bluuebunny/crossref_metadata_2025 huggingface dataset:
Intercomparison of Surface Albedo Retrievals from MISR, MODIS, CGLS Using Tower and Upscaled Tower Measurements
Authors: Song Rui , Muller Jan-Peter , Kharbouche Said , Woodgate William
Published: March 2019

Surface albedo is of crucial interest in land–climate interaction studies, since it is a key parameter that affects the Earth’s radiation budget. The temporal and spatial variation of surface albedo can be retrieved from conventional satellite observations after a series of processes, including atmospheric correction to surface spectral bi-directional reflectance factor (BRF), bi-directional reflectance distribution function (BRDF) modelling using these BRFs, and, where required, narrow-to-broadband albedo conversions. This processing chain introduces errors that can be accumulated and then affect the accuracy of the retrieved albedo products. In this study, the albedo products derived from the multi-angle imaging spectroradiometer (MISR), moderate resolution imaging spectroradiometer (MODIS) and the Copernicus Global Land Service (CGLS), based on the VEGETATION and now the PROBA-V sensors, are compared with albedometer and upscaled in situ measurements from 19 tower sites from the FLUXNET network, surface radiation budget network (SURFRAD) and Baseline Surface Radiation Network (BSRN) networks. The MISR sensor onboard the Terra satellite has 9 cameras at different view angles, which allows a near-simultaneous retrieval of surface albedo. Using a 16-day retrieval algorithm, the MODIS generates the daily albedo products (MCD43A) at a 500-m resolution. The CGLS albedo products are derived from the VEGETATION and PROBA-V, and updated every 10 days using a weighted 30-day window. We describe a newly developed method to derive the two types of albedo, which are directional hemispherical reflectance (DHR) and bi-hemispherical reflectance (BHR), directly from three tower-measured variables of shortwave radiation: downwelling, upwelling and diffuse shortwave radiation. In the validation process, the MISR, MODIS and CGLS-derived albedos (DHR and BHR) are first compared with tower measured albedos, using pixel-to-point analysis, between 2012 to 2016. The tower measured point albedos are then upscaled to coarse-resolution albedos, based on atmospherically corrected BRFs from high-resolution Earth observation (HR-EO) data, alongside MODIS BRDF climatology from a larger area. Then a pixel-to-pixel comparison is performed between DHR and BHR retrieved from coarse-resolution satellite observations and DHR and BHR upscaled from accurate tower measurements. The experimental results are presented on exploring the parameter space associated with land cover type, heterogeneous vs. homogeneous and instantaneous vs. time composite retrievals of surface albedo.
Preliminary Assessment of Turbidity and Chlorophyll Impact on Bathymetry Derived from Sentinel-2A and Sentinel-3A Satellites in South Florida
Authors: Caballero Isabel , Stumpf Richard , Meredith Andrew
Published: March 2019

Evaluation of the impact of turbidity on satellite-derived bathymetry (SDB) is a crucial step for selecting optimal scenes and for addressing the limitations of SDB. This study examines the relatively high-resolution MultiSpectral instrument (MSI) onboard Sentinel-2A (10–20–60 m) and the moderate-resolution Ocean and Land Color instrument (OLCI) onboard Sentinel-3A (300 m) for generating bathymetric maps through a conventional ratio transform model in environments with some turbidity in South Florida. Both sensors incorporate additional spectral bands in the red-edge near infrared (NIR) region, allowing turbidity detection in optically shallow waters. The ratio model only requires two calibration parameters for vertical referencing using available chart data, whereas independent lidar surveys are used for validation and error analysis. The MSI retrieves bathymetry at 10 m with errors of 0.58 m at depths ranging between 0–18 m (limit of lidar survey) in West Palm Beach and of 0.22 m at depths ranging between 0–5 m in Key West, in conditions with low turbidity. In addition, this research presents an assessment of the SDB depth limit caused by turbidity as determined with the reflectance of the red-edge bands at 709 nm (OLCI) and 704 nm (MSI) and a standard ocean color chlorophyll concentration. OLCI and MSI results are comparable, indicating the potential of the two optical missions as interchangeable sensors that can help determine the selection of the optimal scenes for SDB mapping. OLCI can provide temporal data to identify water quality characteristics and general SDB patterns. The relationship of turbidity with depth detection may help to enhance the operational use of SDB over environments with varying water transparency conditions, particularly in remote and inaccessible regions of the world.
Land Surface Temperature Retrieval from Sentinel-3A Sea and Land Surface Temperature Radiometer, Using a Split-Window Algorithm
Authors: Zheng Yitong , Ren Huazhong , Guo Jinxin , Ghent Darren , Tansey Kevin , Hu Xingbang , Nie Jing , Chen Shanshan
Published: March 2019

Land surface temperature (LST) is a crucial parameter in the interaction between the ground and the atmosphere. The Sentinel-3A Sea and Land Surface Temperature Radiometer (SLSTR) provides global daily coverage of day and night observation in the wavelength range of 0.55 to 12.0 μm. LST retrieved from SLSTR is expected to be widely used in different fields of earth surface monitoring. This study aimed to develop a split-window (SW) algorithm to estimate LST from two-channel thermal infrared (TIR) and one-channel middle infrared (MIR) images of SLSTR observation. On the basis of the conventional SW algorithm, using two TIR channels for the daytime observation, the MIR data, with a higher atmospheric transmittance and a lower sensitivity to land surface emissivity, were further used to develop a modified SW algorithm for the nighttime observation. To improve the retrieval accuracy, the algorithm coefficients were obtained in different subranges, according to the view zenith angle, column water vapor, and brightness temperature. The proposed algorithm can theoretically estimate LST with an error lower than 1 K on average. The algorithm was applied to northern China and southern UK, and the retrieved LST captured the surface features for both daytime and nighttime. Finally, ground validation was conducted over seven sites (four in the USA and three in China). Results showed that LST could be estimated with an error mostly within 1.5 to 2.5 K from the algorithm, and the error of the nighttime algorithm involved with MIR data was about 0.5 K lower than the daytime algorithm.
Identification of a Threshold Minimum Area for Reflectance Retrieval from Thermokarst Lakes and Ponds Using Full-Pixel Data from Sentinel-2
Authors: Freitas Pedro , Vieira Gonçalo , Canário João , Folhas Diogo , Vincent Warwick F.
Published: March 2019

Thermokarst waterbodies caused by permafrost thawing and degradation are ubiquitous in many subarctic and Arctic regions. They are globally important components of the biogeochemical carbon cycle and have potential feedback effects on climate. These northern waters are mostly small lakes and ponds, and although they may be mapped using very high-resolution satellites or aerial photography, these approaches are generally not suitable for monitoring purposes, due to the cost and limited availability of such images. In this study we evaluated the potential use of widely available high-resolution imagery from Sentinel-2 (S2) for the characterization of the spectral reflectance of thermokarst lakes and ponds. Specifically, we aimed to define the minimum lake area that could be reliably imaged, and to identify challenges and solutions for remote sensing of such waters in the future. The study was conducted in subarctic Canada, in the vicinity of Whapmagoostui-Kuujjuarapik (Nunavik, Québec), an area in the sporadic permafrost zone with numerous thermokarst waterbodies that vary greatly in size. Ground truthing lake reflectance data were collected using an Unmanned Aerial System (UAS) fitted with a multispectral camera that collected images at 13 cm resolution. The results were compared with reflectance from Sentinel-2 images, and the effect of lake area on the reflectance response was assessed. Our results show that Sentinel-2 imagery was suitable for waterbodies larger than 350 m2 once their boundaries were defined, which in the two test sites would allow monitoring from 11% to 30% of the waterbodies and 73% to 85% of the total lake area. Challenges for remote sensing of small lakes include the confounding effects of water reflection (both direct radiation and diffuse), wind and shadow. Given the small threshold area and frequent revisit time, Sentinel-2 provides a valuable approach towards the continuous monitoring of waterbodies, including ponds and small lakes such as those found in thermokarst landscapes. UASs provide a complementary approach for ground truthing and boundary definition.
Operational Large-Scale Segmentation of Imagery Based on Iterative Elimination
Authors: Shepherd James , Bunting Pete , Dymond John
Published: March 2019

Image classification and interpretation are greatly aided through the use of image segmentation. Within the field of environmental remote sensing, image segmentation aims to identify regions of unique or dominant ground cover from their attributes such as spectral signature, texture and context. However, many approaches are not scalable for national mapping programmes due to limits in the size of images that can be processed. Therefore, we present a scalable segmentation algorithm, which is seeded using k-means and provides support for a minimum mapping unit through an innovative iterative elimination process. The algorithm has also been demonstrated for the segmentation of time series datasets capturing both the intra-image variation and change regions. The quality of the segmentation results was assessed by comparison with reference segments along with statistics on the inter- and intra-segment spectral variation. The technique is computationally scalable and is being actively used within the national land cover mapping programme for New Zealand. Additionally, 30-m continental mosaics of Landsat and ALOS-PALSAR have been segmented for Australia in support of national forest height and cover mapping. The algorithm has also been made freely available within the open source Remote Sensing and GIS software Library (RSGISLib).
Highly Sensitive Tactile Shear Sensor Using Spatially Digitized Contact Electrodes
Authors: Choi Eunsuk , Hwang Soonhyung , Yoon Yousang , Seo Hojun , Lee Jusin , Yeom Seongoh , Ryu Gunwoo , Yang Heewon , Kim Sunjin , Sul Onejae , Lee Seung-Beck
Published: March 2019

In this article, we report on a highly sensitive tactile shear sensor that was able to detect minute levels of shear and surface slip. The sensor consists of a suspended elastomer diaphragm with a top ridge structure, a graphene layer underneath, and a bottom substrate with multiple spatially digitized contact electrodes. When shear is applied to the top ridge structure, it creates torque and deflects the elastomer downwards. Then, the graphene electrode makes contact with the bottom spatially digitized electrodes completing a circuit producing output currents depending on the number of electrodes making contact. The tactile shear sensor was able to detect shear forces as small as 6 μN, detect shear direction, and also distinguish surface friction and roughness differences of shearing objects. We also succeeded in detecting the contact slip motion of a single thread demonstrating possible applications in future robotic fingers and remote surgical tools.
Assessing Spatial Flood Vulnerability at Kalapara Upazila in Bangladesh Using an Analytic Hierarchy Process
Authors: Hoque Muhammad Al-Amin , Tasfia Saima , Ahmed Naser , Pradhan Biswajeet
Published: March 2019

Floods are common natural disasters worldwide, frequently causing loss of lives and huge economic and environmental damages. A spatial vulnerability mapping approach incorporating multi-criteria at the local scale is essential for deriving detailed vulnerability information for supporting flood mitigation strategies. This study developed a spatial multi-criteria-integrated approach of flood vulnerability mapping by using geospatial techniques at the local scale. The developed approach was applied on Kalapara Upazila in Bangladesh. This study incorporated 16 relevant criteria under three vulnerability components: physical vulnerability, social vulnerability and coping capacity. Criteria were converted into spatial layers, weighted and standardised to support the analytic hierarchy process. Individual vulnerability component maps were created using a weighted overlay technique, and then final vulnerability maps were produced from them. The spatial extents and levels of vulnerability were successfully identified from the produced maps. Results showed that the areas located within the eastern and south-western portions of the study area are highly vulnerable to floods due to low elevation, closeness to the active channel and more social components than other parts. However, with the integrated coping capacity, western and south-western parts are highly vulnerable because the eastern part demonstrated particularly high coping capacity compared with other parts. The approach provided was validated by qualitative judgement acquired from the field. The findings suggested the capability of this approach to assess the spatial vulnerability of flood effects in flood-affected areas for developing effective mitigation plans and strategies.
Analysis of Mobile Edge Computing for Vehicular Networks
Authors: Lamb Zachary W. , Agrawal Dharma P.
Published: March 2019

Vehicular ad-hoc Networks (VANETs) are an integral part of intelligent transportation systems (ITS) that facilitate communications between vehicles and the internet. More recently, VANET communications research has strayed from the antiquated DSRC standard and favored more modern cellular technologies, such as fifth generation (5G). The ability of cellular networks to serve highly mobile devices combined with the drastically increased capacity of 5G, would enable VANETs to accommodate large numbers of vehicles and support range of applications. The addition of thousands of new connected devices not only stresses the cellular networks, but also the computational and storage requirements supporting the applications and software of these devices. Autonomous vehicles, with numerous on-board sensors, are expected to generate large amounts of data that must be transmitted and processed. Realistically, on-board computing and storage resources of the vehicle cannot be expected to handle all data that will be generated over the vehicles lifetime. Cloud computing will be an essential technology in VANETs and will support the majority of computation and long-term data storage. However, the networking overhead and latency associated with remote cloud resources could prove detrimental to overall network performance. Edge computing seeks to reduce the overhead by placing computational resources nearer to the end users of the network. The geographical diversity and varied hardware configurations of resource in a edge-enabled network would require careful management to ensure efficient resource utilization. In this paper, we introduce an architecture which evaluates available resources in real-time and makes allocations to the most logical and feasible resource. We evaluate our approach mathematically with the use of a multi-criteria decision analysis algorithm and validate our results with experiments using a test-bed of cloud resources. Results demonstrate that an algorithmic ranking of physical resources matches very closely with experimental results and provides a means of delegating tasks to the best available resource.
Simultaneous Electrochemical Detection of Nitrite and Hydrogen Peroxide Based on 3D Au-rGO/FTO Obtained Through a One-Step Synthesis
Authors: Li Chengcheng , Chen Delun , Wang Yuanyuan , Lai Xiaoyong , Peng Juan , Wang Xiaohong , Zhang Kexi , Cao Yang
Published: March 2019

In this paper, Au and reduced graphene oxide (rGO) were successively deposited on fluorine-doped SnO2 transparent conductive glass (FTO, 1 × 2 cm) via a facile and one-step electrodeposition method to form a clean interface and construct a three-dimensional network structure for the simultaneous detection of nitrite and hydrogen peroxide (H2O2). For nitrite detection, 3D Au-rGO/FTO displayed a sensitivity of 419 μA mM−1 cm−2 and a linear range from 0.0299 to 5.74 mM, while for the detection of H2O2, the sensitivity was 236 μA mM−1 cm−2 and a range from 0.179 to 10.5 mM. The combined results from scanning electron microscopy (SEM), transmission electron microscopy (TEM), Raman spectroscopy, X-ray diffraction measurements (XRD) and electrochemical tests demonstrated that the properties of 3D Au-rGO/FTO were attributabled to the conductive network consisting of rGO and the good dispersion of Au nanoparticles (AuNPs) which can provide better electrochemical properties than other metal compounds, such as a larger electroactive surface area, more active sites, and a bigger catalytic rate constant.
Resolvable Group State Estimation with Maneuver Based on Labeled RFS and Graph Theory
Authors: Liu Weifeng , Chi Yudong
Published: March 2019

In this paper, multiple resolvable group target tracking was considered in the frame of random finite sets. In particular, a group target model was introduced by combining graph theory with the labeled random finite sets (RFS). This accounted for dependence between group members. Simulations were presented to verify the proposed algorithm.
Performance Evaluation of Miniature Integrated Electrochemical Cells Fabricated Using LTCC Technology
Authors: Szymanowska Paulina , Nowak Damian , Piasecki Tomasz
Published: March 2019

Miniaturized and integrated analytical devices, including chemical sensors, are at the forefront of modern analytical chemistry. The construction of novel analytical tools takes advantage of contemporary micro- and nanotechnologies, as well as materials science and technology. Two electrochemical techniques were used in experiments: electrochemical impedance spectroscopy and cyclic voltammetry. The goal of this study was to investigate electron transfer resistance in a model solution containing Fe 2 + / 3 + ions and protein adsorption using integrated electrochemical cells with different geometry. Tests performed at various Fe 2 + / 3 + concentration allowed to verify that these cells work properly. The influence of bovine serum albumin adsorbing to the surface of the integrated electrochemical cells was investigated. In electrochemical impedance spectroscopy, the value of R c t increased with protein adsorption and the relative change of R c t was in range 21% to 55%. In cyclic voltammetry the decreasing amperometric response of the working electrode was used as evidence of protein adsorption on the electrode.
Calibration of Linear Time-Varying Frequency Errors for Distributed ISAR Imaging Based on the Entropy Minimization Principle
Authors: Kang Hailong , Li Jun , Zhao Hongyan , Bao Zhiyu , Yu Zehua
Published: March 2019

The inevitable frequency errors owing to the frequency mismatch of a transmitter and receiver oscillators could seriously deteriorate the imaging performance in distributed inverse synthetic aperture radar (ISAR) system. In this paper, for this issue, a novel method is proposed to calibrate the linear time-varying frequency errors (LTFE) between the transmitting node and the receiving node. The cost function is constructed based on the entropy minimization principle and the problem of LTFE calibration is transformed into cost function optimization. The frequency error coefficient, which minimizes the image entropy, is obtained by searching optimum solution in the solution space of cost function. Then, the original signal is calibrated by the frequency error coefficient. Finally, the effectiveness of the proposed method is demonstrated by simulation and real-data experiments.
Data Trustworthiness Evaluation in Mobile Crowdsensing Systems with Users’ Trust Dispositions’ Consideration
Authors: Zupančič Eva , Žalik Borut
Published: March 2019

Mobile crowdsensing is a powerful paradigm that exploits the advanced sensing capabilities and ubiquity of smartphones in order to collect and analyze data on a scale that is impossible with fixed sensor networks. Mobile crowdsensing systems incorporate people and rely on their participation and willingness to contribute up-to-date and accurate information, meaning that such systems are prone to malicious and erroneous data. Therefore, trust and reputation are key factors that need to be addressed in order to ensure sustainability of mobile crowdsensing systems. The objective of this work is to define the conceptual trust framework that considers human involvement in mobile crowdsensing systems and takes into account that users contribute their opinions and other subjective data besides the raw sensing data generated by their smart devices. We propose a novel method to evaluate the trustworthiness of data contributed by users that also considers the subjectivity in the contributed data. The method is based on a comparison of users’ trust attitudes and applies nonparametric statistic methods. We have evaluated the performance of our method with extensive simulations and compared it to the method proposed by Huang that adopts Gompertz function for rating the contributions. The simulation results showed that our method outperforms Huang’s method by 28.6% on average and the method without data trustworthiness calculation by 33.6% on average in different simulation settings.
Dimension Reduction for Hyperspectral Remote Sensor Data Based on Multi-Objective Particle Swarm Optimization Algorithm and Game Theory
Authors: Gao Hongmin , Yang Yao , Zhang Xiaoke , Li Chenming , Yang Qi , Wang Yongchang
Published: March 2019

Information entropy and interclass separability are adopted as the evaluation criteria of dimension reduction for hyperspectral remote sensor data. However, it is rather single-faceted to simply use either information entropy or interclass separability as evaluation criteria, and will lead to a single-target problem. In this case, the chosen optimal band combination may be unfavorable for the improvement of follow-up classification accuracy. Thus, in this work, inter-band correlation is considered as the premise, and information entropy and interclass separability are synthesized as the evaluation criterion of dimension reduction. The multi-objective particle swarm optimization algorithm is easy to implement and characterized by rapid convergence. It is adopted to search for the optimal band combination. In addition, game theory is also introduced to dimension reduction to coordinate potential conflicts when both information entropy and interclass separability are used to search for the optimal band combination. Experimental results reveal that compared with the dimensionality reduction method, which only uses information entropy or Bhattacharyya distance as the evaluation criterion, and the method combining multiple criterions into one by weighting, the proposed method achieves global optimum more easily, and then obtains a better band combination and possess higher classification accuracy.
Super Field-of-View Lensless Camera by Coded Image Sensors
Authors: Nakamura Tomoya , Kagawa Keiichiro , Torashima Shiho , Yamaguchi Masahiro
Published: March 2019

A lensless camera is an ultra-thin computational-imaging system. Existing lensless cameras are based on the axial arrangement of an image sensor and a coding mask, and therefore, the back side of the image sensor cannot be captured. In this paper, we propose a lensless camera with a novel design that can capture the front and back sides simultaneously. The proposed camera is composed of multiple coded image sensors, which are complementary-metal-oxide-semiconductor (CMOS) image sensors in which air holes are randomly made at some pixels by drilling processing. When the sensors are placed facing each other, the object-side sensor works as a coding mask and the other works as a sparsified image sensor. The captured image is a sparse coded image, which can be decoded computationally by using compressive sensing-based image reconstruction. We verified the feasibility of the proposed lensless camera by simulations and experiments. The proposed thin lensless camera realized super-field-of-view imaging without lenses or coding masks and therefore can be used for rich information sensing in confined spaces. This work also suggests a new direction in the design of CMOS image sensors in the era of computational imaging.
A Doppler Range Compensation for Step-Frequency Continuous-Wave Radar for Detecting Small UAV
Authors: Pieraccini Massimiliano , Miccinesi Lapo , Rojhani Neda
Published: March 2019

Step-frequency continuous-wave (SFCW) modulation can have a role in the detection of small unmanned aerial vehicles (UAV) at short range (less than 1–2 km). In this paper, the theory of SFCW range detection is reviewed, and a specific method for correcting the possible range shift due to the Doppler effect is devised. The proposed method was tested in a controlled experimental set-up, where a free-falling target (i.e., a corner reflector) was correctly detected by an SFCW radar. This method was finally applied in field for short-range detection of a small UAV.
Transparent CoAP Services to IoT Endpoints through ICN Operator Networks
Authors: Islam Hasan Mahmood Aminul , Lagutin Dmitrij , Ylä-Jääski Antti , Fotiou Nikos , Gurtov Andrei
Published: March 2019

The Constrained Application Protocol (CoAP) is a specialized web transfer protocol which is intended to be used for constrained networks and devices. CoAP and its extensions (e.g., CoAP observe and group communication) provide the potential for developing novel applications in the Internet-of-Things (IoT). However, a full-fledged CoAP-based application may require significant computing capability, power, and storage capacity in IoT devices. To address these challenges, we present the design, implementation, and experimentation with the CoAP handler which provides transparent CoAP services through the ICN core network. In addition, we demonstrate how the CoAP traffic over an ICN network can unleash the full potential of the CoAP, shifting both overhead and complexity from the (constrained) endpoints to the ICN network. The experiments prove that the CoAP Handler helps to decrease the required computation complexity, communication overhead, and state management of the CoAP server.
UAV Landing Based on the Optical Flow Videonavigation
Authors: Miller Alexander , Miller Boris , Popov Alexey , Stepanyan Karen
Published: March 2019

An automatic landing of an unmanned aerial vehicle (UAV) is a non-trivial task requiring a solution of a variety of technical and computational problems. The most important is the precise determination of altitude, especially at the final stage of approaching to the earth. With current altimeters, the magnitude of measurement errors at the final phase of the descent may be unacceptably high for constructing an algorithm for controlling the landing manoeuvre. Therefore, it is desirable to have an additional sensor, which makes possible to estimate the height above the surface of the runway. It is possible to estimate all linear and angular UAV velocities simultaneously with the help of so-called optical flow (OF), determined by the sequence of images recorded by an onboard camera, however in pixel scale. To transform them into the real metrical values it is necessary to know the current flight altitude and the camera angular position values. The critical feature of the OF is its susceptibility to the camera resolution and the shift rate of the observed scene. During the descent phase of flight, these parameters change at least one hundred times together with the altitude. Therefore, for reliable application of the OF one needs to coordinate the shooting parameters with the current altitude. However, in case of the altimeter fault presence, the altitude is also still to be estimated with the aid of the OF, so one needs to have another tool for the camera control. One of the possible and straightforward ways is the camera resolution change by pixels averaging in computer part which performed in coordination with theoretically estimated and measured OF velocity. The article presents results of such algorithms testing from real video sequences obtained in flights with different approaches to the runway with simultaneous recording of telemetry and video data.
Surface-Enhanced Raman Scattering Detection of Fipronil Pesticide Adsorbed on Silver Nanoparticles
Authors: Ly Nguyễn Hoàng , Nguyen Thi Ha , Nghi Ngô Đình , Kim Young-Han , Joo Sang-Woo
Published: March 2019

This work presents a surface-enhanced Raman scattering (SERS) and density functional theory (DFT) study of a fipronil adsorbed on colloidal silver nanoparticles (AgNPs). A standard curve was established to quantify fipronil within a range of 0.0001–0.1 ppm (r2 ≥ 0.985), relying on the unique fipronil Raman shift at ~2236 cm−1 adsorbed on AgNPs. DFT calculations suggest that the nitrile moiety (C≡N) binding should be slightly more favorable, by 1.92 kcal/mol, than those of the nitrogen atom of the pyrazole in fipronil and Ag6 atom clusters. The characteristic peaks of the SERS spectrum were identified, and both the calculated vibrational wavenumbers and the Raman intensity pattern were considered. The vibrational spectra of fipronil were obtained from the potential energy distribution (PED) analysis and selective Raman band enhancement.
A Deep Learning Framework for Driving Behavior Identification on In-Vehicle CAN-BUS Sensor Data
Authors: Zhang Jun , Wu ZhongCheng , Li Fang , Xie Chengjun , Ren Tingting , Chen Jie , Liu Liu
Published: March 2019

Human driving behaviors are personalized and unique, and the automobile fingerprint of drivers could be helpful to automatically identify different driving behaviors and further be applied in fields such as auto-theft systems. Current research suggests that in-vehicle Controller Area Network-BUS (CAN-BUS) data can be used as an effective representation of driving behavior for recognizing different drivers. However, it is difficult to capture complex temporal features of driving behaviors in traditional methods. This paper proposes an end-to-end deep learning framework by fusing convolutional neural networks and recurrent neural networks with an attention mechanism, which is more suitable for time series CAN-BUS sensor data. The proposed method can automatically learn features of driving behaviors and model temporal features without professional knowledge in features modeling. Moreover, the method can capture salient structure features of high-dimensional sensor data and explore the correlations among multi-sensor data for rich feature representations of driving behaviors. Experimental results show that the proposed framework performs well in the real world driving behavior identification task, outperforming the state-of-the-art methods.
Cardioprotective Activity of Some 2-Arylimino-1,3-Thiazole Derivatives
Authors: Drapak Iryna , Perekhoda Lina , Demchenko Natalya , Suleiman Marharyta , Rakhimova Maryna , Demchuk Inna , Taran Svitlana , Seredynska Nataliya , Gerashchenko Inna
Published: March 2019

The article presents the synthesis of 2-arylimino-4-methyl-2,3-dihydro-1,3-thiazoles via Hantzsch reaction of thioureas and 3-chloropentane-2,4-dione or ethyl 2-chloro-3-oxobutanoate. The structure of synthesized compounds was confirmed by LCMS, 1H, and 13C NMR spectra. Cardioprotective activity of synthesized thiazole derivatives were studied in vitro on the isolated rings of the thoracic aorta of laboratory rats. Based on pharmacological studies, the tested compounds possessed a moderate to high cardioprotective effect. A prospective 1-[2-(4-methoxyphenylimino)-4-methyl-3-(4-methylpiperazine-1-yl)-2,3-dihydro-1,3-thiazole-5-yl] ethan-1-one hydrochloride 4c was identified. The mentioned compound has delayed the development of constrictor responses of isolated rings of the thoracic rat aorta and exceeds the activity of L-carnitine by 18.2% and meldonium by 12.9%. The compound 4c may be proposed as a potential cardioprotective agent for in-depth pharmacological studies.
Financing for a Sustainable PPP Development: Valuation of the Contractual Rights under Exercise Conditions for an Urban Railway PPP Project in Korea
Authors: Kim Kangsoo , Cho Hyejin , Yook Donghyung
Published: March 2019

The Minimum Revenue Guarantee (MRG) was designed to mitigate the financial risk of private investors that participate in the transportation project as concessionaire under a public-private partnership (PPP) program. The MRG can pose a significant financial burden to governments especially when the contract revenue is set considerably higher than the actual revenue. This may encourage the concessionaire to inflate the traffic forecast to make the project look as if it will be profitable. In order to mitigate this problem, extra conditions for exercising the MRG can be considered. This study examines how these exercise conditions change the economic value of the MRG using the case study based on the urban railway project in the Republic of Korea. By utilizing the real options analysis, the study identified that the exercise conditions have worked to curtail the expected payment from the government, eventually leading to a reduction in the concessionaire’s expectation of revenue. The value of MRG was at a far lower level compared to the concessionaire’s investment because of the low probability of exercising the MRG when the exercise conditions apply. The findings are expected to contribute to the sustainability of the PPP program by recognizing and quantifying liabilities and risks embedded in the concession agreement in advance.
Corporate Community Involvement and Chinese Rural Tourist Destination Sustainability
Authors: Yang Xueru , Li Haoming , Chen Wenhong (Miranda) , Fu Hui
Published: March 2019

Although rural tourism enterprises have played crucial roles in the prosperity of tourist destinations, environmental contamination due to corporate behaviour is also an important issue to consider. In this study, we introduce corporate community involvement theory to explore the antecedents and contingency effects of corporate green behaviour for tourist destination sustainability from the perspective of tourism corporate social responsibility. Using first-hand survey data collected in Guangdong and Anhui provinces, and matching second-hand data from the statistical yearbook and tourist destination government work reports, we found that corporate community involvement has a positive impact on the green behaviour of rural tourism enterprises. This association is moderated by place identity and the gross tourism receipts of destinations. By doing so, this research extends the scope of tourism environmental governance from ‘the bottom’ (for tourists) to ‘the top’ (for tourism enterprises). Meanwhile, this research provides feasible advice to policymakers by highlighting the coordination value of enterprises’ initiative strategies (e.g., corporate community involvement) and destination contingency.
The Impact of Foreign Investors on the Stock Price of Korean Enterprises during the Global Financial Crisis
Authors: Kim Yoonmin , Jo Gab-Je
Published: March 2019

This paper investigates the impact and behavior of foreign equity investment on the price of the nine largest KOSPI (Korea Composite Stock Price Index) enterprises and Samsung Electronics preference stocks in terms of market capitalization during the global financial crisis (2 January 2007 to 30 December 2008). The empirical results indicate that foreign investors show strong, positive feedback trading behavior with regard to the stock price of Samsung Electronics, which is the largest KOSPI enterprise in terms of market capitalization. We also found evidence that the behavior of foreign investors significantly increased volatility in the stock returns of the two largest Korean conglomerates (Samsung Electronics and Hyundai Motors), which account for approximately 25 percent of total KOSPI market capitalization.
Improving Sustainability in Architectural Research: Biopsychosocial Requirements in the Design of Urban Spaces
Authors: Santi Giovanni , Leporelli Emanuele , Di Sivo Michele
Published: March 2019

There is an ever increasing interest in identifying the links between architecture and public health and in how urban design can positively influence the latter. The psychology of sustainability and sustainable development represents an innovative research area as a recent contribution to sustainability science and its trans-disciplinary configuration. The research topic deals with the importance and the centrality of the user-centered approach in the observation of the relationships among mankind, technological systems, and built environments, for projects that guarantee the conditions of physical, mental, and social well-being. Starting from the plurality of different disciplinary sectors, from anthropometry and sociology to psychology, “human experience” and user’s expectations are explored, understood, and systematized. The analysis of the relationship between health and urban design has allowed researchers to identify design strategies to improve the level of urban livability. The city of Pisa is the case study; mobility within the city is redefined through various levels of the use of space so that paths and areas of inclusion and socialization are re-valued, while new scenarios for some urban spaces open up. In this perspective, the design strategies synthetically follow two main directions: the re-appropriation of these places by the citizens and, at the same time, the promotion of their well-being from both a physical and psychological point of view.
Energy and Economic Impact on the Application of Low-Cost Lightweight Materials in Economic Housing Located in Dry Climates
Authors: Borbon-Almada Ana Cecilia , Rodriguez-Muñoz Norma Alejandra , Najera-Trejo Mario
Published: March 2019

The building sector is considered a key area for sustainable development, due to the potential to reduce greenhouse gas emissions in the numerous economic activities that this sector involves. A low-cost lightweight cementitious composite consisting in perlite mortar was fabricated and evaluated. The thermal conductivity and heat capacity of the proposed composite were tested in the laboratory. The lightweight composite was integrated into a prototypical house and its thermal performance was tested for two different arid climates during a typical meteorological year. A techno-economic analysis of this integration was carried out, which showed the lightweight system integration could reduce the energy demand up to 10.3% due to the decreased use of heating and cooling systems. The CO2 emissions associated with electricity and gas use on cooling and heating systems could be reduced up to 10.9%.
Influence of Transformational Leadership on Employees’ Innovative Work Behavior in Sustainable Organizations: Test of Mediation and Moderation Processes
Authors: Li Hui , Sajjad Nazir , Wang Qun , Muhammad Ali Asadullah , Khaqan Zeb , Amina Shafi
Published: March 2019

The main objective of this research was to examine how transformational leaders boost their followers’ innovative work behavior through trust in a leader, empowerment, and work engagement. Data were collected from 281 multinational organization employees in China. The Statistical Package for the Social Sciences (SPSS) macro process was utilized to test the proposed hypothesis. The findings revealed that transformational leadership and work engagement were significantly related to innovative work behavior. The findings also demonstrated the significant impact of transformational leadership on trust in a leader, and its subsequent positive impact on the work engagement of the employees. Furthermore, the results supported a significant serial mediation between transformational leadership, trust, work engagement, and employees’ innovative behavior. The results also showed a significant moderating effect of empowerment on transformational leadership and innovative work behavior. For boosting employees’ innovative work behavior, leaders in the organization should strive to engage them effectively in their work by gaining their trust, which could help them participate in creative activities. This is the key study to investigate the different perspectives of how transformational leadership can stimulate followers’ innovative behavior through trust in the leader and work engagement within the Chinese organizational context.
Rethinking Environmental Bureaucracies in River Chiefs System (RCS) in China: A Critical Literature Study
Authors: Huang Qidong , Xu Jiajun
Published: March 2019

Efforts to understand the political complexities of water governance must include critical hierarchical or bureaucratical perspectives. The River Chiefs System, China’s national mechanism which has evolved from local attempts, values more political control than governance efficiency. Water governance, which is regarded as a political task, is allocated from river chiefs at higher levels to lower levels. The River Chiefs System stipulates that local river chiefs fully mobilize and integrate various technical and administrative forces to achieve environmental goals. However, the strengthening of local authority enables local river chiefs to combat or eliminate state power. Although public involvement in the River Chiefs System is encouraged to some extent, “government-dependent” public participation hardly ensures real public involvement and supervision.
Analyzing Online Car Reviews Using Text Mining
Authors: Kim En-Gir , Chun Se-Hak
Published: March 2019

Consumer reviews on the web have rapidly become an important information source through which consumers can share their experiences and opinions about products and services. It is a form of text-based communication that provides new possibilities and opens vast perspectives in terms of marketing. Reading consumer reviews gives marketers an opportunity to eavesdrop on their own consumers. This paper examines consumer reviews of three different competitive automobile brands and analyzes the advantages and disadvantages of each vehicle using text mining and association rule methods. The data were collected from an online resource for automotive information, Edmunds.com, with a scraping tool “ParseHub” and then processed in R software for statistical computing and graphics. The paper provides detailed insights into the superior and problematic sides of each brand and into consumers’ perceptions of automobiles and highlights differences between satisfied and unsatisfied groups regarding the best and worst features of the brands.
Limiting Factors that Influence the Formation of Producer Groups in the South-East Region of Romania: A Fuzzy Set Qualitative Comparative Analysis (fsQCA)
Authors: Florea Andrei-Mirel , Capatina Alexandru , Radu Riana Iren , Serban (Bacanu) Constanța , Boboc Madalina Georgiana , Stoica (Dinca) Cristina , Munteanu (Pila) Mihaela , Ion (Dumitriu) Iuliana Manuela , Stanciu Silvius
Published: March 2019

The fragmentation of the Agricultural Real Estate in Romania, which is due to the lack of vision regarding the retrocession of the land and to the ineffective measures for reparcelling farmland, manifests by the existence of a record number of about 3422 million farms in Romania, of which about 92% have a utilized agricultural area (UAA) below 5 ha. The Romanian agricultural sector possesses about 30% of the total European farms but contributes only 3% to the total EU agricultural production. The association of local agricultural producers may be an alternative to reparcelling farmland on a short-term basis in order to reduce the fragmentation degree and increase the competitiveness of the national agricultural sector. According to the statistics of the Ministry of Agriculture and Rural Development, 25 active groups of agricultural producers are registered in the South-East Region in 2018, where these associative entities have been recorded to have a low degree of viability. The paper proposes an analysis on the farmers’ motivation regarding the access to/exit from a form of agricultural association and the identification of some alternatives for increasing the viability of the associative forms in the agricultural sector in the South-East of Romania. In this respect, a study was carried out on a sample of 16 entities that gave up their status of producer groups in the analyzed region in 2011–2018. The Fuzzy Set Quantitative Comparative Analysis (fsQCA) Qualitative analysis method was applied, which identified the main influence factors that have led to the disappearance of this associative form. We consider this study relevant for drawing attention to the main obstacles that Romanian farmers face in joining an associative form. The study has shown that mainly the factors directly influenced by government policies have led to the withdrawal of a relatively large number of producers from producer groups in the studied region.
Emotional Intelligence and the Practice of Organized Physical-Sport Activity in Children
Authors: Amado-Alonso Diana , León-del-Barco Benito , Mendo-Lázaro Santiago , Sánchez-Miguel Pedro A. , Iglesias Gallego Damián
Published: March 2019

Aim: Taking into account Bar-On’s postulations about social-emotional intelligence, the aim of the current work is to find out the differences in the five dimensions of this intelligence between children that practice organized sport and those children that do not practice it at the elementary school level. Method: A randomly selected sample of 940 children from elementary schools, ranging in age from 6 to 12 years old, attending different schools from the Autonomous Community of Extremadura (Spain), was used. Results: The results showed that children who practiced organized sport had better abilities at the intrapersonal and interpersonal level, better adaptability and mood states, and greater emotional intelligence than those who did not. The findings regarding gender and age indicated greater values in girls of emotional intelligence, highlighting the interpersonal dimension, as well as mood state scores, whereas younger children showed greater intrapersonal intelligence and less stress management. Moreover, children who practiced for three or more hours per day had a greater ability to cope with stress than those children who practiced for fewer hours a day. Conclusions: To conclude, it is important to promote federative sport practice in elementary education in order to ensure that children learn to better regulate and manage their emotions.