The Feasibility of Using Zero-Emission Electric Boats to Enhance the Techno-Economic Performance of an Ocean-Energy-Supported Coastal Hotel Building

The topics of zero-emission/energy buildings and electric mobility are increasingly being discussed as solutions to alleviate the environmental burden caused by energy consumption and CO2 emissions in both sectors. This study investigates a zero-energy hotel building supported by a hybrid ocean renewable energy system, which interacts with several zero-emission electric boats. Nine different combinations of floating photovoltaics (FPV) and wave energy converters (WEC) are investigated to compensate for their different fluctuations and the stochasticity of energy generation. Using TRNSYS 18 to perform modeling and simulation, a comprehensive techno-economic-environmental analysis of the hybrid system was conducted. The results indicate that when the total annual generation ratios of WEC and FPV are 76% and 24%, respectively, this combination can achieve the best energy weighted matching index (WMI). The WMI reached its maximum (0.703) when 16 boats were sailing at 15 km/h for a distance of 7.5 km. However, increasing the number of boats to 16 does not help improve economic returns or reduce the annual operational equivalent CO2 emission factor of the hybrid system. Depending on the maximum number of electric boats designed for this study, the non-dominated WMI would be limited to 0.654.

Analysis for spatial-temporal matching pattern between water and land resources in Central Asia

Central Asia, the pioneering place of the ‘Belt and Road’, is under the threat of prominent water issues. Based on the Gini coefficient model and the matching index, the amount of the total renewable water resources and the cultivated land area were introduced to evaluate the matching pattern between the water and land resources in Central Asia. The water problem of Kazakhstan, being the most prominent, shows low water resources per unit area with the highest reclamation rate. The matching degree for the upstream countries of the Aral Sea (Kyrgyzstan, Tajikistan) was better than those of the downstream countries (Turkmenistan, Uzbekistan, Kazakhstan). The Gini coefficient in Central Asia was 0.32, smaller than that of the global average value (0.59). The overall water available for use and the matching cultivated land resources was reasonable. Large differences exist in the matching degree in water distribution and utilization among Central Asian countries. The matching index of water and land resources in Central Asia was 1.25, similar to the matching degree estimated from the Gini coefficient model. Moreover, rational measures are suggested to alleviate the issue of water and land resources matching in Central Asia.

Image Recognition of Rapeseed Pests Based on Random Forest Classifier

Rapeseed pests will result in a rapeseed production reduction. The accurate identification of rapeseed pests is the foundation for the optimal opportunity for treatment and the use of pesticide pertinently. Manual recognition is labour-intensive and strong subjective. This paper propsed a image recognition method of rapeseed pests based on the color characteristics. The GrabCut algorithm is adopted to segment the foreground from the image of the pets. The noise with small area is filtered out. The benchmark images is obtained from the minimum enclosing rectangle of the rapeseed pests. Two types of color feature description of pests is adopt, one is the three order color moments of the normalized H/S channel; the other is the cross matching index calculated by the reverse projection of the color histogram. A multi-dimensional vector, which is used to train the random forest classifier, is extracted from the color feature of the benchmark image. The recognition results can be obtained by inputing the color features of the image to be detected to the random forest classifier and training.The experiment showed that the proposed method may identify five kinds of rapeseed accurately such as erythema, cabbage caterpillar, colaphellus bowringii baly, flea beetle and aphid with the recognition rate of 96%.

PILOT STUDY - A New Experiment on Signature Recognition

The complexity in signature recognition problems lies in the fact that a signature usually comprises a small number of handwritten letters that may have limited identifying features and, at the same time, contain natural variations from one signature to the next. Even though it is a frequently encountered problem in forensic sciences, the document examiner’s common method of comparing a questioned signature with a group of control signatures depends upon human perceptual and cognitive processes that are often subjective. To reduce the subjective element in signature comparisons, the authors have experimented with an interactive signature recognition system called the Matching Index (MI) that allows a forensic document examiner (FDE) to utilize his/her expertise to select comparable characteristic features in both questioned and control signatures as well as introduce greater objectivity in the comparison process. An evaluation and assessment of the MI developed by the authors of the questioned signature with the group of control signatures has been implemented by considering numerically assessable features and quantitatively accounting for the information on natural variations manifested in the group of control signatures. Such a comparison provides a more objective expert opinion to present to the court. Successful results of a preliminary test, suggest that the present experiment is potentially promising to provide a more reliable and less subjective approach to signature identification. Purchase Article - $10