bluuebunny/crossref_metadata_2025 huggingface dataset:
GNSS/INS Integration with Integrity Monitoring for UAV No-fly Zone Management
Authors: Sun Rui , Zhang Wenyu , Zheng Jiazhu , Ochieng Washington Yotto
Published: February 2020

The rapidly increasing use of unmanned aerial vehicles pose a significant challenge to no-fly zone management. The vehicle state in flight should be available for the whole mission, enabling an alert to be issued to the relevant users and entities at an appropriate time and location before intrusion into a no-fly zone. In addition to spatial databases and other control mechanisms, the navigation system used must have the required accuracy, integrity, continuity, and availability. In this paper, the accuracy and integrity requirements, and the positioning system for no-fly zone unmanned aerial vehicle management are specified. The proposed positioning system integrates global navigation satellite systems (GNSS) and inertial navigation system (INS) in the measurement domain. An integrity monitoring layer is incorporated for fault detection and exclusion as well as real-time horizontal protection level computation functions. Experimental results show that the algorithm proposed is capable of delivering accuracy and integrity requirements for unmanned aerial vehicle (UAV) no-fly zone management.
Monitoring Droughts in the Greater Changbai Mountains Using Multiple Remote Sensing-Based Drought Indices
Authors: Han Yang , Li Ziying , Huang Chang , Zhou Yuyu , Zong Shengwei , Hao Tianyi , Niu Haofang , Yao Haiyan
Published: February 2020

Various drought indices have been developed to monitor drought conditions. Each index has typical characteristics that make it applicable to a specific environment. In this study, six popular drought indices, namely, precipitation condition index (PCI), temperature condition index (TCI), vegetation condition index (VCI), vegetation health index (VHI), scaled drought condition index (SDCI), and temperature–vegetation dryness index (TVDI), have been used to monitor droughts in the Greater Changbai Mountains(GCM) in recent years. The spatial pattern and temporal trend of droughts in this area in the period 2001–2018 were explored by calculating these indices from multi-source remote sensing data. Significant spatial–temporal variations were identified. The results of a slope analysis along with the F-statistic test showed that up to 20% of the study area showed a significant increasing or decreasing trend in drought. It was found that some drought indices cannot be explained by meteorological observations because of the time lag between meteorological drought and vegetation response. The drought condition and its changing pattern differ from various land cover types and indices, but the relative drought situation of different landforms is consistent among all indices. This work provides a basic reference for reasonably choosing drought indices for monitoring drought in the GCM to gain a better understanding of the ecosystem conditions and environment.
Statistical Applications to Downscale GRACE-Derived Terrestrial Water Storage Data and to Fill Temporal Gaps
Authors: Sahour Hossein , Sultan Mohamed , Vazifedan Mehdi , Abdelmohsen Karem , Karki Sita , Yellich John , Gebremichael Esayas , Alshehri Fahad , Elbayoumi Tamer
Published: February 2020

The Gravity Recovery and Climate Experiment (GRACE) has been successfully used to monitor variations in terrestrial water storage (GRACETWS) and groundwater storage (GRACEGWS) across the globe, yet such applications are hindered on local scales by the limited spatial resolution of GRACE data. Using the Lower Peninsula of Michigan as a test site, we developed optimum procedures to downscale GRACE Release-06 monthly mascon solutions. A four-fold exercise was conducted. Cluster analysis was performed to identify the optimum number and distribution of clusters (areas) of contiguous pixels of similar geophysical signals (GRACETWS time series); three clusters were identified (cluster 1: 13,700 km2; cluster 2: 59,200 km2; cluster 3: 33,100 km2; Step I). Variables (total precipitation, normalized difference vegetation index (NDVI), snow cover, streamflow, Lake Michigan level, Lake Huron level, land surface temperature, soil moisture, air temperature, and evapotranspiration (ET)), which could potentially contribute to, or correlate with, GRACETWS over the test site were identified, and the dataset was randomly partitioned into training (80%) and testing (20%) datasets (Step II). Multivariate regression, artificial neural network, and extreme gradient boosting techniques were applied on the training dataset for each of the identified clusters to extract relationships between the identified hydro-climatic variables and GRACETWS solutions on a coarser scale (13,700–33,100 km2), and were used to estimate GRACETWS at a spatial resolution matching that of the fine-scale (0.125° × 0.125° or 120 km2) inputs. The statistical models were evaluated by comparing the observed and modeled GRACETWS values using the R-squared, the Nash–Sutcliffe model efficiency coefficient (NSE), and the normalized root-mean-square error (NRMSE; Step III). Lastly, temporal variations in GRACEGWS were extracted using outputs of land surface models and those of the optimum downscaling methodology (downscaled GRACETWS) (Step IV). Findings demonstrate that (1) consideration should be given to the cluster-based extreme gradient boosting technique in downscaling GRACETWS for local applications given their apparent enhanced performance (average value: R-squared: 0.86; NRMSE 0.37; NSE 0.86) over the multivariate regression (R-squared: 0.74; NRMSE 0.56; NSE 0.64) and artificial neural network (R-squared: 0.76; NRMSE 0.5; NSE 0.37) methods; and (2) identifying local hydrologic variables and the optimum downscaling approach for individual clusters is critical to implementing this method. The adopted method could potentially be used for groundwater management purposes on local scales in the study area and in similar settings elsewhere.
First Evidence of Mesoscale Ocean Eddies Signature in GNSS Reflectometry Measurements
Authors: Hoseini Mostafa , Asgarimehr Milad , Zavorotny Valery , Nahavandchi Hossein , Ruf Chris , Wickert Jens
Published: February 2020

Feasibility of sensing mesoscale ocean eddies using spaceborne Global Navigation Satellite Systems-Reflectometry (GNSS-R) measurements is demonstrated for the first time. Measurements of Cyclone GNSS (CYGNSS) satellite missions over the eddies, documented in the Aviso eddy trajectory atlas, are studied. The investigation reports on the evidence of normalized bistatic radar cross section ( σ 0 ) responses over the center or the edges of the eddies. A statistical analysis using profiles over eddies in 2017 is carried out. The potential contributing factors leaving the signature in the measurements are discussed. The analysis of GNSS-R observations collocated with ancillary data from the European Centre for Medium-Range Weather Forecasts (ECMWF) Reanalysis-5 (ERA-5) shows strong inverse correlations of σ 0 with the sensible heat flux and surface stress in certain conditions.
Multifractal Detrended Cross-Correlation Analysis of Global Methane and Temperature
Authors: Tzanis Chris , Koutsogiannis Ioannis , Philippopoulos Kostas , Kalamaras Nikolaos
Published: February 2020

Multifractal Detrended Cross-Correlation Analysis (MF-DCCA) was applied to time series of global methane concentrations and remotely-sensed temperature anomalies of the global lower and mid-troposphere, with the purpose of investigating the multifractal characteristics of their cross-correlated time series and examining their interaction in terms of nonlinear analysis. The findings revealed the multifractal nature of the cross-correlated time series and the existence of positive persistence. It was also found that the cross-correlation in the lower troposphere displayed more abundant multifractal characteristics when compared to the mid-troposphere. The source of multifractality in both cases was found to be mainly the dependence of long-range correlations on different fluctuation magnitudes. Multifractal Detrended Fluctuation Analysis (MF-DFA) was also applied to the time series of global methane and global lower and mid-tropospheric temperature anomalies to separately study their multifractal properties. From the results, it was found that the cross-correlated time series exhibit similar multifractal characteristics to the component time series. This could be another sign of the dynamic interaction between the two climate variables.
Automatic Mapping of Center Pivot Irrigation Systems from Satellite Images Using Deep Learning
Authors: Saraiva Marciano , Protas Églen , Salgado Moisés , Souza Carlos
Published: February 2020

The availability of freshwater is becoming a global concern. Because agricultural consumption has been increasing steadily, the mapping of irrigated areas is key for supporting the monitoring of land use and better management of available water resources. In this paper, we propose a method to automatically detect and map center pivot irrigation systems using U-Net, an image segmentation convolutional neural network architecture, applied to a constellation of PlanetScope images from the Cerrado biome of Brazil. Our objective is to provide a fast and accurate alternative to map center pivot irrigation systems with very high spatial and temporal resolution imagery. We implemented a modified U-Net architecture using the TensorFlow library and trained it on the Google cloud platform with a dataset built from more than 42,000 very high spatial resolution PlanetScope images acquired between August 2017 and November 2018. The U-Net implementation achieved a precision of 99% and a recall of 88% to detect and map center pivot irrigation systems in our study area. This method, proposed to detect and map center pivot irrigation systems, has the potential to be scaled to larger areas and improve the monitoring of freshwater use by agricultural activities.
Silicon Microcantilever Sensors to Detect the Reversible Conformational Change of a Molecular Switch, Spiropyan
Authors: Grogan Catherine , Amarandei George , Lawless Shauna , Pedreschi Fran , Lyng Fiona , Benito-Lopez Fernando , Raiteri Roberto , Florea Larisa
Published: February 2020

The high sensitivity of silicon microcantilever sensors has expanded their use in areas ranging from gas sensing to bio-medical applications. Photochromic molecules also represent promising candidates for a large variety of sensing applications. In this work, the operating principles of these two sensing methods are combined in order to detect the reversible conformational change of a molecular switch, spiropyran. Thus, arrays of silicon microcantilever sensors were functionalized with spiropyran on the gold covered side and used as test microcantilevers. The microcantilever deflection response was observed, in five sequential cycles, as the transition from the spiropyran (SP) (CLOSED) to the merocyanine (MC) (OPEN) state and vice-versa when induced by UV and white light LED sources, respectively, proving the reversibility capabilities of this type of sensor. The microcantilever deflection direction was observed to be in one direction when changing to the MC state and in the opposite direction when changing back to the SP state. A tensile stress was induced in the microcantilever when the SP to MC transition took place, while a compressive stress was observed for the reverse transition. These different type of stresses are believed to be related to the spatial conformational changes induced in the photochromic molecule upon photo-isomerisation.
Wearable Sensor System to Monitor Physical Activity and the Physiological Effects of Heat Exposure
Authors: Pham Sean , Yeap Danny , Escalera Gisela , Basu Rupa , Wu Xiangmei , Kenyon Nicholas J. , Hertz-Picciotto Irva , Ko Michelle J. , Davis Cristina E.
Published: February 2020

Mobile health monitoring via non-invasive wearable sensors is poised to advance telehealth for older adults and other vulnerable populations. Extreme heat and other environmental conditions raise serious health challenges that warrant monitoring of real-time physiological data as people go about their normal activities. Mobile systems could be beneficial for many communities, including elite athletes, military special forces, and at-home geriatric monitoring. While some commercial monitors exist, they are bulky, require reconfiguration, and do not fit seamlessly as a simple wearable device. We designed, prototyped and tested an integrated sensor platform that records heart rate, oxygen saturation, physical activity levels, skin temperature, and galvanic skin response. The device uses a small microcontroller to integrate the measurements and store data directly on the device for up to 48+ h. continuously. The device was compared to clinical standards for calibration and performance benchmarking. We found that our system compared favorably with clinical measures, such as fingertip pulse oximetry and infrared thermometry, with high accuracy and correlation. Our novel platform would facilitate an individualized approach to care, particularly those whose access to healthcare facilities is limited. The platform also can be used as a research tool to study physiological responses to a variety of environmental conditions, such as extreme heat, and can be customized to incorporate new sensors to explore other lines of inquiry.
Connected Elbow Exoskeleton System for Rehabilitation Training Based on Virtual Reality and Context-Aware
Authors: de la Iglesia Daniel H. , Mendes André Sales , González Gabriel Villarrubia , Jiménez-Bravo Diego M. , de Paz Santana Juan F.
Published: February 2020

Traditional physiotherapy rehabilitation systems are evolving into more advanced systems based on exoskeleton systems and Virtual Reality (VR) environments that enhance and improve rehabilitation techniques and physical exercise. In addition, due to current connected systems and paradigms such as the Internet of Things (IoT) or Ambient Intelligent (AmI) systems, it is possible to design and develop advanced, effective, and low-cost medical tools that patients may have in their homes. This article presents a low-cost exoskeleton for the elbow that is connected to a Context-Aware architecture and thanks to a VR system the patient can perform rehabilitation exercises in an interactive way. The integration of virtual reality technology in rehabilitation exercises provides an intensive, repetitive and task-oriented capacity to improve patient motivation and reduce work on medical professionals. One of the system highlights is the intelligent ability to generate new exercises, monitor the exercises performed by users in search of progress or possible problems and the dynamic modification of the exercises characteristics. The platform also allows the incorporation of commercial medical sensors capable of collecting valuable information for greater accuracy in the diagnosis and evolution of patients. A case study with real patients with promising results has been carried out.
Message-Based Communication for Heterogeneous Internet of Things Systems
Authors: Oniga Bogdan , Denis Leon , Dadarlat Vasile , Munteanu Adrian
Published: February 2020

The Internet of Things (IoT) domain presents a wide spectrum of technologies for building IoT applications. The requirements are varying from one application to another granting uniqueness to each IoT system. Each application demands custom implementations to achieve efficient, secure and cost-effective environments. They pose a set of properties that cannot be addressed by a single-based protocol IoT network. Such properties are achievable by designing a heterogeneous IoT system, which integrates diverse IoT protocols and provides a network management solution to efficiently manage the system components. This paper proposes an IoT message-based communication model applied atop the IoT protocols in order to achieve functional scalability and network management transparency agnostic to the employed communication protocol. The paper evaluates the proposed communication model and proves its functional scalability in a heterogeneous IoT system. The experimental assessment compares the payload size of the proposed system with respect to the LwM2M standard, a protocol designed specifically for IoT applications. In addition, the paper discusses the energy consumption introduced by the proposed model as well as the options available to reduce such impact.
Multi-under-Actuated Unmanned Surface Vessel Coordinated Path Tracking
Authors: Li Zefang , Liu Zhong , Zhang Jianqiang
Published: February 2020

Multi-under-actuated unmanned surface vehicles (USV) path tracking control is studied and decoupled by virtue of decentralized control. First, an improved integral line-of-sight guidance strategy is put forward and combined with feedback control to design the path tracking controller and realize the single USV path tracking in the horizontal plane. Second, graph theory is utilized to design the decentralized velocity coordination controller for USV formation, so that multiple USVs could consistently realize the specified formation to the position and velocity of the expected path. Third, cascade system theory and Lyapunov stability are used to respectively prove the uniform semi-global exponential stability of single USV path tracking control system and the global asymptotic stability and uniform local exponential stability of coordinated formation system. At last, simulation and field experiment are conducted to analyze and verify the advancement and effectiveness of the proposed algorithms in this paper.
A Real-Time 3D Measurement System for the Blast Furnace Burden Surface Using High-Temperature Industrial Endoscope
Authors: Xu Tianxiang , Chen Zhipeng , Jiang Zhaohui , Huang Jiancai , Gui Weihua
Published: February 2020

Capturing the three-dimensional (3D) shape of the burden surface of a blast furnace (BF) in real-time with high accuracy is crucial for improving gas flow distribution, optimizing coke operation, and stabilizing BF operation. However, it is difficult to perform 3D shape measurement of the burden surface in real-time during the ironmaking process because of the high-temperature, high-dust, and lightless enclosed environment inside the BF. To solve this problem, a real-time 3D measurement system is developed in this study by combining an industrial endoscope with a virtual multi-head camera array 3D reconstruction method. First, images of the original burden surface are captured using a purpose-built industrial endoscope. Second, a novel micro-pixel luminance polarization method is proposed and applied to compensate for the heavy noise in the backlit images due to high dust levels and poor light in the enclosed environment. Third, to extract depth information, a multifeature-based depth key frame classifier is designed to filter out images with high levels of clarity and displacement. Finally, a 3D shape burden surface reconstruction method based on a virtual multi-head camera array is proposed for capturing the real-time 3D shape of the burden surface in an operational BF. The results of an industrial experiment illustrate that the proposed method can measure the 3D shape of the entire burden surface and provide reliable burden surface shape information for BF control.
Real-Time Facial Affective Computing on Mobile Devices
Authors: Guo Yuanyuan , Xia Yifan , Wang Jing , Yu Hui , Chen Rung-Ching
Published: February 2020

Convolutional Neural Networks (CNNs) have become one of the state-of-the-art methods for various computer vision and pattern recognition tasks including facial affective computing. Although impressive results have been obtained in facial affective computing using CNNs, the computational complexity of CNNs has also increased significantly. This means high performance hardware is typically indispensable. Most existing CNNs are thus not generalizable enough for mobile devices, where the storage, memory and computational power are limited. In this paper, we focus on the design and implementation of CNNs on mobile devices for real-time facial affective computing tasks. We propose a light-weight CNN architecture which well balances the performance and computational complexity. The experimental results show that the proposed architecture achieves high performance while retaining the low computational complexity compared with state-of-the-art methods. We demonstrate the feasibility of a CNN architecture in terms of speed, memory and storage consumption for mobile devices by implementing a real-time facial affective computing application on an actual mobile device.
Secure Authentication and Credential Establishment in Narrowband IoT and 5G
Authors: Sanchez-Gomez Jesus , Garcia-Carrillo Dan , Marin-Perez Rafael , Skarmeta Antonio
Published: February 2020

Security is critical in the deployment and maintenance of novel IoT and 5G networks. The process of bootstrapping is required to establish a secure data exchange between IoT devices and data-driven platforms. It entails, among other steps, authentication, authorization, and credential management. Nevertheless, there are few efforts dedicated to providing service access authentication in the area of constrained IoT devices connected to recent wireless networks such as narrowband IoT (NB-IoT) and 5G. Therefore, this paper presents the adaptation of bootstrapping protocols to be compliant with the 3GPP specifications in order to enable the 5G feature of secondary authentication for constrained IoT devices. To allow the secondary authentication and key establishment in NB-IoT and 4G/5G environments, we have adapted two Extensible Authentication Protocol (EAP) lower layers, i.e., PANATIKI and LO-CoAP-EAP. In fact, this approach presents the evaluation of both aforementioned EAP lower layers, showing the contrast between a current EAP lower layer standard, i.e., PANA, and one specifically designed with the constraints of IoT, thus providing high flexibility and scalability in the bootstrapping process in 5G networks. The proposed solution is evaluated to prove its efficiency and feasibility, being one of the first efforts to support secure service authentication and key establishment for constrained IoT devices in 5G environments.
Highly Selective Electrochemiluminescence Sensor Based on Molecularly Imprinted-quantum Dots for the Sensitive Detection of Cyfluthrin
Authors: Xu Jinjin , Zhang Rongrong , Liu Chenxi , Sun Aili , Chen Jiong , Zhang Zeming , Shi Xizhi
Published: February 2020

A highly selective and sensitive molecularly imprinted electrochemiluminescence (MIECL) sensor was developed based on the multiwall carbon nanotube (MWCNT)-enhanced molecularly imprinted quantum dots (MIP-QDs) for the rapid determination of cyfluthrin (CYF). The MIP-QDs fabricated by surface grafting technique exhibited excellent selective recognition to CYF, resulting in a specific decrease of ECL signal at the MWCNT/MIP-QD modified electrode. Under optimal conditions, the MIECL signal was proportional to the logarithm of the CYF concentration in the range of 0.2 µg/L to 1.0 × 103 µg/L with a determination coefficient of 0.9983. The detection limit of CYF was 0.05 µg/L, and good recoveries ranging from 86.0% to 98.6% were obtained in practical samples. The proposed MIECL sensor provides a novel, rapid, high sensitivity detection strategy for successfully analyzing CYF in fish and seawater samples.
Artificial Intelligence-Based Hole Quality Prediction in Micro-Drilling Using Multiple Sensors
Authors: Ranjan Jitesh , Patra Karali , Szalay Tibor , Mia Mozammel , Gupta Munish Kumar , Song Qinghua , Krolczyk Grzegorz , Chudy Roman , Pashnyov Vladislav Alievich , Pimenov Danil Yurievich
Published: February 2020

The prevalence of micro-holes is widespread in mechanical, electronic, optical, ornaments, micro-fluidic devices, etc. However, monitoring and detection tool wear and tool breakage are imperative to achieve improved hole quality and high productivity in micro-drilling. The various multi-sensor signals are used to monitor the condition of the tool. In this work, the vibration signals and cutting force signals have been applied individually as well as in combination to determine their effectiveness for tool-condition monitoring applications. Moreover, they have been used to determine the best strategies for tool-condition monitoring by prediction of hole quality during micro-drilling operations with 0.4 mm micro-drills. Furthermore, this work also developed an adaptive neuro fuzzy inference system (ANFIS) model using different time domains and wavelet packet features of these sensor signals for the prediction of the hole quality. The best prediction of hole quality was obtained by a combination of different sensor features in wavelet domain of vibration signal. The model’s predicted results were found to exert a good agreement with the experimental results.
Electroplating of Multiple Materials in Parallel Using Patterned Gels with Applications in Electrochemical Sensing
Authors: Mohammadzadeh Aliakbar , Fox-Robichaud Alison , Selvaganapathy P. Ravi
Published: February 2020

Electrodeposition is a versatile technique for the fabrication of electrodes in micro-electroanalytical devices. Conductive but low-cost materials, such as copper, can be coated with functional yet higher-cost materials such as gold or silver using electrodeposition to lower the overall cost while maintaining functionality. When the electrodeposition of multiple materials is required, current methods use a multistep process that deposits one material at a time, which requires a significant amount of time and a significant number of steps. Additionally, they use a large volume of electrolytes suitable for coating large objects, which is wasteful and unnecessary for the prototyping or coating of microelectrodes with a small area. In this paper, a new method of electroplating is introduced in which we used gels to immobilize and pattern electroplating electrolytes on a substrate surface. Agarose, as an immobilizing medium, enables the immersion of the substrate in a common working electrolyte without cross-mixing different electrolytes. We demonstrate the printing of jelly electrolytes by using spot-dispensing or microfluidic flow. Xurographically patterned films laminated on the substrate function as a mask and confine the printed gels to desired locations. After printing, the substrate is placed in a common working electrolyte container, and multimaterial patterns are produced through the application of an electrical current in a single step.
A New Edge Patch with Rotation Invariance for Object Detection and Pose Estimation
Authors: Tong Xunwei , Li Ruifeng , Ge Lianzheng , Zhao Lijun , Wang Ke
Published: February 2020

Local patch-based methods of object detection and pose estimation are promising. However, to the best of the authors’ knowledge, traditional red-green-blue and depth (RGB-D) patches contain scene interference (foreground occlusion and background clutter) and have little rotation invariance. To solve these problems, a new edge patch is proposed and experimented with in this study. The edge patch is a local sampling RGB-D patch centered at the edge pixel of the depth image. According to the normal direction of the depth edge, the edge patch is sampled along a canonical orientation, making it rotation invariant. Through a process of depth detection, scene interference is eliminated from the edge patch, which improves the robustness. The framework of the edge patch-based method is described, and the method was evaluated on three public datasets. Compared with existing methods, the proposed method achieved a higher average F1-score (0.956) on the Tejani dataset and a better average detection rate (62%) on the Occlusion dataset, even in situations of serious scene interference. These results showed that the proposed method has higher detection accuracy and stronger robustness.
An Oximetry Based Wireless Device for Sleep Apnea Detection
Authors: Mendonça Fábio , Mostafa Sheikh Shanawaz , Morgado-Dias Fernando , Ravelo-García Antonio G.
Published: February 2020

Sleep related disorders can severely disturb the quality of sleep. Among these disorders, obstructive sleep apnea (OSA) is highly prevalent and commonly undiagnosed. Polysomnography is considered to be the gold standard exam for OSA diagnosis. Even though this multi-parametric test provides highly accurate results, it is time consuming, labor-intensive, and expensive. A non-invasive and easy to self-assemble home monitoring device was developed to address these issues. The device can perform the OSA diagnosis at the patient’s home and a specialized technician is not required to supervise the process. An automatic scoring algorithm was developed to examine the blood oxygen saturation signal for a minute-by-minute OSA assessment. It was performed by analyzing statistical and frequency-based features that were fed to a classifier. Afterward, the ratio of the number of minutes classified as OSA to the time in bed in minutes was compared with a threshold for the global (subject-based) OSA diagnosis. The average accuracy, sensitivity, specificity, and area under the receiver operating characteristic curve for the minute-by-minute assessment were, respectively, 88%, 80%, 91%, and 0.86. The subject-based accuracy was 95%. The performance is in the same range as the best state of the art methods for the models based only on the blood oxygen saturation analysis. Therefore, the developed model has the potential to be employed in clinical analysis.
Smartphone Architecture for Edge-Centric IoT Analytics
Authors: Marah Bockarie Daniel , Jing Zilong , Ma Tinghuai , Alsabri Raeed , Anaadumba Raphael , Al-Dhelaan Abdullah , Al-Dhelaan Mohammed
Published: February 2020

The current baseline architectures in the field of the Internet of Things (IoT) strongly recommends the use of edge computing in the design of the solution applications instead of the traditional approach which solely uses the cloud/core for analysis and data storage. This research, therefore, focuses on formulating an edge-centric IoT architecture for smartphones which are very popular electronic devices that are capable of executing complex computational tasks at the network edge. A novel smartphone IoT architecture (SMIoT) is introduced that supports data capture and preprocessing, model (i.e., machine learning models) deployment, model evaluation and model updating tasks. Moreover, a novel model evaluation and updating scheme is provided which ensures model validation in real-time. This ensures a sustainable and reliable model at the network edge that automatically adjusts to changes in the IoT data subspace. Finally, the proposed architecture is tested and evaluated using an IoT use case.
Model-Aided Localization and Navigation for Underwater Gliders Using Single-Beacon Travel-Time Differences
Authors: Sun Jie , Hu Feng , Jin Wenming , Wang Jin , Wang Xu , Luo Yeteng , Yu Jiancheng , Zhang Aiqun
Published: February 2020

An accurate motion model and reliable measurements are required for autonomous underwater vehicle localization and navigation in underwater environments. However, without a propeller, underwater gliders have limited maneuverability and carrying capacity, which brings difficulties for modeling and measuring. In this paper, an extended Kalman filter (EKF)-based method, combining a modified kinematic model of underwater gliders with the travel-time differences between signals received from a single beacon, is proposed for estimating the glider positions in a predict-update cycle. First, to accurately establish a motion model for underwater gliders moving in the ocean, we introduce two modification parameters, the attack and drift angles, into a kinematic model of underwater gliders, along with depth-averaged current velocities. The attack and drift angles are calculated based on the coefficients of hydrodynamic forces and the sensor-measured angle variation over time. Then, instead of satisfying synchronization requirements, the travel-time differences between signals received from a single beacon, multiplied by the sound speed, are taken as the measurements. To further reduce the EKF estimation error, the Rauch-Tung-Striebel (RTS) smoothing method is merged into the EKF system. The proposed method is tested in a virtual spatiotemporal environment from an ocean model. The experimental results show that the performance of the RTS-EKF estimate is improved when compared with the motion model estimate, especially by 46% at the inflection point, at least in the particular study developed in this article.
A Prototype Framework Design for Assisting the Detection of Atrial Fibrillation Using a Generic Low-Cost Biomedical Sensor
Authors: Pérez-Valero Jesús , Garcia-Sanchez Antonio-Javier , Ruiz Marín Manuel , Garcia-Haro Joan
Published: February 2020

Cardiovascular diseases are the leading cause of death around the world. As a result, low-cost biomedical sensors have been gaining importance in business and research over the last few decades. Their main benefits include their small size, light weight, portability and low power consumption. Despite these advantages, they are not generally used for clinical monitoring mainly because of their low accuracy in data acquisition. In this emerging technological context, this paper contributes by discussing a methodology to help practitioners build a prototype framework based on a low-cost commercial sensor. The resulting application consists of four modules; namely, a digitalization module whose input is an electrocardiograph signal in portable document format (PDF) or joint photographic expert group format (JPEG), a module to further process and filter the digitalized signal, a selectable data calibration module and, finally, a module implementing a classification algorithm to distinguish between individuals with normal sinus rhythms and those with atrial fibrillation. This last module employs our recently published symbolic recurrence quantification analysis (SRQA) algorithm on a time series of RR intervals. Moreover, we show that the algorithm applies to any biomedical low-cost sensor, achieving good results without requiring any calibration of the raw data acquired. In addition, it has been validated with a well-accepted public electrocardiograph (ECG) data base, obtaining 87.65%, 91.84%, and 91.31% in terms of sensitivity, specificity and accuracy, respectively.
The Design and Verification of an Active SAMSR Ultrasonic Guided Wave Monitoring System with Ultra-Low Crosstalk
Authors: Xue Wendong , Yang Mengjiao , Hong Deming , Wu Di , Wang Yishou , Qing Xinlin
Published: February 2020

Due to long propagation distance and high sensitivity to a variety of damages, ultrasonic guided wave technologies have been widely applied in the damage detection or health monitoring of pipe networks and large plate-like structures. However, there are two important problems to be solved when applying this technology; namely, the large scanning time required for monitoring large-scaled structures and the serious crosstalk between the actuation and receiving signals, especially when monitoring hot-spot regions. Therefore, this study mainly designed key parts, such as the matrix switcher and attenuation circuit. The single-actuation and multiple-simultaneous-reception (SAMSR) mechanism based on an analog switching matrix and a low noise charge amplifier circuit was designed and integrated with the SPI control bus to shorten the scanning time. Moreover, a two-stage attenuation circuit with an interlocking isolation structure is presented to effectively isolate the receiving signals from the actuation signals to obtain ultra-low crosstalk even under a high voltage actuation source. In this study, the designed matrix switcher and other components were integrated into the developed ultrasonic guided wave monitoring system. Several experiments were conducted on a stiffened composite structure to illustrate the effectivity of the developed SAMSR ultrasonic guided wave system by comparing the signals collected with those from a commercial ultrasonic guided wave system.
DMD Mask Construction to Suppress Blocky Structural Artifacts for Medium Wave Infrared Focal Plane Array-Based Compressive Imaging
Authors: Wu Zimu , Wang Xia
Published: February 2020

With medium wave infrared (MWIR) focal plane array-based (FPA) compressive imaging (CI), high-resolution images can be obtained with a low-resolution MWIR sensor. However, restricted by the size of digital micro-mirror devices (DMD), aperture interference is inevitable. According to the system model of FPA CI, aperture interference aggravates the blocky structural artifacts (BSA) in the reconstructed images, which reduces the image quality. In this paper, we propose a novel DMD mask design strategy, which can effectively suppress BSA and maximize the reconstruction efficiency. Compared with random binary codes, the storage space and computation cost can be significantly reduced. Based on the actual MWIR FPA CI system, we demonstrate the proposed DMD masks can effectively suppress the BSA in the reconstructed images. In addition, a new evaluation index, blocky root mean square error, is proposed to indicate the BSA in FPA CI.
Noise Removal in the Developing Process of Digital Negatives
Authors: Szczepański Marek , Giemza Filip
Published: February 2020

Most modern color digital cameras are equipped with a single image sensor with a color filter array (CFA). One of the most important stages of preprocessing is noise reduction. Most research related to this topic ignores the problem associated with the actual color image acquisition process and assumes that we are processing the image in the sRGB space. In the presented paper, the real process of developing raw images obtained from the CFA sensor was analyzed. As part of the work, a diverse database of test images in the form of a digital negative and its reference version was prepared. The main problem posed in the work was the location of the denoising and demosaicing algorithms in the entire raw image processing pipeline. For this purpose, all stages of processing the digital negative are reproduced. The process of noise generation in the image sensors was also simulated, parameterizing it with ISO sensitivity for a specific CMOS sensor. In this work, we tested commonly used algorithms based on the idea of non-local means, such as NLM or BM3D, in combination with various techniques of interpolation of CFA sensor data. Our experiments have shown that the use of noise reduction methods directly on the raw sensor data, improves the final result only in the case of highly disturbed images, which corresponds to the process of image acquisition in difficult lighting conditions.
Pharmacies for the Pharmacists—Ukrainian Fears and Polish Experiences
Authors: Zaprutko Tomasz , Hromovyk Bohdan , Lesyk Roman , Lesyk Lilia , Kremin Yuliia , Kus Krzysztof , Kopciuch Dorota , Ratajczak Piotr , Paczkowska Anna , Nowakowska Elżbieta
Published: February 2020

In 2017, a regulation referred to as “pharmacies for the pharmacists” was implemented in Poland, and Ukraine is going to implement a similar act of law. The study was to collect Ukrainian pharmacists’ opinions about the upcoming market regulation and to compare their views with opinions obtained from Polish pharmacists collected two years following the amendment of this legislation. The study was conducted in Poland and Ukraine using a self-designed questionnaire. Of 2162 questionnaires received, 2043 were included in the study (1623 from Ukraine and 420 from Poland). Ukrainian pharmacists (76.8%) feared that medicine prices would increase. Moreover, they presented concerns related to poorer access to pharmaceuticals and reduced turnovers of pharmacies. Two years after the market regulation, 55.23% of Polish pharmacists pointed out that none of the fears reported in Ukraine were observed in Poland. However, 33.10% revealed that market regulation led to “a reduction in the number of pharmacies”. Ukrainian pharmacists are afraid of community pharmacies’ regulation. Polish pharmacists, however, have not observed such problems during the two years following the market regulation. The only noticeable market change in Poland was the reduced number of pharmacies.
The Roads, Tracks, Paths, and Ropeways of the First World War: An Opportunity to Preserve, Maintain, and Valorize Alpine Landscape
Authors: Gatti Maria Paola , Indrigo Antonella
Published: February 2020

This research aims at understanding how to reuse infrastructure built in the Alps during the First World War to facilitate access to upland areas, increasingly used for tourism, sports, and hiking, but neglected in terms of maintenance. In other words, the main goal here is to improve and preserve the state of the mountain environment (including forests, meadows, pastures, etc.) through the reuse of historical infrastructures such as ropeways and mule tracks. Any form of reactivation of the now abandoned military logistics system, consisting of roads, mule-tracks, paths, and ropeways would enable the currently depopulated places to initiate a new and virtuous cycle. In this way, controlled planning would allow adequate maintenance to be provided for those natural and anthropic landscapes which have been progressively deprived of a productive role. The condition of abandonment and the lack of maintenance of the Alpine landscape have allowed the abundant rains of recent years, which are the result of climate change, to damage the forests of northern Italy and cause a series of hydrogeological landslides. That said, it could be assumed that the conversion of abandoned mule tracks, paths, and ropeways would not only help preserve a healthy Alpine environment but would also contribute to control these phenomena. Furthermore, it would be a way of giving new use to the historical infrastructures that played such an important role in the early 1900s, recognizing in this way their historical value. The transformation of the Alpine landscape and the building of the infrastructures involved all the lines of the front which were located on the mountains. Therefore, the choice of the Asiago Plateau, a portion of the Venetian Prealps comprised between the provinces of Vicenza and Trento, is just paradigmatic, namely, it reflects the features of a more widespread situation. However, the laws promoted by the Italian state have, as their objective, the recovery and maintenance of forts, trenches and buildings of historical value, but do not include the mountain territory that surrounds them. Therefore, reusing the infrastructures from the First World War would allow the whole landscape to be kept active.
Investing In CSR Pays You Back in Many Ways! The Case of Perceptual, Attitudinal and Behavioral Outcomes of Customers
Authors: Ahmed Ishfaq , Nazir Mian Sajid , Ali Imran , Nurunnabi Mohammad , Khalid Arooj , Shaukat Muhammad Zeeshan
Published: February 2020

Researchers and scholars have widely attributed corporate social responsibility (CSR) to enormous outcomes. However, the customer-specific outcomes are either less investigated or lack clarity. By focusing on perceptual, attitudinal and behavioral outcomes of CSR, this study entails that CSR influences customers’ citizenship behavior (behavioral outcome) both directly and indirectly (through service quality and affective commitment—perceptual and attitudinal outcomes). Survey data collected from 669 fast-food restaurant customers were analyzed through the structural equation modeling technique. The results revealed a positive and significant relationship between restaurants’ CSR efforts and customers’ behavioral responses in terms of citizenship behavior. Findings also highlight that CSR does not only have a direct relation but the sequential mediation mechanism also exists. The study extends the existing literature by focusing on the ignored causal link of CSR and customer citizenship behavior (CCB) by considering the service quality and affective commitment as an explanatory mechanism, and provides certain practical implications which could also be useful for managers of the restaurant industry to devise their socially responsible practices.
The Survival of Cultural Firms: A Study of Multiple Accounting Parameters in Spain
Authors: Muñoz Dueñas Ma del Pilar , Vaamonde Liste Antonio , Cabrita Maria do Rosário
Published: February 2020

Cultural firms are an important development factor in economic and social terms. Their objectives are often aimed at maintaining and disseminating the traditions and values of societies. The prosperity of these firms in a nation ensures that its tangible and intangible cultural heritage is made known to other nations and generations. Despite their importance, little is known about their survival and the factors associated with it. This paper analyses data from 6951 Spanish firms, of which 2105 are cultural firms. We have studied the survival of non-cultural firms in comparison with cultural firms and also the impact that profitability, solvency and indebtedness may have on their survival. We have used the Kaplan–Meier method in order to assess their survival and the Harrington–Fleming test and the Cox regression model to check the statistical significance of variables. These variables are key factors influencing the survival of cultural enterprises. Particularly, low solvency in firms increases by twenty the risk of disappearance. This paper contributes to literature highlighting some of the key factors for the survival of cultural enterprises. It provides administrations with a roadmap in order to implement measures for the promotion of the cultural industry, favouring the process of enhancement of cultural heritage.
Are Social Networks Sufficiently Used in Companies? Case Study in the Czech Republic
Authors: Marešová Petra , Fadeyi Oluwaseun , Kuča Kamil
Published: February 2020

Social media use is currently on the rise and companies find it useful for communicating with their customers or business associates. This paper aims to analyze perceived benefits and the use of social networks in Czech companies in relation to certain specifics of the company. A questionnaire survey was done in cooperation with the Regional Economic Chamber of Hradec Kralove region and a return rate of 2% was achieved. The Chi-square test and the Mann-Whitney test was used to understand the strength of the intensity of dependence of the basis of model coefficients. It was discovered that 55% of the companies surveyed use social networks, while 80% of companies regard them as an important part of business. Significant differences in the use of social networks were found based on the industries in which firms do their business. Industrial companies do not use social networks, compared to 72% of companies doing business in services who use social networks. It was also found that companies with more than 200 customers use social networks the most. Overall, the use of social networks in the Czech companies is low. The fact that only 52% of respondents analyze their efforts on social networks is especially startling. This results in unfulfilled organizational potential, which is more significant especially when compared with the results of foreign studies where the social networks are used by up to 96%.
Sustainable Use of Soils and Water: The Role of Environmental Land Use Conflicts
Authors: Pacheco Fernando A. L.
Published: February 2020

Sustainability is a utopia of societies, that could be achieved by a harmonious balance between socio-economic development and environmental protection, including the sustainable exploitation of natural resources. The present Special Issue addresses a multiplicity of realities that confirm a deviation from this utopia in the real world, as well as the concerns of researchers. These scholars point to measures that could help lead the damaged environment to a better status. The studies were focused on sustainable use of soils and water, as well as on land use or occupation changes that can negatively affect the quality of those resources. Some other studies attempt to assess (un)sustainability in specific regions through holistic approaches, like the land carrying capacity, the green gross domestic product or the eco-security models. Overall, the special issue provides a panoramic view of competing interests for land and the consequences for the environment derived therefrom.