujasite type zeolite with D = 1.89 × 10 − 13   m 2 / s at 120   ° C and the propene adsorption in Linde Type A type zeolite with D = 5.9 × 10 − 14   m 2 / s at 80   ° C , two diffusion coefficients which are extracted experimentally for first time. Our results are within the order of magnitude of other VOC/zeolite values reported in literature.
Structural Operativity Evaluation of Strategic Buildings through Finite Element (FE) Models Validated by Operational Modal Analysis (OMA)
Authors: Foti Dora , Giannoccaro Nicola Ivan , Vacca Vitantonio , Lerna Michela
Published: June 2020

In this paper, a non-destructive technique based on the monitoring of the environmental vibrations of two strategic buildings by positioning accelerometers in well-defined points was used for fixing their dynamic behavior. The accelerometers measurements were elaborated through Operational Modal Analysis (OMA) techniques, in order to identify natural frequencies, damping coefficients, and modal shapes of the structure. Once these parameters have been determined, a numerical model calibrated on the identified frequencies and verified on the corresponding mode shapes was created for each building. The structural operational efficiency index of the buildings was determined by using the Seismic Model Ambient Vibration (SMAV) methodology, which allows us to evaluate their seismic vulnerability. The results obtained from the experimental analysis (on three different tests for each analyzed building) concern the frequencies and the modal shapes of the structure. They have been compared to the results of the finite element model, with a very small error, indicating a good quality of the analysis and also the possibility of using directly well-tuned models for verifying the structural operating indices.
Design and Test of a Microdestructive Tree-Ring Measurement System
Authors: Hu Xueyang , Zheng Yili , Liang Hao , Zhao Yandong
Published: June 2020

Analysis of a tree ring is the primary method for determining the growth and age of a tree. In a microdestructive tree-ring measurement system, the tree under test is drilled with a microdrill at a constant rotating speed to detect the difference in density between the early and late wood, thereby realizing a microdestructive measurement of the tree-ring. The measurement system comprises a microdrill with a diameter of 3 mm, mechanical transmission, direct current (DC) servomotor, stepper motor, and control and detection circuit. The DC servomotor and stepper motor realize rotation and translation of the microdrill, respectively, through mechanical transmission. When the microdrill rotates and drills into the tree, the control and detection circuit samples and acquires the armature current of the DC servomotor, which is proportional to the resistance encountered by the drill bit and reflects the change in the density of the tree. The tree-ring number can be obtained by filtering the sampled original signals of the armature current using a finite impulse response (FIR) filtering algorithm. The annual rings of larch and fir tree discs were measured and tested using the designed system. It was observed that the average annual ring measurement accuracy of the larch discs reached 95.28%, while that of the fir discs was 84.16%. The diameter of the drill hole in the trunk was less than 3 mm after measuring the living wood, thereby achieving a microdestructive measurement of the tree-ring.
A Power-Efficient Radiation Sensor Interface with a Peak-Triggered Sampling Scheme for Mobile Dosimeters
Authors: Jeon Hyuntak , Choi Injun , Kweon Soon-Jae , Je Minkyu
Published: June 2020

Radiation sensor interfaces for battery-powered mobile dosimeters must consume low power to monitor the amount of radiation exposure over a long period. This paper proposes a power-efficient radiation sensor interface using a peak-triggered sampling scheme. Since the peak of the analog-to-digital converter’s (ADC’s) input represents radiation energy, our ADC only operates around the peak value thanks to the proposed sampling scheme. Although our ADC operates with a high sampling frequency, this proposed sampling scheme reduces the power consumption of the sensor interface because of the reduced operation time of the ADC. Our sensor interface does not have signal distortion caused by a conventional shaper because the interface quantizes the peak value using the high sampling frequency instead of the shaper. When the radiation input occurs once every 10 μs, the power consumption of the ADC with the proposed sampling scheme is only about 21.5% of the ADC’s power consumption when the ADC continuously operates. In this worst case, the fabricated radiation sensor interface in a 0.18-μm complementary metal-oxide-semiconductor (CMOS) process consumes only 1.11 mW.
Recent Advances in the Aptamer-Based Electrochemical Biosensors for Detecting Aflatoxin B1 and Its Pertinent Metabolite Aflatoxin M1
Authors: Beitollahi Hadi , Tajik Somayeh , Dourandish Zahra , Zhang Kaiqiang , Le Quyet Van , Jang Ho Won , Kim Soo Young , Shokouhimehr Mohammadreza
Published: June 2020

The notable toxicological impacts of aflatoxin B1 (AFB1) and its main metabolite, aflatoxin M1 (AFM1), on human being health make the evaluation of food quality highly significant. Due to the toxicity of those metabolites—even very low content in foodstuffs—it is crucial to design a sensitive and reliable procedure for their detection. Electrochemical aptamer-based biosensors are considered the most encouraging option, based on multi-placed analysis, rapid response, high sensitivity and specificity. The present review specifically emphasizes the potential utilization of the electrochemical aptasensors for determining the AFM1 and AFB1 with different electrodes.
Multi-Stage Pedestrian Positioning Using Filtered WiFi Scanner Data in an Urban Road Environment
Authors: Huang Zilin , Xu Lunhui , Lin Yongjie
Published: June 2020

Since widespread applications of wireless sensors networks, low-speed traffic positioning based on the received signal strength indicator (RSSI) from personal devices with WiFi broadcasts has attracted considerable attention. This study presents a new range-based localization method for outdoor pedestrian positioning by using the combination of offline RSSI distance estimation and real-time continuous position fitting, which can achieve high-position accuracy in the urban road environment. At the offline stage, the piecewise polynomial regression model (PPRM) is proposed to formulate the Euclidean distance between the targets and WiFi scanners by replacing the common propagation model (PM). The online stage includes three procedures. Firstly, a constant velocity Kalman filter (CVKF) is developed to smooth the real-time RSSI time series and estimate the target-detector distance. Then, a least squares Taylor series expansion (LS-TSE) is developed to calculate the actual 2-dimensional coordinate with the replacement of existing trilateral localization. Thirdly, a trajectory-based technique of the unscented Kalman filter (UKF) is introduced to smooth estimated positioning points. In tests that used field scenarios from Guangzhou, China, the experiments demonstrate that the combined CVKF and PPRM can achieve the highly accurate distance estimator of <1.98 m error with the probability of 90% or larger, which outperforms the existing propagation model. In addition, the online method can achieve average positioning error of 1.67 m with the much better than classical methods.
A Fiber Bragg Grating Borehole Deformation Sensor for Stress Measurement in Coal Mine Rock
Authors: Zhao Wusheng , Zhong Kun , Chen Weizhong
Published: June 2020

A borehole deformation sensor for long-term stress monitoring in coal mine rock based on optical fiber Bragg gratings (FBGs) is presented. The sensor converts borehole deformation into optical fiber strain by using four rings. For each ring, two FBGs are bonded with the ring to measure the borehole deformation, and a reference FBG free from mechanical load is introduced to remove the temperature effect. Two simple checks on the test data can be performed to improve the test accuracy. Laboratory and field tests were conducted to validate the accuracy and long-term performance of the sensor. The results show that the sensor is capable of measuring stress in rock with good accuracy, and it performs well over a long period of time in coal mines. The developed sensor provides an approach for the long-term monitoring of stress changes in coal mine rock.
Adaptive Intrawell Matched Stochastic Resonance with a Potential Constraint Aided Line Enhancer for Passive Sonars
Authors: Dong Haitao , He Ke , Shen Xiaohong , Ma Shilei , Wang Haiyan , Qiao Changcheng
Published: June 2020

Remote passive sonar detection and classification are challenging problems that require the user to extract signatures under low signal-to-noise (SNR) ratio conditions. Adaptive line enhancers (ALEs) have been widely utilized in passive sonars for enhancing narrowband discrete components, but the performance is limited. In this paper, we propose an adaptive intrawell matched stochastic resonance (AIMSR) method, aiming to break through the limitation of the conventional ALE by nonlinear filtering effects. To make it practically applicable, we addressed two problems: (1) the parameterized implementation of stochastic resonance (SR) under the low sampling rate condition and (2) the feasibility of realization in an embedded system with low computational complexity. For the first problem, the framework of intrawell matched stochastic resonance with potential constraint is implemented with three distinct merits: (a) it can ease the insufficient time-scale matching constraint so as to weaken the uncertain affect on potential parameter tuning; (b) the inaccurate noise intensity estimation can be eased; (c) it can release the limitation on system response which allows a higher input frequency in breaking through the large sampling rate limitation. For the second problem, we assumed a particular case to ease the potential parameter a o p t = 1 . As a result, the computation complexity is greatly reduced, and the extremely large parameter limitation is relaxed simultaneously. Simulation analyses are conducted with a discrete line signature and harmonic related line signature that reflect the superior filtering performance with limited sampling rate conditions; without loss of generality of detection, we considered two circumstances corresponding to H 1 (periodic signal with noise) and H 0 (pure noise) hypotheses, respectively, which indicates the detection performance fairly well. Application verification was experimentally conducted in a reservoir with an autonomous underwater vehicle (AUV) to validate the feasibility and efficiency of the proposed method. The results indicate that the proposed method surpasses the conventional ALE method in lower frequency contexts, where there is about 10 dB improvement for the fundamental frequency in the sense of power spectrum density (PSD).
A Review on Vehicle Classification and Potential Use of Smart Vehicle-Assisted Techniques
Authors: Shokravi Hoofar , Shokravi Hooman , Bakhary Norhisham , Heidarrezaei Mahshid , Rahimian Koloor Seyed Saeid , Petrů Michal
Published: June 2020

Vehicle classification (VC) is an underlying approach in an intelligent transportation system and is widely used in various applications like the monitoring of traffic flow, automated parking systems, and security enforcement. The existing VC methods generally have a local nature and can classify the vehicles if the target vehicle passes through fixed sensors, passes through the short-range coverage monitoring area, or a hybrid of these methods. Using global positioning system (GPS) can provide reliable global information regarding kinematic characteristics; however, the methods lack information about the physical parameter of vehicles. Furthermore, in the available studies, smartphone or portable GPS apparatuses are used as the source of the extraction vehicle’s kinematic characteristics, which are not dependable for the tracking and classification of vehicles in real time. To deal with the limitation of the available VC methods, potential global methods to identify physical and kinematic characteristics in real time states are investigated. Vehicular Ad Hoc Networks (VANETs) are networks of intelligent interconnected vehicles that can provide traffic parameters such as type, velocity, direction, and position of each vehicle in a real time manner. In this study, VANETs are introduced for VC and their capabilities, which can be used for the above purpose, are presented from the available literature. To the best of the authors’ knowledge, this is the first study that introduces VANETs for VC purposes. Finally, a comparison is conducted that shows that VANETs outperform the conventional techniques.
A Smart Realtime Service to Broadcast the Precise Orbits of GPS Satellite and Its Performance on Precise Point Positioning
Authors: Li Dehai , Yan Wei , Mi Jinzhong , Dang Yamin , Yuan Yunbin , Gan Xingli
Published: June 2020

At present, Global Position System (GPS) navigation ephemeris mainly broadcasts satellite orbits with meter-level precision for standard point positioning and precise relative positioning. With the rapid development of real-time precise point positioning (PPP), the receiver or smartphone has begun to demand more and more convenient, continuous, and reliable access to real-time services of precise orbits. Therefore, this study proposes a solution of utilizing the 18-parameter ephemeris to directly broadcast ultra-rapid precise predicted orbits with centimeter-level precision for real-time PPP. For the first time in GPS, the difference in the PPP results between the precise orbits and the calculated orbits broadcasted from the generated ephemeris parameters is supplied as follows: (1) During the validity period of 2 h, root mean square (RMS) of the relative distance offsets between the results of PPP with the precise orbits and the results of PPP the 18-parameter ephemeris is only 0.0098 m. (2) Within 15 min after the validity period of 2 h, RMS of the relative distance offsets between the results of PPP with the precise orbits and the results of PPP with the predicted orbits by 18-parameter ephemeris is only 0.0057 m. Consequently, the 18-parameter ephemeris is feasible and advisable to broadcast precise predicted orbits for real-time PPP applications. Compared with the classic precise orbits broadcast mode with the orbit corrections defined by the radio technical commission for maritime services standards 10403.2 (RTCM), the mode of broadcasting the precise orbits with the 18-parameter ephemeris achieved the following improvements in convenience, continuity, and reliability: (1) The calculation of satellite position is the same as that of the navigation ephemeris excluding the additional correction operations required to the RTCM; (2) the amount of broadcast parameters was reduced by 20 times; (3) the length of the validity period was expanded 120 times, where the longer valid period helped to overcome the orbit corrections loss caused by RTCM stream failures; and (4) within 15 min after the validity period, the predicted orbits with an accuracy of 2 cm could still be provided by the 18-parameter ephemeris, which can ensure the real-time services of precise orbits in the case of a 15 min communication interruption of the RTCM orbit correction data stream.
SenseCrypt: A Security Framework for Mobile Crowd Sensing Applications
Authors: Pius Owoh Nsikak , Mahinderjit Singh Manmeet
Published: June 2020

The proliferation of mobile devices such as smartphones and tablets with embedded sensors and communication features has led to the introduction of a novel sensing paradigm called mobile crowd sensing. Despite its opportunities and advantages over traditional wireless sensor networks, mobile crowd sensing still faces security and privacy issues, among other challenges. Specifically, the security and privacy of sensitive location information of users remain lingering issues, considering the “on” and “off” state of global positioning system sensor in smartphones. To address this problem, this paper proposes “SenseCrypt”, a framework that automatically annotates and signcrypts sensitive location information of mobile crowd sensing users. The framework relies on K-means algorithm and a certificateless aggregate signcryption scheme (CLASC). It incorporates spatial coding as the data compression technique and message query telemetry transport as the messaging protocol. Results presented in this paper show that the proposed framework incurs low computational cost and communication overhead. Also, the framework is robust against privileged insider attack, replay and forgery attacks. Confidentiality, integrity and non-repudiation are security services offered by the proposed framework.
Enhancement of Biosensors by Implementing Photoelectrochemical Processes
Authors: del Barrio Melisa , Luna-López Gabriel , Pita Marcos
Published: June 2020

Research on biosensors is growing in relevance, taking benefit from groundbreaking knowledge that allows for new biosensing strategies. Electrochemical biosensors can benefit from research on semiconducting materials for energy applications. This research seeks the optimization of the semiconductor-electrode interfaces including light-harvesting materials, among other improvements. Once that knowledge is acquired, it can be implemented with biological recognition elements, which are able to transfer a chemical signal to the photoelectrochemical system, yielding photo-biosensors. This has been a matter of research as it allows both a superior suppression of background electrochemical signals and the switching ON and OFF upon illumination. Effective electrode-semiconductor interfaces and their coupling with biorecognition units are reviewed in this work.
Research on the Single-Value Indicators for Centrifugal Pump Based on Vibration Signals
Authors: Luo Yin , Han Yuejiang , Yuan Shouqi , Yuan Jianping
Published: June 2020

Off-design operation conditions might not only seriously affect the internal flow status of a centrifugal pump, but also result in additional energy loss and potential mechanical damage. Therefore, early-stage monitoring and predication on off-design operation conditions for centrifugal pumps have become essential. Single-value indicators have favorable factors such as a smaller amount of calculation and easier identification. As a result, industries prefer the more straightforward approach: obtaining single-value indicators directly from the signals which could be easier compared with accepted standards. The possibility of applying the single-value indicators of vibration into operation condition monitoring for a centrifugal pump is studied theoretically and experimentally, which shows that the statistical features of vibration might be suitable for hydraulic instability detection for a centrifugal pump.
Characterization and Performance of a Thermal Camera Communication System
Authors: Guerra Victor , Ticay-Rivas Jaime R. , Alonso-Eugenio Victor , Perez-Jimenez Rafael
Published: June 2020

This work presents a novel communications technology named Thermal Camera Communication (TCC), which is analogous to Optical Camera Communication (OCC). Thermographic cameras and Peltier cells are proposed as receiver and transmitter, respectively, changing completely their usual field of application. Furthermore, a comprehensive characterization of the Peltier–Thermal camera pair is carried out, presenting their bandwidth, achievable data rate under On-Off-Keying (OOK) modulation, noise characteristics, and energy efficiency. A comparison against the current state-of-the-art OCC technology is also provided, showing that TCC is a promising technology suitable for sensor networks. The thorough analysis of TCC performed in this work shows that commercial Peltier cells can be re-thought under a communications viewpoint in order to improve their performance. This novel communication technology can be applied in environments such as the access to public transportation or buildings due to the new health emergency situation. The use of thermographic cameras will become massive and dual measurement and communication purposes could be considered for applications such as sensor networks, using a yet unexploited wavelength range.
Challenges of Post-measurement Histology for the Dielectric Characterisation of Heterogeneous Biological Tissues
Authors: La Gioia Alessandra , O’Halloran Martin , Porter Emily
Published: June 2020

The dielectric properties of biological tissues are typically measured using the open-ended coaxial probe technique, which is based on the assumption that the tissue sample is homogeneous. Therefore, for heterogeneous tissue samples, additional post-measurement sample processing is conducted. Specifically, post-measurement histological analysis may be performed in order to associate the measured dielectric properties with the tissue types present in a heterogeneous sample. Accurate post-measurement histological analysis enables identification of the constituent tissue types that contributed to the measured dielectric properties, and their relative distributions. There is no standard protocol for conducting post-measurement histological analysis, which leads to high numbers of excluded tissue samples and inconsistencies in the resulting reported data for heterogeneous tissues. To this extent, this study examines the post-measurement histological process and the challenges in associating the acquired dielectric properties with the different tissue types present in heterogeneous samples. The results demonstrate that the histological process inevitably alters the morphology of samples, thus introducing errors in the interpretation of the dielectric properties acquired from heterogeneous biological samples. Notably, sample size was seen to shrink by up to 90% through the histological process, meaning that sensing volume determined from fresh tissues is not directly applicable to histology images.
Mechanisms for Innovative-Driven Solutions in European Smart Cities
Authors: Manika Stella
Published: June 2020

Innovative procurement is an important tool for smart cities to improve the effectiveness and efficiency of public services, especially in sectors such as smart living (for example, health conditions), smart mobility, or smart environment (with emphasis on waste and water management). The European Union (EU) public procurement legislative framework encourages the deployment of innovation by several means (including, inter alia, the introduction of competitive procedures promoting innovation, use of award criteria based on factors other than price, and the life-cycle approach) and sets the scene for a more strategic procurement for EU smart cities. Despite the proven benefits of innovative procurement, public authorities, driven mainly by their preference to follow traditional tender procedures under solely budgetary considerations, have hesitated to introduce innovation. The case study of Greece is examined, and it is concluded that despite the adopted policy measures that are conducive for mainstreaming innovation procurement, innovation procurement in Greece is at an early development stage. One of the reasons that hinder the application of innovation-oriented procedures by public purchasers is their insufficient knowledge of the available legal framework. The broad objective of this article is to outline the main innovation-friendly tools, as set out in the applicable European public procurement legislative framework that smart cities should adopt in order to make strategic use of innovative procurement.
Blame It on Individual or Organization Environment: What Predicts Workplace Deviance More?
Authors: Načinović Braje Ivana , Aleksić Ana , Rašić Jelavić Sanda
Published: June 2020

Deviant workplace behavior is one of the widely present employee behaviors that create significant organizational cost, create an unhealthy working environment, and lead to various social and psychological job- and non-job-related consequences. Although various personality, situational, and organizational factors have been analyzed as instigators of such behavior, literature calls for a more comprehensive approach that analyzes interaction and mutual effects of different sources of deviant behavior. This paper explores organizational culture and individual personality as the antecedents of deviant workplace behavior. A multilevel perspective is applied in empirical research that was done on a sample of 251 employees from 11 organizations in Croatia. Results of our research and hierarchical linear modeling imply that individual-related factors, namely, age and gender, as well as personality traits, are greater predictors of both individual and organizational deviance as opposed to organizational culture.