ALBERT

Description: Vessel monitoring is one of the most important maritime applications of Synthetic Aperture Radar (SAR) data. Because of the dihedral reflections between the vessel hull and sea surface and the trihedral reflections among superstructures, vessels usually have strong backscattering in SAR images. Furthermore, in high-resolution SAR images, detailed information on vessel structures can be observed, allowing for vessel classification in high-resolution SAR images. This paper focuses on the feature analysis of merchant vessels, including bulk carriers, container ships and oil tankers, in 3 m resolution COSMO-SkyMed stripmap HIMAGE mode images and proposes a method for vessel classification. After preprocessing, a feature vector is estimated by calculating the average value of the kernel density estimation, three structural features and the mean backscattering coefficient. Support vector machine (SVM) classifier is used for the vessel classification, and the results are compared with traditional methods, such as the K-nearest neighbor algorithm (K-NN) and minimum distance classifier (MDC). In situ investigations are conducted during the SAR data acquisition. Corresponding Automatic Identification System (AIS) reports are also obtained as ground truth to evaluate the effectiveness of the classifier. The preliminary results show that the combination of the average value of the kernel density estimation and mean backscattering coefficient has good ability for classifying the three types of vessels. When adding the three structural features, the results slightly improve. The result of the SVM classifier is better than that of K-NN and MDC. However, the SVM requires more time, when the parameters of the kernel are estimated.

Description: Energies, Vol. 10, Pages 1270: A Decision Framework for Electric Vehicle Charging Station Site Selection for Residential Communities under an Intuitionistic Fuzzy Environment: A Case of Beijing Energies doi: 10.3390/en10091270 Authors: Yunna Wu Chao Xie Chuanbo Xu Fang Li Electric vehicle charging station (EVCS) site selection occupies a prominent position in the development of the electric community to solve the hard problem of Electric Vehicle (EV) charging. However, two critical issues have not been solved by the existing research. Firstly, the scope of EVCS site selection only considers the whole city, which deviates from the actual situation. Secondly, the uncertainty and hesitation of decision information is not well expressed. To handle the above problems, this paper builds a comprehensive EVCS site selection decision framework for Residential Communities (EVCSRC) with triangular intuitionistic fuzzy numbers (TIFNs). First of all, the distinctive index system of EVCSRC site selection factors including economy, social, environment, planning and feature portrait of residential communities is established. Then, the TIFNs is utilized for decision makers (DMs) to express the indeterminate information. Furthermore, a fuzzy Vlsekriterijumska Optimizacija I Kompromisno Resenje (Fuzzy-VIKOR) is approach is utilized to rank the alternative EVCSRC sites. Finally, a case of Beijing is studied to demonstrate the validity of the proposed site selection framework. The result shows the EVCSRC site located at Sijiqing community in Haidian district should be selected as the optimal site. This paper presents a feasible and easy-to-use decision-making framework for investors.

Description: Sensors, Vol. 17, Pages 2015: A Hot-Polymer Fiber Fabry–Perot Interferometer Anemometer for Sensing Airflow Sensors doi: 10.3390/s17092015 Authors: Cheng-Ling Lee Kai-Wen Liu Shi-Hong Luo Meng-Shan Wu Chao-Tsung Ma This work proposes the first hot-polymer fiber Fabry–Perot interferometer (HPFFPI) anemometer for sensing airflow. The proposed HPFFPI is based on a single-mode fiber (SMF) endface that is attached to a UV-cured polymer to form an ultracompact fiber Fabry–Perot microcavity. The proposed polymer microcavity was heated using a low-cost chip resistor with a controllable dc driving power to achieve a desired polymer’s steady-state temperature (T) that exceeds the T of the surrounding environment. The polymer is highly sensitive to variations of T with high repeatability. When the hot polymer was cooled by the measured flowing air, the wavelength fringes of its optical spectra shifted. The HPFFPI anemometers have been experimentally evaluated for different cavity lengths and heating power values. Experimental results demonstrate that the proposed HPFFPI responses well in terms of airflow measurement. A high sensitivity of 1.139 nm/(m/s) and a good resolution of 0.0088 m/s over the 0~2.54 m/s range of airflow were achieved with a cavity length of 10 μm and a heating power of 0.402 W.

Description: Materials, Vol. 10, Pages 1332: Solution Growth of Two-Dimensional Bi2Se3 Nanosheets for Two-Color All-Optical Switching Materials doi: 10.3390/ma10111332 Authors: Xinghua Wu Chao Tan Qingkai Wang Yanyan Guo Dianyuan Wang Yongqian Wang Dawei Meng Two-dimensional Bi2Se3 nanosheets with hexagonal shape are synthesized by a solution synthetic route. The Bi2Se3 nanosheets are 120 nm in edge width and 7 nm in thickness. The size of the Bi2Se3 nanosheets can be controlled by choosing different kinds of reducing agents including hydroxylamine and ethylenediamine. Subsequently, we demonstrate a configuration of two-color all-optical switching based on plasma channels effect using the as-synthesized Bi2Se3 nanosheets as an optical media. The signal light can be modulated as two states including dot and ring shape by changing the intensity of control light. The modulated signal light exhibits excellent spatial propagation properties. As a type of interesting optical material, ultrathin two-dimensional Bi2Se3 nanosheets might provide an effective option for photoelectric applications.

Description: Water, Vol. 10, Pages 235: Long-Term Hydropower Generation of Cascade Reservoirs under Future Climate Changes in Jinsha River in Southwest China Water doi: 10.3390/w10020235 Authors: Yu Feng Jianzhong Zhou Li Mo Zhe Yuan Peilun Zhang Jiang Wu Chao Wang Yongqiang Wang In this paper, the impact of future climate changes on long-term hydropower generation (LTHG) of cascade hydropower stations in the lower reaches of the Jinsha River is discussed. Global climate models (GCM) were used to estimate the impacts of future climate changes, the Xinanjiang model (XAJ) was applied to project the streamflow of the hydropower stations, and then gravitational search algorithm (GSA) was adopted to solve the LTHG problem. In case studies, the validation of the XAJ model shows that it perform well in the projection of streamflow in the Jinsha River. Moreover, the future hydropower generation is simulated based on five different GCMs under three climate change scenarios. Finally, the GSA algorithm is used to obtain a set of schemes under the influence of climate change. The results show that future climate changes are expected to have different impact on power generation of cascade reservoirs in the downstream of the Jinsha River when the climate change scenarios are different. These findings can provide decision support for future water resources management of the Jinsha River.

Description: Sustainability, Vol. 10, Pages 142: Engineering Properties of Self-Consolidating Lightweight Aggregate Concrete and Its Application in Prestressed Concrete Members Sustainability doi: 10.3390/su10010142 Authors: How-Ji Chen Kuo-Cheng Wu Chao-Wei Tang Chung-Ho Huang Self-consolidating lightweight aggregate concrete (SCLC) is a highly flowable and lightweight concrete. In this study, the properties of SCLC and prestressed SCLC members were tested and compared with those made of normal-weight self-consolidating concrete (SCC). The test results show that SCLC can be used for prestressed concrete members. The use of lightweight aggregates with a particle density larger than 1100 kg/m3 can avoid the serious segregation of fresh concrete. In addition, the SCLC designed in this study can meet most of the SCC Rank 2 test standards, except for the V-funnel test. The water contained in the lightweight aggregates supplied sustained curing, so the level of drying shrinkage of the SCLC was lower than that of the conventional SCC. However, the level of creep of the SCLC was higher than that of the conventional SCC, because normal-weight aggregates are more able to inhibit the change of the concrete’s volume. On-site test results show that after 180 days of prestressing, the prestress loss was about 5.35–6.83% for the full-size SCLC members, which was smaller than that for the conventional SCC members (about 8.19–9.06% loss).

Description: An effective method to monitor heavy metal stress in crops is of critical importance to assure agricultural production and food security. Phenology, as a sensitive indicator of environmental change, can respond to heavy metal stress in crops and remote sensing is an effective method to detect plant phenological changes. This study focused on identifying the rice phenological differences under varied heavy metal stress using EVI (enhanced vegetation index) time-series, which was obtained from HJ-1A/B CCD images and fitted with asymmetric Gaussian model functions. We extracted three phenological periods using first derivative analysis: the tillering period, heading period, and maturation period; and constructed two kinds of metrics with phenological characteristics: date-intervals and time-integrated EVI, to explore the rice phenological differences under mild and severe stress levels. Results indicated that under severe stress the values of the metrics for presenting rice phenological differences in the experimental areas of heavy metal stress were smaller than the ones under mild stress. This finding represents a new method for monitoring heavy metal contamination through rice phenology.