bluuebunny/crossref_metadata_2025 huggingface dataset:
Underwater Hyperspectral Imaging Technology and Its Applications for Detecting and Mapping the Seafloor: A Review
Authors: Liu Bohan , Liu Zhaojun , Men Shaojie , Li Yongfu , Ding Zhongjun , He Jiahao , Zhao Zhigang
Published: September 2020

Common methods of ocean remote sensing and seafloor surveying are mainly carried out by airborne and spaceborne hyperspectral imagers. However, the water column hinders the propagation of sunlight to deeper areas, thus limiting the scope of observation. As an emerging technology, underwater hyperspectral imaging (UHI) is an extension of hyperspectral imaging technology in air conditions, and is undergoing rapid development for applications in shallow and deep-sea environments. It is a close-range, high-resolution approach for detecting and mapping the seafloor. In this paper, we focus on the concepts of UHI technology, covering imaging systems and the correction methods of eliminating the water column’s influence. The current applications of UHI, such as deep-sea mineral exploration, benthic habitat mapping, and underwater archaeology, are highlighted to show the potential of this technology. This review can provide an introduction and overview for those working in the field and offer a reference for those searching for literature on UHI technology.
Generating Comfortable Navigable Space for 3D Indoor Navigation Considering Users’ Dimensions
Authors: Zhen Wenjie , Yang Lin , Kwan Mei-Po , Zuo Zejun , Qian Haoyue , Zhou Shunping
Published: September 2020

Most existing indoor navigation methods implicitly treat indoor users as ideal points. However, the ignorance of individual 3D indoor space needs may result in that navigation users do not have enough space or comfortable space to move in a real situation. Therefore, this paper proposes a novel human-oriented navigation approach that considers users’ dimensions and interactions with indoor objects to establish comfortable navigable space. First, object space (O-Space) for users is derived according to their types (i.e., non-disabled people or disabled people) and functional space (F-Space) for indoor objects is determined according to their functions, locations, sizes, and interactions. Then, narrow gaps where users cannot pass through easily are calculated based on indoor obstacles defined by O-Space, the use of F-Space, and stationary objects. Finally, comfortable navigable space is established by excluding inappropriate sealed spaces that wrap indoor obstacles and narrow gaps of the entire indoor space. Two indoor navigation cases were conducted and the results demonstrate that our method could provide comfortable space and user-friendly paths that navigation users can navigate easily without stress. Furthermore, our method also shows great potential for improving user experience during navigation, especially in unfamiliar indoor environments and even emergencies.
A Novel End-To-End Fault Diagnosis Approach for Rolling Bearings by Integrating Wavelet Packet Transform into Convolutional Neural Network Structures
Authors: Xiong Shoucong , Zhou Hongdi , He Shuai , Zhang Leilei , Xia Qi , Xuan Jianping , Shi Tielin
Published: September 2020

Accidental failures of rotating machinery components such as rolling bearings may trigger the sudden breakdown of the whole manufacturing system, thus, fault diagnosis is vital in industry to avoid these massive economical costs and casualties. Since convolutional neural networks (CNN) are poor in extracting reliable features from original signal data, the time-frequency analysis method is usually called for to transform 1D signal into a 2D time-frequency coefficient matrix in which richer information could be exposed more easily. However, realistic fault diagnosis applications face a dilemma in that signal time-frequency analysis and fault classification cannot be implemented together, which means manual signal conversion work is also needed, which reduces the integrity and robustness of the fault diagnosis method. In this paper, a novel network named WPT-CNN is proposed for end-to-end intelligent fault diagnosis of rolling bearings. WPT-CNN creatively uses the standard deep neural network structure to realize the wavelet packet transform (WPT) time-frequency analysis function, which seamlessly integrates fault diagnosis domain knowledge into deep learning algorithms. The overall network architecture can be trained with gradient descent backpropagation algorithms, indicating that the time-frequency analysis module of WPT-CNN is also able to learn the dataset characteristics, adaptively representing signal information in the most suitable way. Two experimental rolling bearing fault datasets were used to validate the proposed method. Testing results showed that WPT-CNN obtained the testing accuracies of 99.73% and 99.89%, respectively, in two datasets, which exhibited a better and more reliable diagnosis performance than any other existing deep learning and machine learning methods.
Continuous Estimation of Knee Joint Angle Based on Surface Electromyography Using a Long Short-Term Memory Neural Network and Time-Advanced Feature
Authors: Ma Xunju , Liu Yali , Song Qiuzhi , Wang Can
Published: September 2020

Continuous joint angle estimation based on a surface electromyography (sEMG) signal can be used to improve the man-machine coordination performance of the exoskeleton. In this study, we proposed a time-advanced feature and utilized long short-term memory (LSTM) with a root mean square (RMS) feature and its time-advanced feature (RMSTAF; collectively referred to as RRTAF) of sEMG to estimate the knee joint angle. To evaluate the effect of joint angle estimation, we used root mean square error (RMSE) and cross-correlation coefficient ρ between the estimated angle and actual angle. We also compared three methods (i.e., LSTM using RMS, BPNN (back propagation neural network) using RRTAF, and BPNN using RMS) with LSTM using RRTAF to highlight its good performance. Five healthy subjects participated in the experiment and their eight muscle (i.e., rectus femoris (RF), biceps femoris (BF), semitendinosus (ST), gracilis (GC), semimembranosus (SM), sartorius (SR), medial gastrocnemius (MG), and tibialis anterior (TA)) sEMG signals were taken as algorithm inputs. Moreover, the knee joint angles were used as target values. The experimental results showed that, compared with LSTM using RMS, BPNN using RRTAF, and BPNN using RMS, the average RMSE values of LSTM using RRTAF were respectively reduced by 8.57%, 46.62%, and 68.69%, whereas the average ρ values were respectively increased by 0.31%, 4.15%, and 18.35%. The results demonstrated that LSTM using RRTAF, which contained the time-advanced feature, had better performance for estimating the knee joint motion.
Development of an Anthropomorphic Phantom of the Axillary Region for Microwave Imaging Assessment
Authors: Savazzi Matteo , Abedi Soroush , Ištuk Niko , Joachimowicz Nadine , Roussel Hélène , Porter Emily , O’Halloran Martin , Costa Jorge R. , Fernandes Carlos A. , Felício João M. , Conceição Raquel C.
Published: September 2020

We produced an anatomically and dielectrically realistic phantom of the axillary region to enable the experimental assessment of Axillary Lymph Node (ALN) imaging using microwave imaging technology. We segmented a thoracic Computed Tomography (CT) scan and created a computer-aided designed file containing the anatomical configuration of the axillary region. The phantom comprises five 3D-printed parts representing the main tissues of interest of the axillary region for the purpose of microwave imaging: fat, muscle, bone, ALNs, and lung. The phantom allows the experimental assessment of multiple anatomical configurations, by including ALNs of different size, shape, and number in several locations. Except for the bone mimicking organ, which is made of solid conductive polymer, we 3D-printed cavities to represent the fat, muscle, ALN, and lung and filled them with appropriate tissue-mimicking liquids. Existing studies about complex permittivity of ALNs have reported limitations. To address these, we measured the complex permittivity of both human and animal lymph nodes using the standard open-ended coaxial-probe technique, over the 0.5 GHz–8.5 GHz frequency band, thus extending current knowledge on dielectric properties of ALNs. Lastly, we numerically evaluated the effect of the polymer which constitutes the cavities of the phantom and compared it to the realistic axillary region. The results showed a maximum difference of 7 dB at 4 GHz in the electric field magnitude coupled to the tissues and a maximum of 10 dB difference in the ALN response. Our results showed that the phantom is a good representation of the axillary region and a viable tool for pre-clinical assessment of microwave imaging technology.
In-Service Detection and Quantification of Railway Wheel Flat by the Reflective Optical Position Sensor
Authors: Gao Run , He Qixin , Feng Qibo , Cui Jianying
Published: September 2020

Railway wheel tread flat is one of the main faults of railway wheels, which brings great harm to the safety of vehicle operation. In order to detect wheel flats dynamically and quantitatively when trains are running at high speed, a new wheel flat detection system based on the self-developed reflective optical position sensor is demonstrated in this paper. In this system, two sensors were mounted along each rail to measure the wheel-rail impact force of the entire circumference by detecting the displacement of the collimated laser spot. In order to establish a quantitative relationship between the sensor signal and the wheel flat length, a vehicle-track coupling dynamics analysis model was developed using the finite element method and multi-body dynamics method. The effects of train speed, load, wheel flat lengths, as well as the impact positions on impact forces were simulated and evaluated, and the measured data can be normalized according to the simulation results. The system was assessed through simulation and laboratory investigation, and real field tests were conducted to certify its validity and correctness. The system can determine the position of the flat wheel and can realize the quantification of the detected wheel flat, which has extensive application prospects.
On-Chip Selective Capture and Detection of Magnetic Fingerprints of Malaria
Authors: Milesi Francesca , Giacometti Marco , Coppadoro Lorenzo Pietro , Ferrari Giorgio , Fiore Gianfranco Beniamino , Bertacco Riccardo
Published: September 2020

The development of innovative diagnostic tests is fundamental in the route towards malaria eradication. Here, we discuss the sorting capabilities of an innovative test for malaria which allows the quantitative and rapid detection of all malaria species. The physical concept of the test exploits the paramagnetic property of infected erythrocytes and hemozoin crystals, the magnetic fingerprints of malaria common to all species, which allows them to undergo a selective magnetophoretic separation driven by a magnetic field gradient in competition with gravity. Upon separation, corpuscles concentrate at the surface of a silicon microchip where interdigitated electrodes are placed in close proximity to magnetic concentrators. The impedance variation proportional to the amount of attracted particles is then measured. The capability of our test to perform the selective detection of infected erythrocytes and hemozoin crystals has been tested by means of capture experiments on treated bovine red blood cells, mimicking the behavior of malaria-infected ones, and suspensions of synthetic hemozoin crystals. Different configuration angles of the chip with respect to gravity force and different thicknesses of the microfluidic chamber containing the blood sample have been investigated experimentally and by multiphysics simulations. In the paper, we describe the optimum conditions leading to maximum sensitivity and specificity of the test.
Real-Time Compact Environment Representation for UAV Navigation
Authors: Meng  Kaitao , Li  Deshi , He  Xiaofan , Liu  Mingliu , Song  Weitao
Published: September 2020

Recently, unmanned aerial vehicles (UAVs) have attracted much attention due to their on-demand deployment, high mobility, and low cost. For UAVs navigating in an unknown environment, efficient environment representation is needed due to the storage limitation of the UAVs. Nonetheless, building an accurate and compact environment representation model is highly non-trivial because of the unknown shape of the obstacles and the time-consuming operations such as finding and eliminating the environmental details. To overcome these challenges, a novel vertical strip extraction algorithm is proposed to analyze the probability density function characteristics of the normalized disparity value and segment the obstacles through an adaptive size sliding window. In addition, a plane adjustment algorithm is proposed to represent the obstacle surfaces as polygonal prism profiles while minimizing the redundant obstacle information. By combining these two proposed algorithms, the depth sensor data can be converted into the multi-layer polygonal prism models in real time. Besides, a drone platform equipped with a depth sensor is developed to build the compact environment representation models in the real world. Experimental results demonstrate that the proposed scheme achieves better performance in terms of precision and storage as compared to the baseline.
Rational Design of a User-Friendly Aptamer/Peptide-Based Device for the Detection of Staphylococcus aureus
Authors: Ronda Luca , Tonelli Alessandro , Sogne Elisa , Autiero Ida , Spyrakis Francesca , Pellegrino Sara , Abbiati Giorgio , Maffioli Elisa , Schulte Carsten , Piano Riccardo , Cozzini Pietro , Mozzarelli Andrea , Bettati Stefano , Clerici Francesca , Milani Paolo , Lenardi Cristina , Tedeschi Gabriella , Gelmi Maria Luisa
Published: September 2020

The urgent need to develop a detection system for Staphylococcus aureus, one of the most common causes of infection, is prompting research towards novel approaches and devices, with a particular focus on point-of-care analysis. Biosensors are promising systems to achieve this aim. We coupled the selectivity and affinity of aptamers, short nucleic acids sequences able to recognize specific epitopes on bacterial surface, immobilized at high density on a nanostructured zirconium dioxide surface, with the rational design of specifically interacting fluorescent peptides to assemble an easy-to-use detection device. We show that the displacement of fluorescent peptides upon the competitive binding of S. aureus to immobilized aptamers can be detected and quantified through fluorescence loss. This approach could be also applied to the detection of other bacterial species once aptamers interacting with specific antigens will be identified, allowing the development of a platform for easy detection of a pathogen without requiring access to a healthcare environment.
Assessment of Cracking Widths in a Concrete Wall Based on TIR Radiances of Cracking
Authors: Su Tung-Ching
Published: September 2020

The techniques of concrete crack detection, as well as assessments based on thermography coupled with ultrasound, have been presented in many works; however, they have generally needed an additional source of thermal infrared (TIR) radiance and have only been applied in laboratories. Considering the accessibility of thermal infrared cameras, a TIR camera (NEC F30W) was employed to detect cracking in the concrete wall of an historic house with a western architectural style in Kinmen, Taiwan, based on the TIR radiances of cracking. An operation procedure involving a series of image processing and statistical analysis processes was designed to evaluate the performance of the TIR camera in the assessment of the cracking width. This procedure using multiple measurements was implemented from March to August 2019, and the t-tests indicated that the temperature differences between the inside and outline of the concrete cracks remained insignificant as the temperature or relative humidity (RH) in the subtropical climate rose. The experimental results of the operation procedure indicated that the maximum focusing range, which is related to the size of the sensor array, and the minimum detectable crack width of a TIR camera should be 1.0 m and 6.0 mm, respectively, in order to derive a linear regression model with a determination coefficient R2 of 0.733 to estimate the cracking widths, based on the temperature gradients. The validation results showed that there was an approximate R2 value of 0.8 and a total root mean square error of ±2.5 mm between the cracking width estimations and the observations.
ARS: Adaptive Robust Synchronization for Underground Coal Wireless Internet of Things
Authors: Zhang Kuiyuan , Pang Mingzhi , Yin Yuqing , Gao Shouwan , Chen Pengpeng
Published: September 2020

Clock synchronization is still a vital and challenging task for underground coal wireless internet of things (IoT) due to the uncertainty of underground environment and unreliability of communication links. Instead of considering on-demand driven clock synchronization, this paper proposes a novel Adaptive Robust Synchronization (ARS) scheme with packets loss for mine wireless environment. A clock synchronization framework that is based on Kalman filtering is first proposed, which can adaptively adjust the sampling period of each clock and reduce the communication overhead in single-hop networks. The proposed scheme also solves the problem of outliers in data packets with time-stamps. In addition, this paper extends the ARS algorithm to multi-hop networks. Additionally, the upper and lower bounds of error covariance expectation are analyzed in the case of incomplete measurement. Extensive simulations are conducted in order to evaluate the performance. In the simulation environment, the clock accuracy of ARS algorithm is improved by 7.85% when compared with previous studies for single-hop networks. For multi-hop networks, the proposed scheme improves the accuracy by 12.56%. The results show that the proposed algorithm has high scalability, robustness, and accuracy, and can quickly adapt to different clock accuracy requirements.
Spectral Efficiency Augmentation in Uplink Massive MIMO Systems by Increasing Transmit Power and Uniform Linear Array Gain
Authors: Arshad Jehangir , Rehman Abdul , Rehman Ateeq Ur , Ullah Rehmat , Hwang Seong Oun
Published: September 2020

Improved Spectral Efficiency (SE) is a prominent feature of Massive Multiple-Input and Multiple-Output systems. These systems are prepared with antenna clusters at receiver (Rx) and transmitter (Tx). In this paper, we examined a massive MIMO system to increase SE in each cell that ultimately improves the area throughput of the system. We are aiming to find appropriate values of average cell-density (D), available bandwidth (B), and SE to maximize area throughput because it is the function of these parameters. Likewise, a SE augmentation model was developed to attain an increased transmit power and antenna array gain. The proposed model also considers the inter-user interference from neighboring cells along with incident angles of desired and interfering users. Moreover, simulation results validate the proposed model that is implementable in real-time scenarios by realizing maximum SE of 12.79 bits/s/Hz in Line of Sight (LoS) and 12.69 bits/s/Hz in Non-Line of Sight (NLoS) scenarios, respectively. The proposed results also substantiate the SE augmentation because it is a linear function of transmit power and array gain while using the Uniform Linear Array (ULA) configuration. The findings of this work ensure the efficient transmission of information in future networks.
Robust RGB-D SLAM Using Point and Line Features for Low Textured Scene
Authors: Zou Yajing , Eldemiry Amr , Li Yaxin , Chen Wu
Published: September 2020

Three-dimensional (3D) reconstruction using RGB-D camera with simultaneous color image and depth information is attractive as it can significantly reduce the cost of equipment and time for data collection. Point feature is commonly used for aligning two RGB-D frames. Due to lacking reliable point features, RGB-D simultaneous localization and mapping (SLAM) is easy to fail in low textured scenes. To overcome the problem, this paper proposes a robust RGB-D SLAM system fusing both points and lines, because lines can provide robust geometry constraints when points are insufficient. To comprehensively fuse line constraints, we combine 2D and 3D line reprojection error with point reprojection error in a novel cost function. To solve the cost function and filter out wrong feature matches, we build a robust pose solver using the Gauss–Newton method and Chi-Square test. To correct the drift of camera poses, we maintain a sliding-window framework to update the keyframe poses and related features. We evaluate the proposed system on both public datasets and real-world experiments. It is demonstrated that it is comparable to or better than state-of-the-art methods in consideration with both accuracy and robustness.
Direct Georeferencing for the Images in an Airborne LiDAR System by Automatic Boresight Misalignments Calibration
Authors: Ma Haichi , Ma Hongchao , Liu Ke , Luo Wenjun , Zhang Liang
Published: September 2020

Airborne Light Detection and Ranging (LiDAR) system and digital camera are usually integrated on a flight platform to obtain multi-source data. However, the photogrammetric system calibration is often independent of the LiDAR system and performed by the aerial triangulation method, which needs a test field with ground control points. In this paper, we present a method for the direct georeferencing of images collected by a digital camera integrated in an airborne LiDAR system by automatic boresight misalignments calibration with the auxiliary of point cloud. The method firstly uses an image matching to generate a tie point set. Space intersection is then performed to obtain the corresponding object coordinate values of the tie points, while the elevation calculated from the space intersection is replaced by the value from the LiDAR data, resulting in a new object point called Virtual Control Point (VCP). Because boresight misalignments exist, a distance between the tie point and the image point of VCP can be found by collinear equations in that image from which the tie point is selected. An iteration process is performed to minimize the distance with boresight corrections in each epoch, and it stops when the distance is smaller than a predefined threshold or the total number of epochs is reached. Two datasets from real projects were used to validate the proposed method and the experimental results show the effectiveness of the method by being evaluated both quantitatively and visually.
Coherence Time Evaluation in Indoor Optical Wireless Communication Channels
Authors: Bykhovsky Dima
Published: September 2020

The coherence time is the time over which the channel-gain-values correlation coefficient drops below a predefined threshold. The coherence time is typically used to quantify the pace of appreciable channel changes and is important, for example, for determining handoff and resource allocation time constraints. The goal of this work is to experimentally measure the coherence time of indoor optical wireless communication (OWC) channels under various mobile scenarios. The amount of movement was quantified by mobile sensor measurements. The experiments show that it is reasonable to assume that the channel varies slowly for a time period of ~100 milliseconds for most mobile scenarios.
Advances in Optical Biosensors and Sensors Using Nanoporous Anodic Alumina
Authors: Amouzadeh Tabrizi Mahmoud , Ferre-Borrull Josep , Marsal Lluis F.
Published: September 2020

This review paper focuses on recent progress in optical biosensors using self-ordered nanoporous anodic alumina. We present the fabrication of self-ordered nanoporous anodic alumina, surface functionalization, and optical sensor applications. We show that self-ordered nanoporous anodic alumina has good potential for use in the fabrication of antibody-based (immunosensor), aptamer-based (aptasensor), gene-based (genosensor), peptide-based, and enzyme-based optical biosensors. The fabricated optical biosensors presented high sensitivity and selectivity. In addition, we also showed that the performance of the biosensors and the self-ordered nanoporous anodic alumina can be used for assessing biomolecules, heavy ions, and gas molecules.
Feasibility and Reliability of SmartWatch to Obtain 3-Lead Electrocardiogram Recordings
Authors: Behzadi Amirali , Sepehri Shamloo Alireza , Mouratis Konstantinos , Hindricks Gerhard , Arya Arash , Bollmann Andreas
Published: September 2020

Some of the recently released smartwatch products feature a single-lead electrocardiogram (ECG) recording capability. The reliability of obtaining 3-lead ECG with smartwatches is yet to be confirmed in a large study. This study aimed to assess the feasibility and reliability of smartwatch to obtain 3-lead ECG recordings, the classical Einthoven ECG leads I-III compared to standard ECG. To record lead I, the watch was worn on the left wrist and the right index finger was placed on the digital crown for 30 s. For lead II, the watch was placed on the lower abdomen and the right index finger was placed on the digital crown for 30 s. For lead III, the same process was repeated with the left index finger. Spearman correlation and Bland-Altman tests were used for data analysis. A total of 300 smartwatch ECG tracings were successfully obtained. ECG waves’ characteristics of all three leads obtained from the smartwatch had a similar duration, amplitude, and polarity compared to standard ECG. The results of this study suggested that the examined smartwatch (Apple Watch Series 4) could obtain 3-lead ECG tracings, including Einthoven leads I, II, and III by placing the smartwatch on the described positions.
Blockchain for Vehicular Internet of Things: Recent Advances and Open Issues
Authors: Peng Chunrong , Wu Celimuge , Gao Liming , Zhang Jiefang , Alvin Yau Kok-Lim , Ji Yusheng
Published: September 2020

The vehicular Internet of Things (IoT) comprises enabling technologies for a large number of important applications including collaborative autonomous driving and advanced transportation systems. Due to the mobility of vehicles, strict application requirements, and limited communication resources, the conventional centralized control fails to provide sufficient quality of service for connected vehicles, so a decentralized approach is required in the vicinity to satisfy the requirements of delay-sensitive and mission-critical applications. A decentralized system is also more resistant to the single point of failure problem and malicious attacks. Blockchain technology has been attracting great interest due to its capability of achieving a decentralized, transparent, and tamper-resistant system. There are many studies focusing on the use of blockchain in managing data and transactions in vehicular environments. However, the application of blockchain in vehicular environments also faces some technical challenges. In this paper, we first explain the fundamentals of blockchain and vehicular IoT. Then, we conduct a literature review on the existing research efforts of the blockchain for vehicular IoT by discussing the research problems and technical issues. After that, we point out some future research issues considering the characteristics of both blockchain and vehicular IoT.
Convolutional Neural Networks-Based Object Detection Algorithm by Jointing Semantic Segmentation for Images
Authors: Qiang Baohua , Chen Ruidong , Zhou Mingliang , Pang Yuanchao , Zhai Yijie , Yang Minghao
Published: September 2020

In recent years, increasing image data comes from various sensors, and object detection plays a vital role in image understanding. For object detection in complex scenes, more detailed information in the image should be obtained to improve the accuracy of detection task. In this paper, we propose an object detection algorithm by jointing semantic segmentation (SSOD) for images. First, we construct a feature extraction network that integrates the hourglass structure network with the attention mechanism layer to extract and fuse multi-scale features to generate high-level features with rich semantic information. Second, the semantic segmentation task is used as an auxiliary task to allow the algorithm to perform multi-task learning. Finally, multi-scale features are used to predict the location and category of the object. The experimental results show that our algorithm substantially enhances object detection performance and consistently outperforms other three comparison algorithms, and the detection speed can reach real-time, which can be used for real-time detection.
LRF-Net: Learning Local Reference Frames for 3D Local Shape Description and Matching
Authors: Zhu Angfan , Yang Jiaqi , Zhao Weiyue , Cao Zhiguo
Published: September 2020

The local reference frame (LRF) acts as a critical role in 3D local shape description and matching. However, most existing LRFs are hand-crafted and suffer from limited repeatability and robustness. This paper presents the first attempt to learn an LRF via a Siamese network that needs weak supervision only. In particular, we argue that each neighboring point in the local surface gives a unique contribution to LRF construction and measure such contributions via learned weights. Extensive analysis and comparative experiments on three public datasets addressing different application scenarios have demonstrated that LRF-Net is more repeatable and robust than several state-of-the-art LRF methods (LRF-Net is only trained on one dataset). We show that LRFNet achieves 0.686 MeanCos performance on the UWA 3D modeling (UWA3M) dataset, outperforming the closest method by 0.18. In addition, LRF-Net can significantly boost the local shape description and 6-DoF pose estimation performance when matching 3D point clouds.
Dynamic Displacement Estimation for Long-Span Bridges Using Acceleration and Heuristically Enhanced Displacement Measurements of Real-Time Kinematic Global Navigation System
Authors: Kim Kiyoung , Sohn Hoon
Published: September 2020

In this paper, we propose a dynamic displacement estimation method for large-scale civil infrastructures based on a two-stage Kalman filter and modified heuristic drift reduction method. When measuring displacement at large-scale infrastructures, a non-contact displacement sensor is placed on a limited number of spots such as foundations of the structures, and the sensor must have a very long measurement distance (typically longer than 100 m). RTK-GNSS, therefore, has been widely used in displacement measurement on civil infrastructures. However, RTK-GNSS has a low sampling frequency of 10–20 Hz and often suffers from its low stability due to the number of satellites and the surrounding environment. The proposed method combines data from an RTK-GNSS receiver and an accelerometer to estimate the dynamic displacement of the structure with higher precision and accuracy than those of RTK-GNSS and 100 Hz sampling frequency. In the proposed method, a heuristic drift reduction method estimates displacement with better accuracy employing a low-pass-filtered acceleration measurement by an accelerometer and a displacement measurement by an RTK-GNSS receiver. Then, the displacement estimated by the heuristic drift reduction method, the velocity measured by a single GNSS receiver, and the acceleration measured by the accelerometer are combined in a two-stage Kalman filter to estimate the dynamic displacement. The effectiveness of the proposed dynamic displacement estimation method was validated through three field application tests at Yeongjong Grand Bridge in Korea, San Francisco–Oakland Bay Bridge in California, and Qingfeng Bridge in China. In the field tests, the root-mean-square error of RTK-GNSS displacement measurement reduces by 55–78 percent after applying the proposed method.
Distributed Node Scheduling with Adjustable Weight Factor for Ad-hoc Networks
Authors: Lee Wonseok , Kim Taehong , Kim Taejoon
Published: September 2020

In this paper, a novel distributed scheduling scheme for an ad-hoc network is proposed. Specifically, the throughput and the delay of packets with different importance are flexibly adjusted by quantifying the importance as weight factors. In this scheme, each node is equipped with two queues, one for packets with high importance and the other for packets with low importance. The proposed scheduling scheme consists of two procedures: intra-node slot reallocation and inter-node reallocation. In the intra-node slot reallocation, self-fairness is adopted as a key metric, which is a composite of the quantified weight factors and traffic loads. This intra-node slot reallocation improves the throughput and the delay performance. Subsequently, through an inter-node reallocation algorithm adopted from LocalVoting (slot exchange among queues having the same importance), the fairness of traffics with the same importance is enhanced. Thorough simulations were conducted under various traffic load and weight factor settings. The simulation results show that the proposed algorithm can adjust packet delivery performance according to a predefined weight factor. Moreover, compared with conventional algorithms, the proposed algorithm achieves better performance in throughput and delay. The low average delay while attaining the high throughput ensures the excellent performance of the proposed algorithm.
Insulator Based Dielectrophoresis: Micro, Nano, and Molecular Scale Biological Applications
Authors: Benhal Prateek , Quashie David , Kim Yoontae , Ali Jamel
Published: September 2020

Insulator based dielectrophoresis (iDEP) is becoming increasingly important in emerging biomolecular applications, including particle purification, fractionation, and separation. Compared to conventional electrode-based dielectrophoresis (eDEP) techniques, iDEP has been demonstrated to have a higher degree of selectivity of biological samples while also being less biologically intrusive. Over the past two decades, substantial technological advances have been made, enabling iDEP to be applied from micro, to nano and molecular scales. Soft particles, including cell organelles, viruses, proteins, and nucleic acids, have been manipulated using iDEP, enabling the exploration of subnanometer biological interactions. Recent investigations using this technique have demonstrated a wide range of applications, including biomarker screening, protein folding analysis, and molecular sensing. Here, we review current state-of-art research on iDEP systems and highlight potential future work.
Synthesis, Antimicrobial Study, and Molecular Docking Simulation of 3,4-Dimethoxy-β-Nitrostyrene Derivatives as Candidate PTP1B Inhibitor
Authors: Alfarisi Salman , Santoso Mardi , Kristanti Alfinda Novi , Siswanto Imam , Puspaningsih Ni Nyoman Tri
Published: September 2020

A derivative series of 3,4-dimethoxy-β-nitrostyrene was synthesized through nitroaldol reaction, including a new compound of 3,4-ethylenedioxy-β-bromo-β-nitrostyrene. The antimicrobial activity effect of 3,4-alkyloxy modification of β-nitrostyrene was investigated. A molecular docking study was also performed to obtain information about their interactions with protein tyrosine phosphatase 1B (PTP1B). The active residues of cysteine-215 and arginine-221 of PTP1B play a key role in signaling pathways that regulate various microorganism cell functions. It also acts as a negative regulator in signaling pathways of insulin that are involved in type 2 diabetes and other metabolic diseases. These derivatives exhibited potential antifungal activity. The studied compounds were also had potential as fragments to be PTP1B inhibitors by interacting with serine-216 and arginine-221 residues, according to their molecular docking. 3,4-Ethylenedioxy-β-methyl-β-nitrostyrene was the most successful potential candidate as a PTP1B inhibitor. However, further research is needed to investigate their potential for medicinal use.
A Simple Time-Varying Sensitivity Analysis (TVSA) for Assessment of Temporal Variability of Hydrological Processes
Authors: Medina Yelena , Muñoz Enrique
Published: September 2020

Time-varying sensitivity analysis (TVSA) allows sensitivity in a moving window to be estimated and the time periods in which the specific components of a model can affect its performance to be identified. However, one of the disadvantages of TVSA is its high computational cost, as it estimates sensitivity in a moving window within an analyzed series, performing a series of repetitive calculations. In this article a function to implement a simple TVSA with a low computational cost using regional sensitivity analysis is presented. As an example of its application, an analysis of hydrological model results in daily, monthly, and annual time windows is carried out. The results show that the model allows the time sensitivity of a model with respect to its parameters to be detected, making it a suitable tool for the assessment of temporal variability of processes in models that include time series analysis. In addition, it is observed that the size of the moving window can influence the estimated sensitivity; therefore, analysis of different time windows is recommended.
Exploring How Cyanobacterial Traits Affect Nutrient Loading Thresholds in Shallow Lakes: A Modelling Approach
Authors: Chang Manqi , Teurlincx Sven , Janse Jan , Paerl Hans , Mooij Wolf , Janssen Annette
Published: September 2020

Globally, many shallow lakes have shifted from a clear macrophyte-dominated state to a turbid phytoplankton-dominated state due to eutrophication. Such shifts are often accompanied by toxic cyanobacterial blooms, with specialized traits including buoyancy regulation and nitrogen fixation. Previous work has focused on how these traits contribute to cyanobacterial competitiveness. Yet, little is known on how these traits affect the value of nutrient loading thresholds of shallow lakes. These thresholds are defined as the nutrient loading at which lakes shift water quality state. Here, we used a modelling approach to estimate the effects of traits on nutrient loading thresholds. We incorporated cyanobacterial traits in the process-based ecosystem model PCLake+, known for its ability to determine nutrient loading thresholds. Four scenarios were simulated, including cyanobacteria without traits, with buoyancy regulation, with nitrogen fixation, and with both traits. Nutrient loading thresholds were obtained under N-limited, P-limited, and colimited conditions. Results show that cyanobacterial traits can impede lake restoration actions aimed at removing cyanobacterial blooms via nutrient loading reduction. However, these traits hardly affect the nutrient loading thresholds for clear lakes experiencing eutrophication. Our results provide references for nutrient loading thresholds and draw attention to cyanobacterial traits during the remediation of eutrophic water bodies.
RELIGIOUS (“FAITH-BASED”) EDUCATION IN PROTESTANT EDUCATIONAL INSTITUTIONS OF UKRAINE: TO THE PROBLEM OF CONCEPT FORMULATION
Authors: Kunderenko Ivan
Published: September 2020

The author analyses the three most common ways to address the institutions of higher education established by religious organizations.
GP perceptions of community-based children’s mental health services in Pennine Lancashire: a qualitative study
Authors: Lambert Alice Kate , Doherty Alison Jayne , Wilson Neil , Chauhan Umesh , Mahadevan Dushyanthan
Published: September 2020

Background

GP satisfaction with specialist Child & Adolescent Mental Health Services (CAMHS) is often reported as low in the UK, and internationally.

Aim

To explore GP perceptions of local children’s mental health services and to understand their experiences of a novel GP-attached Primary Mental Health Worker (PMHW) service.

Design & setting

Qualitative research involving GPs in Pennine Lancashire.

Method

Semi-structured face-to-face interviews of GPs (n = 9) were carried out. Thematic analysis was undertaken.

Results

Themes identified included: 1) The role of the GP: most GPs perceived their role to be signposting and referring patients with mental health issues to specialist services, rather than offering care directly; 2) Clarity on help available: GPs were unclear about specialist CAMHS referral criteria and alternative resources available. GPs experienced communication challenges with specialist CAMHS; 3) Getting advice and support: PMHWs enabled GPs to have informal discussions, and to seek advice about children. Some GPs felt they could recognise problems earlier and were able to access help more quickly; and 4) Development needs: some GPs felt they required increased training in supporting children with mental health problems, and identified a need for further collaboration with schools and specialist CAMHS.

Conclusion

The study identified challenges that GPs face with accessing and utilising specialist CAMHS. GPs who had PMHWs based in their practices expressed increased satisfaction with these services. GP-attached PMHWs can potentially reduce the challenges faced by GPs in primary care by offering timely and accessible advice, and improving access to specialist CAMHS.
Sermayenin Tüketiş Kurgusu: Bereketli Topraklar Üzerinde
Authors: ELIUZ Ülkü , ARMAĞAN Burak
Published: September 2020

Sanayi devrimleri ile başlayan süreçte, endüstriyel çalışmalarda teknik icatların ve seri üretim modellerinin kullanımının yaygınlaşması, evrensel ölçekte iki zıt kutbun görülmesini sağlar: maddi gücün ilahlaştırıldığı yeni bir toplumsal düzeni inşa eden kapitalistler/sermayedarlar ve onların kurguladığı tüketimi öğütleyen senaryoya tükeniş kanalından eklemlenen işçiler/emekçiler.Kapitalizmin/sermayenin tüketim üzerine kurguladığı yeni yaşam düzenine edebî sahadaki tepki, toplumcu gerçekçi kuram/ akım doğrultusunda yazılan eserler tarafından gösterilir. Bu tepkinin Türk edebiyatındaki sözcülüğünü üstlenen yazarlardan olan Orhan Kemal, Bereketli Topraklar Üzerinde romanı ile farklı sektörlerdeki işçilerin, iş ahlakının, işçileşme süreçlerinin ve işleyişin görüntü düzeylerini aktarırken Türkiye’nin sanayileşme döneminde sosyal hayatta yaşanan sancılara da dikkat çeker. Yozlaşma teması üzerine kurgulanan eserde, üç karakterin fiziksel ve ruhsal bakımdan var oluş-yok oluş düzlemindeki serüvenleri trajik boyutları ile ele alınır.Bu makalede Bereketli Topraklar Üzerinde romanından hareketle sermayenin tüketiş kurgusunun maddi ve manevi alanlarda yarattığı tahribatlar, sebep-sonuç çerçevesinde incelenecektir.
Orhan Kemal Romancılığının Nitelikleri Yenilikleri
Authors: NARLI Mehmet
Published: September 2020

Orhan Kemal, çok genel manada, en azından vakayı diyaloglarla takdim etme ve şiveleri kullanma açısından Hüseyin Rahmi Gürpınar’a kadar uzanan natüralist ve realist roman anlayışını, Sadri Ertem, Sabahattin Ali gibi romancılar kanalından devralan "sosyal gerçekçi" bir romancıdır. Türk romanında "Anadolu’ya yöneliş" şeklinde kendini gösteren içerik genişlemesi, Orhan Kemal’de, küçük, haylaz ve yoksul gençlerin yaşayışları; sınıf değiştirmek veya ekmeğini kazanmak için mücadele eden işçi, küçük esnaf mücadeleleri; yeni gelişen sanayileşmeyi ağalık ve patronluk arası bir tutumla yansıtan fabrika sahiplerinin hayatları; köylülükten şehir işçiliğine doğru kaymaya çalışan insanların yaşadıkları değişimler olarak görünür. Orhan Kemal, bu malzemeye yaklaşırken "diyalektik materyalizm"in bakış açısına bağlıdır. Yani sosyal çatışmaları "sınıfsal bir bakış"la görür. Fakat bu malzemeyi işleyişi, kendi çağdaşları olan bazı yazarların (mesela köy romancılarının) uyguladığı "toplumcu gerçekçilik" anlayışından farklıdır. Diyebiliriz ki o, sosyal hayata bakarken ve malzemesini seçerken "toplumcu gerçekçi"; bu malzemeyi yansıtırken "gözlemci ve eleştirel gerçekçi"dir. Bu tavrın Orhan Kemal tarafından "Aydınlık gerçekçilik" olarak adlandırıldığını söyleyebiliriz.
APRENDIZAGEM MOTORA PELA FILOSOFIA (S) DA (S) DIFERENÇA (S): POSSIBILIDADES E DESLOCAMENTOS
Authors: Lopes Paulo Henrique Oliveira
Published: September 2020

O presente trabalho busca aproximar a literatura da (s) filosofia (s) da (s) diferença (s) às discussões sobre aprendizagem motora. Tenho como método de pesquisa a proposta de “método como acontecimento” desenvolvida por Ribeiro (2016), na qual a autora considera importante a experiência do pensamento para além dos confrontos epistemológicos e aquém das dimensões ético-políticas. A pesquisa baseia-se em leituras de estudiosos do comportamento motor como: Go Tani e Richard A. Magill; e os filósofos/psicólogos (as) Gilles Deleuze, Henri Bergson, Silvio Gallo e Virginia Kastrup. Relata-se ao final desta pesquisa a possibilidade de pensar a invenção no relacionamento sensório-motor; reivindicando uma dimensão analítica dos afectos neste intermeio.
EMPODERAMENTO DA MULHER-DAMA? CORPOS DESEJANTES NA DANÇA DE SALÃO
Authors: Polezi Carolina , Pacheco Debora Reis
Published: September 2020

Este trabalho parte dos discursos de verdades produzidos na dança de salão sobre a mulher que assume o papel de dama problematizando as tentativas de escapes na contemporaneidade. No âmbito da dança de salão os papéis de homens e mulheres são claramente divididos a partir de uma perspectiva heteronormativa. Deste modo debate-se a ideia de mulher-dama carregada de elementos que definem um modo de ser na sociedade e na dança, bem como os movimentos que tentam desconstruir esses olhares a partir do empoderamento feminino, mas que são capturados pela máquina social mantendo os mesmos lugares de homens e mulheres, só que através de outra roupagem. Inicialmente apresenta-se uma breve contextualização da Dança de Salão. Posteriormente, a partir de um levantamento em livros e texto que circulam em sites, blogs e redes sociais visitados por dançarinos, apresenta-se uma análise principalmente sobre a perspectiva Deleuze Guattariana.
DESDOBRAMENTOS, RESSONÂNCIAS, CONTÁGIOS... AS PRODUÇÕES DAS CRIANÇAS SOBRE O PAPEL E SEUS CORTES-FLUXOS DESEJANTES E FABULADORES
Authors: Vazzoler Camilla Borini
Published: September 2020

O que enuncia uma criança quando desenha? É de comum acordo que os desenhos das crianças fazem parte da rotina dos centros de educação infantil, e, pensando na potência desses registros, buscou-se problematizar a força dos desenhos das crianças por meio de uma aula-acontecimento com um personagem do folclore brasileiro. Desse modo, visou-se movimentar o pensamento em movimento com as fabulações criadas pelas crianças nos seus processos de criação desejante e imanente. Ao usarem lápis colorido e papel, produzem e criam mundos, fabulam outros modos de pensar, criam cortes-fluxos, pois algo passou pelo seu corpo, e, ao criarem, a virtualidade atualizou-se em traços intensivos impressos em um papel. A potência deste texto está nos desenhos das crianças e na maneira como as professoras se afetam com as forças que elas produzem, ao pintarem o mundo, criando desdobramentos, ressonâncias e contágios...
CONEXÕES NO CINEMA DE APICHATPONG WEERASETHAKUL: POÉTICAS E LINGUAGENS E...
Authors: Vicentin Pedro Santos Paviotti , Vicentin Marcelo , Sebastião Wagner Gomes
Published: September 2020

Este artigo se propõe a apresentar os movimentos fronteiriços do cinema de Apichatpong Weerasethakul, movimentos de devires, conexões e alianças por uma imanência antropofágica. Para tanto, nos pautamos pelo encontro do pensamento de Gilles Deleuze e Félix Guattari, e Oswald de Andrade, e os filmes do diretor na emergência de hibridismos e devires que territorializam cartografias outras, singularidades e individuações arbitrárias humanas e não humanas; a potência de uma cinematografia por seus desdobramentos, ressonâncias e contágios...