Dynamic Iteration Method: New Approach to Cultural Events Management

This article provides project managers, the cultural events organizers, a new approach to plan preparation and to the monitoring of events realization. The Dynamic Iteration Method introduced in this article is based on the system dynamic modelling and on the principles of project iterative development. The plan model and the reality model are structurally similar; they differ in values of exogenous variables. The new approach enables to easily monitor the real project course in close connection with the plan and to take timely controlling steps. The effects resulting from the manager´s decisionmaking process are compared with the plan in regular iterations. The method thus reminds of a traveller whose route is adjusted by a GPS navigation system.

An Improved Louvain Algorithm for Community Detection

Social network analysis has important research significance in sociology, business analysis, public security, and other fields. The traditional Louvain algorithm is a fast community detection algorithm with reliable results. The scale of complex networks is expanding larger all the time, and the efficiency of the Louvain algorithm will become lower. To improve the detection efficiency of large-scale networks, an improved Fast Louvain algorithm is proposed. The algorithm optimizes the iterative logic from the cyclic iteration to dynamic iteration, which speeds up the convergence speed and splits the local tree structure in the network. The split network is divided iteratively, then the tree structure is added to the partition results, and the results are optimized to reduce the computation. It has higher community aggregation, and the effect of community detection is improved. Through the experimental test of several groups of data, the Fast Louvain algorithm is superior to the traditional Louvain algorithm in partition effect and operation efficiency.

The Advanced Multilevel Predictor-Corrector Quasi-Static Method for Pin-Resolved Neutron Kinetics Simulation

The Advanced Multilevel Predictor-Corrector Quasi-static Method (AML-PCQM) is proposed in this work. The four computational levels, including transport, Multi-Group (MG) Coarse Mesh Finite Difference (CMFD), One-Group (1G) CMFD, and Exact Point-Kinetics Equation (EPKE), are coupled with a new dynamic iteration strategy. In each coupling algorithm, the original Transient Fixed Source Problem (TFSP) is solved in the predictor process using coarse time step, and then the flux distribution is factorized to the functions of amplitude and shape in the next corrector process. Finally, multiple fine time steps are used to adjust the predicted solution. Two heterogeneous single assembly problems with the prompt control rod withdrawal event are used to verify the AML-PCQM scheme’s accuracy and efficiency. The numerical results obtained by different cases are compared and analyzed. The final results indicate that the AML-PCQM performs the remarkable advantages of efficiency and accuracy with the reference cases.

A Combination of Block-Based Chaos with Dynamic Iteration Pattern and Stream Cipher for Color Image Encryption

This research proposes an encryption method on images using a combination of chaotic methods, streams, and hash functions. SHA-1 is used as a hash function to encrypt key inputs to be more secure and can produce more dynamic keys at chaotic and stream encryption stages. Chaos encryption is done by dividing the image into small blocks where each encrypted block differs based on a dynamic key pattern based on chaotic keys. At the last stage, all blocks are made as whole images again to be encrypted by the stream method. Tests carried out on standard RGB images and Indonesian batik images. Encryption quality measurements using entropy, histogram analysis, UACI, NPCR, SSIM, PSNR, and the avalanche effect. Based on the results of trials the proposed method is proven to be resistant to various attacks such as statistics as evidenced by the average entropy value of 7.9996, avalanche effect value of 50.0366 and a relatively uniform histogram, while differential attack as evidenced by the value of UACI 33.5716 and NPCR 99.6082 where this value is very close to ideal. Also visually the results of the encryption look very chaotic and very different from the original image, which is evidenced by the value of PSNR 8.0191 and SSIM 0.0081. The decryption process can also be done perfectly wherein the resulting infinity value on PSNR and value 1 on SSIM.