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North Korea being one of the most degraded forests globally has recently been emphasizing in forest restoration. Monitoring the trend of forest restoration in North Korea has important reference significance for regional environmental management and ecological security. Thus, this study constructed and analyzed a time-series land use land cover (LULC) map to identify the LULC changes (LULCCs) over extensive periods across North Korea and understand the forest change trends. The analysis of LULC used Landsat multi-temporal image and Random Forest algorithm on Google Earth Engine(GEE) from 2001 to 2018 in North Korea. Through the LULCC detection technique and consideration of the cropland change relation with elevation, the forest change in North Korea for 2001–2018 was evaluated. We extended the existing sampling methodology and obtained a higher overall accuracy (98.2% ± 1.6%), with corresponding kappa coefficients (0.959 ± 0.037), and improved the classification accuracy in cropland and forest cover. Through the change detection and spatial analysis, our research shows that the forests in the southern and central regions of North Korea are undergoing restoration. The sampling method we extended in this study can effectively and reliably monitoring the change trend of North Korea forests. It also provides an important reference for the regional environmental management and ecological security in North Korea.

Carbon nitride films were deposited by a twinned microwave electron cyclotron resonance (ECR) plasma source enhanced unbalanced magnetron sputtering system. The results indicate that the structure of the films is sensitive to the nitrogen content. The increase in the nitrogen flow ratio leads to an increase in the sp3 content and an improvement of the tribological properties.

A new 3D image encryption method using integral imaging technology and maximum length cellular automata (MLCA) is proposed in this paper. First, an elemental image (EI) is generated by the integral imaging pickup process. The Wolfram rule is then selected and the state transition matrix, T, is created by MLCA. A random number matrix (RNM) is generated according to the MLCA rule. The generated EI and RNM are compared and pixel values are transitioned. Finally, a basis image is generated by another MLCA rule. The basis image is applied by performing a logic bit exclusive-OR (XOR) operation on the final encrypted image. This method changes the basic image information. Using pixel values to visualize image data gives better encryption results than the previous method. The robustness of the encryption method for lost data, including added noise or cropping attacks, was analyzed and the results of encryption method safety test experiments are presented using histograms.

Abstract. As a well-known NP-hard problem, the Three-Index Assignment Problem (AP3) has attracted lots of research efforts for developing heuristics. However, existing heuristics either obtain less competitive solutions or consume too much running time. In this paper, a new heuristic named Approximate Muscle guided Beam Search (AMBS) is developed to achieve a good trade-off between solution quality and running time. By combining the approximate muscle with beam search, the solution space size can be significantly decreased, thus the time for searching the solution can be sharply reduced. Extensive experimental results on the benchmark indicate that the new algorithm is able to obtain solutions with competitive quality and it can be employed on instances with large-scale. Work of this paper not only proposes a new efficient heuristic, but also provides a promising method to improve the efficiency of beam search.

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