Multi-objective genetic algorithm is much suitable for solving multi-objective optimization problems. By use of Genetic algorithm, the optimization of S-boxes is explored in this paper. Results of the experiments show...Multi-objective genetic algorithm is much suitable for solving multi-objective optimization problems. By use of Genetic algorithm, the optimization of S-boxes is explored in this paper. Results of the experiments show that, with heuristic mutation strategy, the algorithm has high searching efficiency and fast convergence speed. Meanwhile, we also have take the avalanche probability of S-boxes into account, besides nonlinearity and difference uniformity. Under this method, an effective genetic algorithm for 6×6 S-boxes is provided and a number of S-boxes with good cryptographic capability can be obtained.展开更多
The authors consider optimization methods for box constrained variational inequalities. First, the authors study the KKT-conditions problem based on the original problem. A merit function for the KKT-conditions proble...The authors consider optimization methods for box constrained variational inequalities. First, the authors study the KKT-conditions problem based on the original problem. A merit function for the KKT-conditions problem is proposed, and some desirable properties of the merit function are obtained. Through the merit function, the original problem is reformulated as minimization with simple constraints. Then, the authors show that any stationary point of the optimization problem is a solution of the original problem. Finally, a descent algorithm is presented for the optimization problem, and global convergence is shown.展开更多
Hashing and Trie tree data structures are among the preeminent data mining techniques considered for the ideal search. Hashing techniques have the amortized time complexity of O(1). Although in worst case, searching a...Hashing and Trie tree data structures are among the preeminent data mining techniques considered for the ideal search. Hashing techniques have the amortized time complexity of O(1). Although in worst case, searching a hash table can take as much as θ(n) time [1]. On the other hand, Trie tree data structure is also well renowned data structure. The ideal lookup time for searching a string of length m in database of n strings using Trie data structure is O(m) [2]. In the present study, we have proposed a novel Prime Box parallel search algorithm for searching a string of length m in a dictionary of dynamically increasing size, with a worst case search time complexity of O(log2m). We have exploited parallel techniques over this novel algorithm to achieve this search time complexity. Also this prime Box search is independent of the total words present in the dictionary, which makes it more suitable for dynamic dictionaries with increasing size.展开更多
随着养宠需求增长,现有智能猫砂盆在猫咪健康监测方面存在局限,为此设计一款智能猫砂盆健康监测系统,以解决这些问题。系统以Raspberry Pi 4B为主控芯片,集成空气质量监测、自动清理、称重等多个硬件模块,运用YOLOv9算法进行排泄物识别...随着养宠需求增长,现有智能猫砂盆在猫咪健康监测方面存在局限,为此设计一款智能猫砂盆健康监测系统,以解决这些问题。系统以Raspberry Pi 4B为主控芯片,集成空气质量监测、自动清理、称重等多个硬件模块,运用YOLOv9算法进行排泄物识别,并通过手机App实现数据查看与远程控制。经测试,该系统的空气质量监测系统准确性极高,与手动测量相比,平均误差小于5%,在检测到氨气浓度超标后,平均响应时间仅1.5 s,自动启动清理程序后,氨气浓度平均降低75%。自动清理功能效率测试显示,智能猫砂盆清理频率比常规猫砂盆高50%,且清理后清洁度更高,90%的猫表现出对其明显偏好。设计的系统实现了对猫咪健康状况的精准监测与猫砂盆的智能管理,为宠物主人提供了便利,提升了对猫咪健康的关注度。后续仍有优化空间,如优化图像识别算法、拓展空气质量监测种类、增加App健康数据分析功能等。展开更多
基金Supported by the National Natural Science Foundation of China (60473012)
摘要Multi-objective genetic algorithm is much suitable for solving multi-objective optimization problems. By use of Genetic algorithm, the optimization of S-boxes is explored in this paper. Results of the experiments show that, with heuristic mutation strategy, the algorithm has high searching efficiency and fast convergence speed. Meanwhile, we also have take the avalanche probability of S-boxes into account, besides nonlinearity and difference uniformity. Under this method, an effective genetic algorithm for 6×6 S-boxes is provided and a number of S-boxes with good cryptographic capability can be obtained.
基金the National Natural Science Foundation of China(No.19971002)
摘要The authors consider optimization methods for box constrained variational inequalities. First, the authors study the KKT-conditions problem based on the original problem. A merit function for the KKT-conditions problem is proposed, and some desirable properties of the merit function are obtained. Through the merit function, the original problem is reformulated as minimization with simple constraints. Then, the authors show that any stationary point of the optimization problem is a solution of the original problem. Finally, a descent algorithm is presented for the optimization problem, and global convergence is shown.
摘要Hashing and Trie tree data structures are among the preeminent data mining techniques considered for the ideal search. Hashing techniques have the amortized time complexity of O(1). Although in worst case, searching a hash table can take as much as θ(n) time [1]. On the other hand, Trie tree data structure is also well renowned data structure. The ideal lookup time for searching a string of length m in database of n strings using Trie data structure is O(m) [2]. In the present study, we have proposed a novel Prime Box parallel search algorithm for searching a string of length m in a dictionary of dynamically increasing size, with a worst case search time complexity of O(log2m). We have exploited parallel techniques over this novel algorithm to achieve this search time complexity. Also this prime Box search is independent of the total words present in the dictionary, which makes it more suitable for dynamic dictionaries with increasing size.
摘要随着养宠需求增长,现有智能猫砂盆在猫咪健康监测方面存在局限,为此设计一款智能猫砂盆健康监测系统,以解决这些问题。系统以Raspberry Pi 4B为主控芯片,集成空气质量监测、自动清理、称重等多个硬件模块,运用YOLOv9算法进行排泄物识别,并通过手机App实现数据查看与远程控制。经测试,该系统的空气质量监测系统准确性极高,与手动测量相比,平均误差小于5%,在检测到氨气浓度超标后,平均响应时间仅1.5 s,自动启动清理程序后,氨气浓度平均降低75%。自动清理功能效率测试显示,智能猫砂盆清理频率比常规猫砂盆高50%,且清理后清洁度更高,90%的猫表现出对其明显偏好。设计的系统实现了对猫咪健康状况的精准监测与猫砂盆的智能管理,为宠物主人提供了便利,提升了对猫咪健康的关注度。后续仍有优化空间,如优化图像识别算法、拓展空气质量监测种类、增加App健康数据分析功能等。