bluuebunny/crossref_metadata_2025 huggingface dataset:
Validation of 7 Years in-Flight HY-2A Calibration Microwave Radiometer Products Using Numerical Weather Model and Radiosondes
Authors: Wu Zhilu , Wang Jungang , Liu Yanxiong , He Xiufeng , Liu Yang , Xu Wenxue
Published: July 2019

Haiyang-2A (HY-2A) has been working in-flight for over seven years, and the accuracy of HY-2A calibration microwave radiometer (CMR) data is extremely important for the wet troposphere delay correction (WTC) in sea surface height (SSH) determination. We present a comprehensive evaluation of the HY-2A CMR observation using the numerical weather model (NWM) for all the data available period from October 2011 to February 2018, including the WTC and the precipitable water vapor (PWV). The ERA(ECMWF Re-Analysis)-Interim products from European Centre for Medium-Range Weather Forecasts (ECMWF) are used for the validation of HY-2A WTC and PWV products. In general, a global agreement of root-mean-square (RMS) of 2.3 cm in WTC and 3.6 mm in PWV are demonstrated between HY-2A observation and ERA-Interim products. Systematic biases are revealed where before 2014 there was a positive WTC/PWV bias and after that, a negative one. Spatially, HY-2A CMR products show a larger bias in polar regions compared with mid-latitude regions and tropical regions and agree better in the Antarctic than in the Arctic with NWM. Moreover, HY-2A CMR products have larger biases in the coastal area, which are all caused by the brightness temperature (TB) contamination from land or sea ice. Temporally, the WTC/PWV biases increase from October 2011 to March 2014 with a systematic bias over 1 cm in WTC and 2 mm in PWV, and the maximum RMS values of 4.62 cm in WTC and 7.61 mm in PWV occur in August 2013, which is because of the unsuitable retrieval coefficients and systematic TB measurements biases from 37 GHz band. After April 2014, the TB bias is corrected, HY-2A CMR products agree very well with NWM from April 2014 to May 2017 with the average RMS of 1.68 cm in WTC and 2.65 mm in PWV. However, since June 2017, TB measurements from the 18.7 GHz band become unstable, which led to the huge differences between HY-2A CMR products and the NWM with an average RMS of 2.62 cm in WTC and 4.33 mm in PWV. HY-2A CMR shows high accuracy when three bands work normally and further calibration for HY-2A CMR is in urgent need. Furtherly, 137 global coastal radiosonde stations were used to validate HY-2A CMR. The validation based on radiosonde data shows the same variation trend in time of HY-2A CMR compared to the results from ECMWF, which verifies the results from ECMWF.
A Lightweight Hyperspectral Image Anomaly Detector for Real-Time Mission
Authors: Ma Ning , Yu Ximing , Peng Yu , Wang Shaojun
Published: July 2019

In real-time onboard hyperspectral-image(HSI) anomalous targets detection, processing speed and accuracy are equivalently desirable which is hard to satisfy at the same time. To improve detection accuracy, deep learning based HSI anomaly detectors (ADs) are widely studied. However, their large scale network results in a massive computational burden. In this paper, to improve the detection throughput without sacrificing the accuracy, a pruning–quantization–anomaly–detector (P-Q-AD) is proposed by building an underlying constraint formulation to make a trade-off between accuracy and throughput. To solve this formulation, multi-objective optimization with nondominated sorting genetic algorithm II (NSGA-II) is employed to shrink the network. As a result, the redundant neurons are removed. A mixed precision network is implemented with a delicate customized fixed-point data expression to further improve the efficiency. In the experiments, the proposed P-Q-AD is implemented on two real HSI data sets and compared with three types of detectors. The results show that the performance of the proposed approach is no worse than those comparison detectors in terms of the receiver operating characteristic curve (ROC) and area under curve (AUC) value. For the onboard mission, the proposed P-Q-AD reaches over 4.5 × speedup with less than 0.5 % AUC loss compared with the floating-based detector. The pruning and the quantization approach in this paper can be referenced for designing the anomalous targets detectors for high efficiency.
A Remote Control Strategy for an Autonomous Vehicle with Slow Sensor Using Kalman Filtering and Dual-Rate Control
Authors: Cuenca Ángel , Zhan Wei , Salt Julián , Alcaina José , Tang Chen , Tomizuka Masayoshi
Published: July 2019

This work presents a novel remote control solution for an Autonomous Vehicle (AV), where the system structure is split into two sides. Both sides are assumed to be synchronized and linked through a communication network, which introduces time-varying delays and packet disorder. An Extended Kalman Filter (EKF) is used to cope with the non-linearities that appear in the global model of the AV. The EKF fuses the data provided by the sensing devices of the AV in order to estimate the AV state, reducing the noise effect. Additionally, the EKF includes an h-step-ahead state prediction stage, which, together with the consideration of a packet-based control strategy, enables facing the network-induced delays. Since the AV position is provided by a camera, which is a slow sensing device, a dual-rate controller is required to achieve certain desired (nominal) dynamic control performance. The use of a dual-rate control framework additionally enables saving network bandwidth and deals with packet disorder. As the path-tracking control algorithm, pure pursuit is used. Application results show that, despite existing communication problems and slow-rate measurements, the AV is able to track the desired path, keeping the nominal control performance.
Deep Learning Convolutional Neural Network for the Retrieval of Land Surface Temperature from AMSR2 Data in China
Authors: Tan Jiancan , NourEldeen Nusseiba , Mao Kebiao , Shi Jiancheng , Li Zhaoliang , Xu Tongren , Yuan Zijin
Published: July 2019

A convolutional neural network (CNN) algorithm was developed to retrieve the land surface temperature (LST) from Advanced Microwave Scanning Radiometer 2 (AMSR2) data in China. Reference data were selected using the Moderate Resolution Imaging Spectroradiometer (MODIS) LST product to overcome the problem related to the need for synchronous ground observation data. The AMSR2 brightness temperature (TB) data and MODIS surface temperature data were randomly divided into training and test datasets, and a CNN was constructed to simulate passive microwave radiation transmission to invert the surface temperature. The twelve V/H channel combinations (7.3, 10.65, 18.7, 23.8, 36.5, 89 GHz) resulted in the most stable and accurate CNN retrieval model. Vertical polarizations performed better than horizontal polarizations; however, because CNNs rely heavily on large amounts of data, the combination of vertical and horizontal polarizations performed better than a single polarization. The retrievals in different regions indicated that the CNN accuracy was highest over large bare land areas. A comparison of the retrieval results with ground measurement data from meteorological stations yielded R2 = 0.987, RMSE = 2.69 K, and an average relative error of 2.57 K, which indicated that the accuracy of the CNN LST retrieval algorithm was high and the retrieval results can be applied to long-term LST sequence analysis in China.
Non-Target Structural Displacement Measurement Using Reference Frame-Based Deepflow
Authors: Won Jongbin , Park Jong-Woong , Park Kyoohong , Yoon Hyungchul , Moon Do-Soo
Published: July 2019

Displacement is crucial for structural health monitoring, although it is very challenging to measure under field conditions. Most existing displacement measurement methods are costly, labor-intensive, and insufficiently accurate for measuring small dynamic displacements. Computer vision (CV)-based methods incorporate optical devices with advanced image processing algorithms to accurately, cost-effectively, and remotely measure structural displacement with easy installation. However, non-target-based CV methods are still limited by insufficient feature points, incorrect feature point detection, occlusion, and drift induced by tracking error accumulation. This paper presents a reference frame-based Deepflow algorithm integrated with masking and signal filtering for non-target-based displacement measurements. The proposed method allows the user to select points of interest for images with a low gradient for displacement tracking and directly calculate displacement without drift accumulated by measurement error. The proposed method is experimentally validated on a cantilevered beam under ambient and occluded test conditions. The accuracy of the proposed method is compared with that of a reference laser displacement sensor for validation. The significant advantage of the proposed method is its flexibility in extracting structural displacement in any region on structures that do not have distinct natural features.
Conductometric Sensing with Individual InAs Nanowires
Authors: Demontis Valeria , Rocci Mirko , Donarelli Maurizio , Maiti Rishi , Zannier Valentina , Beltram Fabio , Sorba Lucia , Roddaro Stefano , Rossella Francesco , Baratto Camilla
Published: July 2019

In this work, we isolate individual wurtzite InAs nanowires and fabricate electrical contacts at both ends, exploiting the single nanostructures as building blocks to realize two different architectures of conductometric sensors: (a) the nanowire is drop-casted onto—supported by—a SiO2/Si substrate, and (b) the nanowire is suspended at approximately 250 nm from the substrate. We test the source-drain current upon changes in the concentration of humidity, ethanol, and NO2, using synthetic air as a gas carrier, moving a step forward towards mimicking operational environmental conditions. The supported architecture shows higher response in the mid humidity range (50% relative humidity), with shorter response and recovery times and lower detection limit with respect to the suspended nanowire. These experimental pieces of evidence indicate a minor role of the InAs/SiO2 contact area; hence, there is no need for suspended nanostructures to improve the sensing performance. Moreover, the sensing capability of single InAs nanowires for detection of NO2 and ethanol in the ambient atmosphere is reported and discussed.
A CSI-Based Indoor Fingerprinting Localization with Model Integration Approach
Authors: Yin Yuqing , Song Changze , Li Ming , Niu Qiang
Published: July 2019

Convenient indoor positioning has become an urgent need due to the improvement it offers to quality of life, which inspires researchers to focus on device-free indoor location. In areas covered with Wi-Fi, people in different locations will to varying degrees have an impact on the transmission of channel state information (CSI) of Wi-Fi signals. Because space is divided into several small regions, the idea of classification is used to locate. Therefore, a novel localization algorithm is put forward in this paper based on Deep Neural Networks (DNN) and a multi-model integration strategy. The approach consists of three stages. First, the local outlier factor (LOF), the anomaly detection algorithm, is used to correct the abnormal data. Second, in the training phase, 3 DNN models are trained to classify the region fingerprints by taking advantage of the processed CSI data from 3 antennas. Third, in the testing phase, a model fusion method named group method of data handling (GMDH) is adopted to integrate 3 predicted results of multiple models and give the final position result. The test-bed experiment was conducted in an empty corridor, and final positioning accuracy reached at least 97%.
Extraction Method of Crack Signal for Inspection of Complicated Steel Structures Using A Dual-Channel Magnetic Sensor
Authors: Hayashi Minoru , Saito Taisuke , Nakamura Yoshihiro , Sakai Kenji , Kiwa Toshihiko , Tanikura Izumi , Tsukada Keiji
Published: July 2019

Conventional eddy current testing (ECT) using a pickup coil probe is widely employed for the detection of structural cracks. However, the inspection of conventional ECT for steel structures is difficult because of the magnetic noise caused by the nonuniform permeability of steel. To combat this challenge, we have developed a small magnetic sensor probe with a dual-channel tunneling magnetoresistance sensor that is capable of reducing magnetic noise. Applying this probe to a complicated component of steel structures—such as the welds joining a U-shaped rib and deck plate together—requires the reduction of signal fluctuation caused by the distance (liftoff) variations between the sensor probe and the subject. In this study, the fundamental crack signal and the liftoff signal were investigated with the dual-channel sensor. The results showed that the liftoff signals could be reduced and differentiated from the crack signals by the differential parameters of the dual-channel sensor. In addition, we proposed an extraction technique for the crack signal using the Lissajous curve of the differential parameters. The extraction technique could be applied to the inspections not only for flat plates but also for welded angles to detect cracks without the influence of the liftoff signal.
CA-CWA: Channel-Aware Contention Window Adaption in IEEE 802.11ah for Soft Real-Time Industrial Applications
Authors: Cheng Yujun , Zhou Huachun , Yang Dong
Published: July 2019

In 2016, the IEEE task group ah (TGah) released a new standard called IEEE 802.11ah, and industrial Internet of Things (IoT) is one of its typical use cases. The restricted access window (RAW) is one of the core MAC mechanisms of IEEE 802.11ah, which aims to address the collision problem in the dense wireless networks. However, in each RAW period, stations still need to contend for the channel by Distributed Coordination Function and Enhanced Distributed Channel Access (DCF/EDCA), which cannot meet the real-time requirements of most industrial applications. In this paper, we propose a channel-aware contention window adaption (CA-CWA) algorithm. The algorithm dynamically adapts the contention window based on the channel status with an external interference discrimination ability, and improves the real-time performance of the IEEE 802.11ah. To validate the real-time performance of CA-CWA, we compared CA-CWA with two other backoff algorithms with an NS-3 simulator. The results illustrate that CA-CWA has better performance than the other two algorithms in terms of packet loss rate and average delay. Compared with the other two algorithms, CA-CWA is able to support industrial applications with higher deadline constraints under the same channel conditions in IEEE 802.11ah.
Monitoring Surface Defects Deformations and Displacements in Hot Steel Using Magnetic Induction Tomography
Authors: Li Fang , Spagnul Stefano , Odedo Victor , Soleimani Manuchehr
Published: July 2019

Magnetic Induction Tomography (MIT) is a non-invasive imaging technique that has been widely applied for imaging materials with high electrical conductivity contrasts. Steel production is among an increasing number of applications that require a contactless method for monitoring the casting process due to the high temperature of hot steel. In this paper, an MIT technique is proposed for detecting defects and deformations in the external surfaces of metal, which has the potential to be used to monitor the external surface of hot steel during the continuous casting process. The Total Variation (TV) reconstruction algorithm was developed to image the conductivity distributions. Nonetheless, the reconstructed image of the deformed square metal obtained using the TV algorithm directly does not yield resonable images of the surface deformation. However, differential images obtained by subtracting the image of a perfect square metal with no deformations from the image obtained for a deformed square metal does provide accurate and repeatable deformation information. It is possible to obtain a more precise image of surface deformation by thresholding the differential image. This TV-based threshold-differencing method has been analysed and verified from both simulation and experimental tests. The simulation results reported that 0.92 % of the image region can be detected, and the experimental results indicated a 0.57 % detectability. Use of the proposed method was demonstareted in a MIT device which was used in continuous casting set up. The paper shows results from computer simulation, lab based cold tests, and real life data from continoeus cating demonstating the effectiveness of the proposed method.
Ternary Gas Mixture Quantification Using Field Asymmetric Ion Mobility Spectrometry (FAIMS)
Authors: Yokoshiki Yasufumi , Nakamoto Takamichi
Published: July 2019

Gas mixture quantification is essential for the recording and reproducing odors, because an odor consists of multiple chemical compounds. Gas mixture quantification using field asymmetric ion mobility spectrometry (FAIMS) was studied. Acetone, ethanol, and diethyl ether were selected as components of a ternary gas mixture sample as representatives of the ketone, alcohol, and ether chemical classes, respectively. One hundred and twenty-five points with different concentrations were measured. The results were evaluated by error hypersurface, variance, and the coefficient of variation. The error hypersurface showed that it is possible to reach the target composition by following the error-hypersurface gradient. Successful convergence was achieved with the gradient descent method in a simulation based on the measurement data. This result verified the feasibility of the quantification of a gas mixture using FAIMS.
E-Knitted Textile with Polymer Optical Fibers for Friction and Pressure Monitoring in Socks
Authors: Guignier Claire , Camillieri Brigitte , Schmid Michel , Rossi René , Bueno Marie-Ange
Published: July 2019

The objective of this paper is to study the ability of polymer optical fiber (POF) to be inserted in a knitted fabric and to measure both pressure and friction when walking. Firstly, POF, marketed and in development, have been compared in terms of the required mechanical properties for the insertion of the fiber directly into a knitted fabric on an industrial scale, i.e. elongation, bending rigidity, and minimum bending radius before plastic deformation. Secondly, the chosen optical fiber was inserted inside several types of knitted fabric and was shown to be sensitive to friction and compression. The knitted structure with the highest sensitivity has been chosen for sock prototype manufacturing. Finally, a feasibility study with an instrumented sock showed that it is possible to detect the different phases of walking in terms of compression and friction.
Optimal Share of Natural Gas in the Electric Power Generation of South Korea: A Note
Authors: Kim Gyeong-Sam , Kim Hyo-Jin , Yoo Seung-Hoon
Published: July 2019

Natural gas (NG) not only emits fewer greenhouse gases and air pollutants than coal but also plays the role of a peak power source that can respond immediately to the variability of increasing renewables. Although the share of NG generation worldwide is increasing, it is difficult for South Korea to increase its NG generation significantly in terms of fuel supply security, since it depends on imports for all of the NG used for power generation. Therefore, the optimal share of NG generation in electric power generation is a serious concern. This note attempts to estimate the optimal share by modelling the plausible relationship between NG generation and national output in the Cobb–Douglas production function setting and then deriving the output-maximizing share of NG generation. The production function is statistically significantly estimated using annual data from 1990 to 2016, allowing for the first-order serial correlation. The optimal share is computed to be 20.3%. Therefore, it is recommended that South Korea increases the share of NG generation slightly and makes efforts to secure a stable NG supply, given that, according to the national plan, the share will be 18.8% in 2030.
Urban Green Spaces and Housing Prices: An Alternative Perspective
Authors: Liebelt Veronika , Bartke Stephan , Schwarz Nina
Published: July 2019

Urban green spaces (UGS) are essential components of sustainable cities that provide many benefits to urban residents, such as recreation or aesthetics. Urban residents may be willing to pay for some of these ecosystem services. Indeed, studies investigating the formation of housing prices through hedonic pricing analysis have shown that UGS can influence housing prices. Hedonic pricing analysis puts housing units at the center of analysis. In this study, we investigate whether an alternative perspective provides additional insights into the effects of UGS on pricing. The proposed approach puts UGS into the center of analysis by applying an analysis of buffer zones to housing prices, thus, linking approaches from urban economics and landscape ecology. Such an analysis could deepen our understanding of the effects of UGS on housing prices by analyzing price–distance slopes around UGS-thus supporting more informed decisions on efficient UGS management and urban planning. Our results using a case study on Leipzig, Germany, demonstrate that the size of UGS affects price–distance slopes around them. We conclude that further investigations should be fathomed to unleash the potential of applying the analysis of buffer zones around UGS as a method to inform sustainable UGS design in cities.
Determinants and Mechanisms of Tourists’ Environmentally Responsible Behavior: Applying and Extending the Value-Identity-Personal Norm Model in China
Authors: Xu Yongxun , Wei Xuechao , Chen Shih-Chih
Published: July 2019

It is well recognized that tourists’ environmentally responsible behavior is a prominent contributor to the sustainable development of tourist destinations. Based on the original Value-Identity-Personal norm (VIP) model and self-efficacy theory, this study proposes an extended VIP model for exploring the generalized determinants of tourists’ environmentally responsible behavior and investigating the impact mechanism of this behavior in China. A total number of 435 self-reported questionnaires were collected on a professional online survey platform. Our research results indicated that the extended VIP model could significantly and validly explain tourists’ environmentally responsible behavior. Specifically, biospheric values have an indirect but rooted effect on tourists’ environmentally responsible behavior. Furthermore, two indirect paths play the same mediational role between biospheric values and tourists’ environmentally responsible behavior. The findings expand the application field of the VIP model, contribute to a better understanding for academic researchers of tourists’ environmentally responsible behavior and shed light on managerial implications for practitioners in the sustainable development of tourist destinations.
Using the Norm Activation Model to Predict the Pro-Environmental Behaviors of Public Servants at the Central and Local Governments in Taiwan
Authors: Fang Wei-Ta , Chiang Yi-Te , Ng Eric , Lo Jen-Chieh
Published: July 2019

An understanding of the environmental value-action gap between public servants at the central and local governments is essential for the effective implementation of environmental policies, which is limited in the extant literature. This study has adopted the norm activation model to explore the pro-environmental behaviors of public servants at the central and local governments in Taiwan. A total of 7567 valid questionnaires were collected, and significant differences were evident between public servants at the central (n = 3400) and local (n = 4167) governments in personal norms, awareness of consequences, ascription of responsibility, and pro-environmental behaviors. Findings revealed that personal norms were the key factors predicting pro-environmental behaviors of public servants at both the central and local governments. Results also indicated that the awareness of consequences by public servants at the central government had a direct effect on their pro-environmental behaviors, which in turn had a significant effect on their ascription of responsibility. In contrast, awareness of consequences by public servants at the local government had no significant direct effect on their pro-environmental behaviors and had only a weak positive effect on their ascription of responsibility.
Agritourism in Mountainous Regions—Insights from an International Perspective
Authors: Chiodo Emilio , Fantini Andrea , Dickes Lori , Arogundade Temitope , Lamie R. David , Assing Lucilene , Stewart Corinne , Salvatore Rita
Published: July 2019

Based on the research activity within the ISLE International Sustainability Network, this paper represents a step forward aiming to find some contacts points in the experiences some international cases (USA, Brazil, Italy and France) have grown in the development of agritourism in mountain contexts. Despite the singular differences and the national specificities, agritourism is generally considered a particular form of social innovation in agriculture and rural development of mountainous areas, aiming at recomposing the natural and the human dimensions within the framework of a new sustainable way of doing agriculture. At the basis of the research is the hypothesis that agritourism operations are slowly and gradually shifting towards a new perspective/model. Some years ago, agritourism was traditionally viewed as a way for farmers to integrate or diversify their incomes. Nowadays instead—as the diversity of practice has grown and new values have emerged—the range of farmers’ motivations has become much broader. Some of these motivations include not only economic issues but also social, environmental and cultural ones, while addressing a more comprehensive idea of community-based and sustainable development. Case studies from South Carolina (USA), from Italian mountain regions, from Santa Catarina State in Brazil and from France are illustrated in which different innovation perspectives are highlighted.
Do Overnight Returns Truly Measure Firm-Specific Investor Sentiment in the KOSPI Market?
Authors: Seok Sang Ik , Cho Hoon , Park Chanhi , Ryu Doojin
Published: July 2019

This study analyzes the effect of overnight returns on subsequent stock market returns and investigates whether they do capture investor sentiment in the Korean stock market. Recent study showed that overnight returns are similar to existing sentiment measures, and, thus, are suitable for measuring firm-specific investor sentiment in the U.S. market. Similarly, we found that, for firms in the Korean market, high overnight returns are followed by higher stock returns in the short term (i.e., two or three trading days) but lower stock returns in the long term. However, these effects do not differ for different types of firms (i.e., hard-to-value firms), whereas classical firm-specific sentiment indicators capture these differences. Overall, we found that overnight returns do not truly measure firm-specific investor sentiment in the Korean stock market even though they are partially related to investor sentiment.
Configuring New Business Models for Circular Economy through Product–Service Systems
Authors: P. P. Pieroni Marina , C. McAloone Tim , C. A. Pigosso Daniela
Published: July 2019

Product—service systems (PSSs) are often outlined as potential enablers of new business models for circular economy. However, not all business models based on product-service systems have superior circularity potential. This research demonstrates how the application of a previously developed business model configurator for circular economy can support the design and assessment of customer value, economic and resource decoupling potential for product-service system business models in practice. By applying action research in two Nordic manufacturing companies from the furniture sector, different business model concepts based on product-service systems were proposed and assessed. Results indicate positive uptake by companies regarding the usefulness of the obtained outcomes. This research identified two key findings about ‘product-service system business models for circular economy’: (i) their configuration should fulfil certain simultaneous conditions—i.e. superior customer value, economic growth, and resource decoupling potential—to contribute to circular economy; and (ii) they are often ‘niche solutions’, fulfilling specific needs and customer segments, and more likely to flourish with certain types/characteristic of products, segments or geographical locations. Lastly, a framework outlining the conditions and trade-offs for assessing the circularity potential of business models based on product-service systems is introduced as one of the key contributions.
Development of an Innovative Land Valuation Model (iLVM) for Mass Appraisal Application in Sub-Urban Areas Using AHP: An Integration of Theoretical and Practical Approaches
Authors: Bencure Jannet C. , Tripathi Nitin K. , Miyazaki Hiroyuki , Ninsawat Sarawut , Kim Sohee Minsun
Published: July 2019

Land development in sub-urban areas is more frequent than in highly urbanized cities, causing land prices to increase abruptly and making it harder for valuers to update land values in timely manner. Apart from this, the non-availability of sufficient reliable market values forces valuers to use alternatives and subjective judgement. Land value is critical not only for private individuals but also for government agencies in their day-to-day land dealings. Thus, mass appraisal is necessary. In other words, despite the importance of reliable land value in all aspects of land administration, valuation remains disorganized, with unregulated undertakings that lack concrete scientific, legal, and practical foundations. A holistic and objective way of weighing geospatial factors through expert consultation, legal reviews, and evidence (i.e., news) will provide more realistic results than a regression-based method that does not comprehend valuation factors (i.e., physical, social, economic, environmental, and legal aspects). The analytic hierarchy process (AHP) enables these factors to be included in the model, hence providing a realistic result. The innovative land valuation model (iLVM), developed in this study, is an inclusive approach wherein experts are involved in the selection and weighing of 15 factors through the AHP. The model was validated using root mean squared error (RMSE) and compared with multiple regression analysis (MRA) through a case study in Baybay City, Philippines. Based on the results, the iLVM (RMSE = 0.526) outperformed MRA (RMSE = 1.953).
Periodic Solution of a Non-Smooth Double Pendulum with Unilateral Rigid Constrain
Authors: Guo Xiuying , Zhang Gang , Tian Ruilan
Published: July 2019

In this paper, a double pendulum model is presented with unilateral rigid constraint under harmonic excitation, which leads to be an asymmetric and non-smooth system. By introducing impact recovery matrix, modal analysis, and matrix theory, the analytical expressions of the periodic solutions for unilateral double-collision will be discussed in high-dimensional non-smooth asymmetric system. Firstly, the impact laws are classified in order to detect the existence of periodic solutions of the system. The impact recovery matrix is introduced to transform the impact laws of high-dimensional system into matrix. Furthermore, by use of modal analysis and matrix theory, an invertible transformation is constructed to obtain the parameter conditions for the existence of the impact periodic solution, which simplifies the calculation and can be easily extended to high-dimensional non-smooth system. Hence, the range of physical parameters and the restitution coefficients is calculated theoretically and non-smooth analytic expression of the periodic solution is given, which provides ideas for the study of approximate analytical solutions of high-dimensional non-smooth system. Finally, numerical simulation is carried out to obtain the impact periodic solution of the system with small angle motion.
Algebraic Numbers as Product of Powers of Transcendental Numbers
Authors: Trojovský Pavel
Published: July 2019

The elementary symmetric functions play a crucial role in the study of zeros of non-zero polynomials in C [ x ] , and the problem of finding zeros in Q [ x ] leads to the definition of algebraic and transcendental numbers. Recently, Marques studied the set of algebraic numbers in the form P ( T ) Q ( T ) . In this paper, we generalize this result by showing the existence of algebraic numbers which can be written in the form P 1 ( T ) Q 1 ( T ) ⋯ P n ( T ) Q n ( T ) for some transcendental number T, where P 1 , … , P n , Q 1 , … , Q n are prescribed, non-constant polynomials in Q [ x ] (under weak conditions). More generally, our result generalizes results on the arithmetic nature of z w when z and w are transcendental.
The Three-Way Decisions Method Based on Theory of Reliability with SV-Triangular Neutrosophic Numbers
Authors: Li Xiang , Huang Xianjiu
Published: July 2019

Three-way decisions, as a decision-making mode which is consistent with human cognition, have been widely used in various fields. In this paper, we fuse the theory of reliability into the three-way decisions method, replace the conditional probability in the three-way decisions method with reliability, and then propose a novel three-way decisions method. We also describe the loss functions with single-valued triangular neutrosophic numbers (SVTNNs) and propose an operator to calculate the score function of triangular neutrosophic numbers. Then, the result of decision is attained according to the principle of minimizing loss. Finally, we apply this method to the overhaul of machines in a factory, which proves the practicability and effectiveness of the proposed methods.
A System of Mining Semantic Trajectory Patterns from GPS Data of Real Users
Authors: Zhang Wanlong , Wang Xiang , Huang Zhitao
Published: July 2019

Positioning devices allow users’ movement to be recorded. The GPS (Global Positioning System) trajectory data typically consists of spatiotemporal points, which make up the major part of the big data concerning urban life. Existing knowledge extraction methods about the trajectory share a general limitation—they only investigate data from a spatiotemporal aspect, but fail to take the semantic information of trajectories into consideration. Therefore, extracting the semantic information of trajectories with the context of big data is challenging pattern recognition task that has practical application prospects. In this paper, a system is proposed to extract the semantic trajectory patterns of positioning device users. Firstly, a spatiotemporal threshold and clustering based pre-processing model is proposed to process the raw data. Then, we design a probabilistic generative model to annotate the semantic information of each trajectory after the pre-processing procedure. Finally, we apply the PrefixSpan algorithm to mine the semantic trajectory patterns. We verify our system on a large dataset of users’ real trajectories over a period of 5 years in Beijing, China. The results of the experiment indicate that our system produces meaningful patterns.
Online Learning Method for Drift and Imbalance Problem in Client Credit Assessment
Authors: Zhang Hang , Liu Qingbao
Published: July 2019

Machine learning algorithms have been widely used in the field of client credit assessment. However, few of the algorithms have focused on and solved the problems of concept drift and class imbalance. Due to changes in the macroeconomic environment and markets, the relationship between client characteristics and credit assessment results may change over time, causing concept drift in client credit assessments. Moreover, client credit assessment data are naturally asymmetric and class imbalanced because of the screening of clients. Aiming at solving the joint research issue of concept drift and class imbalance in client credit assessments, in this paper, a novel sample-based online learning ensemble (SOLE) for client credit assessment is proposed. A novel multiple time scale ensemble classifier and a novel sample-based online class imbalance learning procedure are proposed to handle the potential concept drift and class imbalance in the client credit assessment data streams. The experiments are carried out on two real-world client credit assessment cases, which present a comprehensive comparison between the proposed SOLE and other state-of-the-art online learning algorithms. In addition, the base classifier preference and the computing resource consumption of all the comparative algorithms are tested. In general, SOLE achieves a better performance than other methods using fewer computing resources. In addition, the results of the credit scoring model and the Kolmogorov–Smirnov (KS) test also prove that SOLE has good practicality in actual client credit assessment applications.
Selective Poisoning Attack on Deep Neural Networks †
Authors: Kwon Hyun , Yoon Hyunsoo , Park Ki-Woong
Published: July 2019

Studies related to pattern recognition and visualization using computer technology have been introduced. In particular, deep neural networks (DNNs) provide good performance for image, speech, and pattern recognition. However, a poisoning attack is a serious threat to a DNN’s security. A poisoning attack reduces the accuracy of a DNN by adding malicious training data during the training process. In some situations, it may be necessary to drop a specifically chosen class of accuracy from the model. For example, if an attacker specifically disallows nuclear facilities to be selectively recognized, it may be necessary to intentionally prevent unmanned aerial vehicles from correctly recognizing nuclear-related facilities. In this paper, we propose a selective poisoning attack that reduces the accuracy of only the chosen class in the model. The proposed method achieves this by training malicious data corresponding to only the chosen class while maintaining the accuracy of the remaining classes. For the experiment, we used tensorflow as the machine-learning library as well as MNIST, Fashion-MNIST, and CIFAR10 as the datasets. Experimental results show that the proposed method can reduce the accuracy of the chosen class by 43.2%, 41.7%, and 55.3% in MNIST, Fashion-MNIST, and CIFAR10, respectively, while maintaining the accuracy of the remaining classes.
Multivariate Optimal Control with Payoffs Defined by Submanifold Integrals
Authors: Bejenaru Andreea , Udriste Constantin
Published: July 2019

This paper adapts the multivariate optimal control theory to a Riemannian setting. In this sense, a coherent correspondence between the key elements of a standard optimal control problem and several basic geometric ingredients is created, with the purpose of generating a geometric version of Pontryagin’s maximum principle. More precisely, the local coordinates on a Riemannian manifold play the role of evolution variables (“multitime”), the Riemannian structure, and the corresponding Levi–Civita linear connection become state variables, while the control variables are represented by some objects with the properties of the Riemann curvature tensor field. Moreover, the constraints are provided by the second order partial differential equations describing the dynamics of the Riemannian structure. The shift from formal analysis to optimal Riemannian control takes deeply into account the symmetries (or anti-symmetries) these geometric elements or equations rely on. In addition, various submanifold integral cost functionals are considered as controlled payoffs.
Disformal Transformations in Scalar–Torsion Gravity
Authors: Hohmann Manuel
Published: July 2019

We study disformal transformations in the context of scalar extensions to teleparallel gravity, in which the gravitational interaction is mediated by the torsion of a flat, metric compatible connection. We find a generic class of scalar–torsion actions which is invariant under disformal transformations, and which possesses different invariant subclasses. For the most simple of these subclasses we explicitly derive all terms that may appear in the action. We propose to study actions from this class as possible teleparallel analogues of healthy beyond Horndeski theories.
The General Linear Cartan Khronon
Authors: Koivisto Tomi , Hohmann Manuel , Złośnik Tom
Published: July 2019

A Cartan geometry of the General Linear symmetry is formulated by dividing out the displacements from the group. The resulting action is quadratic in curvature, polynomial in all the (minimal) variables, and describes an observer space that—in the symmetry-broken phase—reproduces the predictions of General Relativity in the presence of dark matter.
Crystal Structure of the Japanese Encephalitis Virus Capsid Protein
Authors: Poonsiri Thanalai , Wright Gareth S. A. , Solomon Tom , Antonyuk Svetlana V.
Published: July 2019

Japanese encephalitis (JE) is inflammation and swelling of the brain caused by the JE virus (JEV), a mosquito-borne member of the Flavivirus family. There are around 68,000 JE cases worldwide each year, many of which result in permanent brain damage and death. There is no specific treatment for JE. Here we present the crystal structure of the JEV capsid protein, a potential drug target, at 1.98 Å, and compare it to other flavivirus capsid proteins. The JEV capsid has a helical secondary structure (α helixes 1–4) and a similar protein fold to the dengue virus (DENV), the West Nile virus (WNV), and the Zika virus (ZIKV) capsid proteins. It forms a homodimer by antiparallel pairing with another subunit (‘) through α-helix 1-1’, 2-2’, and 4-4’ interactions. This dimeric form is believed to be the building block of the nucleocapsid. The flexibility of the N-terminal α helix-1 allows the formation of closed and open conformations with possible functional importance. The basic C-terminal pairing of α4-4’ forms a coiled-coil-like structure, indicating possible nucleic acid binding functionality. However, a comparison with other nucleic acid interacting domains indicates that homodimerization would preclude binding. This is the first JEV capsid protein to be described and is an addition to the structural biology of the Flavivirus.
Antiviral Efficacy of Flavonoids against Enterovirus 71 Infection in Vitro and in Newborn Mice
Authors: Dai Wenwen , Bi Jinpeng , Li Fang , Wang Shuai , Huang Xinyu , Meng Xiangyu , Sun Bo , Wang Deli , Kong Wei , Jiang Chunlai , Su Weiheng
Published: July 2019

Enterovirus 71 (EV71) infection is known to cause hand, foot, and mouth disease (HFMD), which is associated with neurological complications; however, there is currently no effective treatment for this infection. Flavonoids are a large group of naturally occurring compounds with multiple bioactivities, and the inhibitory effects of several flavonoids against EV71 have been studied in cell cultures; however, to date, there are no reported data on their effects in animal models. In this study, we confirmed the in vitro activities of eight flavonoids against EV71 infection, based on the inhibition of cytopathic effects. Moreover, these flavonoids were found to reduce viral genomic RNA replication and protein synthesis. We further demonstrated the protective efficacy of these flavonoids in newborn mice challenged with a lethal dose of EV71. Apigenin, luteolin, kaempferol, formononetin, and penduletin conferred survival protection of 88.89%, 91.67%, 88.89%, 75%, and 66.67%, respectively, from the lethal EV71 challenge. In addition, isorhamnetin provided the highest mice survival protection of 100% at a dose of 10 mg/kg. This study, to the best of our knowledge, is the first to evaluate the in vivo anti-EV7l activities of multiple flavonoids, and we accordingly identified flavonoids as potential leading compounds for anti-EV71 drug development.
Evolutionary and Functional Diversity of the 5′ Untranslated Region of Enterovirus D68: Increased Activity of the Internal Ribosome Entry Site of Viral Strains during the 2010s
Authors: Furuse Yuki , Chaimongkol Natthawan , Okamoto Michiko , Oshitani Hitoshi
Published: July 2019

The 5′ untranslated region (UTR) of the RNA genomes of enteroviruses possesses an internal ribosome entry site (IRES) that directs translation of the mRNA by binding to ribosomes. Infection with enterovirus D68 causes respiratory symptoms and is sometimes associated with neurological disorders. The number of reports of the viral infection and neurological disorders has increased in 2010s, although the reason behind this phenomenon remains unelucidated. In this study, we investigated the evolutionary and functional diversity of the 5′ UTR of recently circulating strains of the virus. Genomic sequences of 374 viral strains were acquired and subjected to phylogenetic analysis. The IRES activity of the viruses was measured using a luciferase reporter assay. We found a highly conserved sequence in the 5′ UTR and also identified the location of variable sites in the predicted RNA secondary structure. IRES activities differed among the strains in some cell lines, including neuronal and respiratory cells, and were especially high in strains of a major lineage from the recent surge. The effect of mutations in the 5′ UTR should be studied further in the future for better understanding of viral pathogenesis.
The Optimal Concentration of Formaldehyde is Key to Stabilizing the Pre-Fusion Conformation of Respiratory Syncytial Virus Fusion Protein
Authors: Zhang Wei , Zhang Lu-Jing , Zhan Lu-Ting , Zhao Min , Wu Guang-Hua , Si Jun-Yu , Chen Li , Lin Xue , Sun Yong-Peng , Lin Min , Yu Chao , Fang Mu-Jin , Wang Ying-Bin , Zheng Zi-Zheng , Xia Ning-Shao
Published: July 2019

Background: To date, there is no licensed vaccine available to prevent respiratory syncytial virus (RSV) infection. The valuable pre-fusion conformation of the fusion protein (pre-F) is prone to lose high neutralizing antigenic sites. The goals of this study were to stabilize pre-F protein by fixatives and try to find the possibility of developing an inactivated RSV vaccine. Methods: The screen of the optimal fixative condition was performed with flow cytometry. BALB/c mice were immunized intramuscularly with different immunogens. The serum neutralizing antibody titers of immunized mice were determined by neutralization assay. The protection and safety of these immunogens were assessed. Results: Fixation in an optimal concentration of formaldehyde (0.0244%–0.0977%) or paraformaldehyde (0.0625%–1%) was able to stabilize pre-F. Additionally, BALB/c mice inoculated with optimally stabilized pre-F protein (opti-fixed) induced a higher anti-RSV neutralization (9.7 log2, mean value of dilution rate) than those inoculated with unstable (unfixed, 8.91 log2, p < 0.01) or excessively fixed (exce-fixed, 7.28 log2, p < 0.01) pre-F protein. Furthermore, the opti-fixed immunogen did not induce enhanced RSV disease. Conclusions: Only the proper concentration of fixatives could stabilize pre-F and the optimal formaldehyde condition provides a potential reference for development of an inactivated RSV vaccine.