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Objectives: Three dimensional buffer analysis is a spatial analysis function widely used in geographic information systems, which is of great significance in underwater submersible terrain matching navigation, submarine engineering construction planning, submarine pollution source diffusion analysis and other bathymetric research fields. The traditional buffer surface construction algorithm has limitations in the application of triangulated irregular network digital depth model (TIN-DDM) model accuracy and modeling efficiency. Therefore, taking the rolling ball acceleration optimization model with controllable accuracy threshold as the analysis object, we propose a fast TIN-DDM buffer surface construction algorithm based on the efficient determination of key sampling points. Methods: The main research contents are as follows: (1) Based on the spatial distribution characteristic analysis of alternative point sets, through the numerical convergence analysis of the critical rolling ball radius, the trial iteration strategy of critical rolling sphere radius is designed, then a new criterion for determining key sampling points is given. (2) The spatial data block index modeling is applied to the rapid positioning of adjacent alternative points, and an efficient judgment model of key sampling points for rapid positioning of spatial index is established. Results: From the statistical results of the key data link list parameters and the actual buffer surface construction images, the proposed method can be used to build the buffer surface, and is consistent with the construction accuracy of the rolling ball accelerated optimization model. From the results of buffer surface construction time consuming of different TIN-DDM water depth data, the time consuming of this method is obviously better than that of the rolling ball accelerated optimization model. Conclusions: The experimental results show that in the face of massive TIN-DDM data, the proposed algorithm can effectively improve the construction efficiency of buffer surface on the basis of ensuring the construction accuracy of buffer surface, and reduce the time complexity of overall buffer surface construction. [ABSTRACT FROM AUTHOR]

This paper proposed an aggregate signature scheme based on the SM9 algorithm to address the issue of excessive storage space occupied by the signatures of n messages generated by the conventional SM9 signature scheme. This scheme reduced the time cost of verifying multiple signatures compared to the original SM9 scheme, with a space cost of about 66.7% of the original SM9 scheme. Furthermore, the scheme introduced a locally verifiable approach based on the SM9 aggregate signature to tackle the problem where validators need only verify the correctness of specific messages when verifying signatures in current aggregate signature algorithms but still require knowledge of the complete message list. For the aggregated signatures S of a messages generated by a single user, the signer generated verification tags for a specific message m, enabling the verifier to verify the correctness of the message's signature without knowledge of the complete message list. Theoretical and experimental analysis confirm that the proposed scheme achieves a time complexity of O(1) for verifying specific messages given an aggregated signature. [ABSTRACT FROM AUTHOR]

Aiming at the floorplanning problem with only hard modules, it is usually constructed as a combinatorial optimization model, but the time cost of solving process is high. In order to improve the solving efficiency, this paper proposed a floorplanning algorithm based on non-smooth analytic mathematical programming. Based on the coordinate representation of modules, this paper established a non-smooth mathematical programming model, which was a generalization of the optimization models corresponding to various optimization stages of different cases that were solved by the conjugate sub-gradient algorithm (CSA). Aiming at the fixed-outline floorplanning problem, this paper achieved wirelength optimization under fixed-outline constraint through the general framework consisted of three stages: global floorplanning, legalization and local optimization. To address the case without fixed-outline constraint, this paper proposed a conjugate sub-gradient algorithm with golden section strategy (CSA_GSS). The algorithm adopted golden section strategy to reduce the area of the fixed-outline and to achieve the dual effect of both area and wirelength optimization. Compared with floorplanning algorithm based on B-tree on GSRC test circuit, the proposed algorithm had advantages in terms of wirelength and time for large-scale circuits. Experimental results show that the algorithm can obtain better wirelength with lower time complexity. [ABSTRACT FROM AUTHOR]

Copyright of Systems Engineering & Electronics is the property of Journal of Systems Engineering & Electronics Editorial Department and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Journal of Chongqing University of Posts & Telecommunications (Natural Science Edition) is the property of Chongqing University of Posts & Telecommunications and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Journal of Beijing University of Civil Engineering & Architecture is the property of Journal of Beijing University of Civil Engineering & Architecture Editorial Office and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

[Purpose] To enable conflict avoidance operation planning for support vehicles in complex environments, a dynamic priority classification method is proposed. [Method] This method prioritizes conflict avoidance based on levels of operation efficiency and risk. Additionally, a conflict avoidance operation planning model were established, along with a two-stage algorithm for global path optimization. A low time complexity conflict detection method was also proposed to ensure accuracy in solving large-scale complex problems quickly. [Result] Compared to the fixed-priority-based two-stage algorithm, the proposed approach improves conflict point reduction by 7.6% and reduces the vehicle-aircraft conflict ratio by 7.5%. [Conclusion] The proposed method meets the requirements of ensuring differentiated vehicle operation, and realizes the function of conflict avoidance path planning in a mixed operation environment of vehicles and aircraft. [ABSTRACT FROM AUTHOR]

Copyright of Automobile Technology is the property of Automobile Technology Editorial Office and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

[Objectives] Identifying crops and weeds are crucial aspects of advancing intelligent and automated weeding. This article aimed to improve the accuracy of crop and weed identification, to enhance the real-time performance of detection models, and to enhance robustness. [Methods] Focusing on maize crops and their corresponding weeds in the leaf age range of 3-8 leaves, this research endeavored to devise a detection method for maize seedlings and associated grasses. The seedling detection method leveraged an improved real-time end-to-end object detection with transformers (RT-DETR) for maize and weed detection in field conditions. The novel concept of replacing large-scale deep convolution with small-scale convolution equivalence within RT-DETR was introduced, reducing training complexity and inference time while maintaining detection accuracy. Furthermore, a self-attention mechanism with contextual information was integrated to enhance target attention and improve small target detection. Additionally, a combined image enhancement strategy was employed to enhance model accuracy and generalization. [Results]The improved model effectively distinguished weeds from crops in complex field scenarios, achieving an average detection accuracy of 90.11%. In the inference stage, each image took 33.67 ms for processing, with a model size of 44.86 MB. Compared with the mainstream target detection model, the improved model had higher overall accuracy and fast speed. [Conclusions]The proposed method had excellent overall detection performance for corn seedlings and associated weeds, which could improve the accuracy and efficiency of weed identification. [ABSTRACT FROM AUTHOR]

It is well recognized that the flexibility of state machine design brings developers high efficiency and convenience, but it also introduces three typical problems: the output errors caused by the state logic and timing dependence, the huge load of computing caused by the historical data caching, and the uncontrollable outputs caused by the close-coupling between states. The problems still exist in software detail design and coding. Without changing state machines' functionalities and following principles of constraint conditions, the paper carries out an equivalent transformation of state machine from both time-complexity and cyclomatic complexity dimensions. The transformation forms a general process of optimization, involves merging or splitting the original state and decision condition, recombining the split or merged state according to the metamodel definition, and adding the transition condition. An optimization algorithm is proposed for three typical problems, the algorithm is used to test the state machine before and after optimization, and the feasibility of the algorithm is verified from the time-complexity and cyclomatic complexity. The practical meaning of the study is that it provides an applicable method for software detail design and refactoring especially in the area of real-time control systems or safety critical systems. [ABSTRACT FROM AUTHOR]

Aiming at the naturalness and structural complexity of multivariate time series (MTS) data as well as the inability of existing algorithms to accurately identify clusters of high-dimensional time series data, the shape extraction multivariate time series clustering algorithm C-Shape under compactness constraints is proposed. Firstly, C-Shape performs largest triangle three buckets processing on the complex MTS to achieve the purpose of using fewer data while keeping the original shape unchanged. The raw data and the processed data are then selected to calculate the compactness between them to ensure the reduced spatial dimensionality is reasonable. Next, new cluster centers are obtained by using shape extraction while effectively preserving the shape integrity of the data, and the final cluster is formed by iteration. C-Shape can avoid the difficulty of grasping the low dimensional spatial dimensionality of the traditional down-sampling algorithm by fully taking into account the similarity between the shapes of the processed data and raw data. To validate its performance, C-Shape is tested with two classical and seven excellent time series clustering algorithms presented in recent years on the eight normal and four imbalanced MTS datasets with dimensions ranging from tens to thousands, respectively. Experimental results demonstrate all C-Shape clustering capabilities outperform those of the nine baseline algorithms, with an average improvement of 16.33% in Rand index and an average improvement of 69.71% in time performance. Thus C-Shape is an accurate and efficient multivariate time series clustering algorithm. [ABSTRACT FROM AUTHOR]

Copyright of Electric Drive is the property of Electric Drive Editorial Office and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

The existing RDH methods usually determine the modification model and the embedding parameters adaptively according to the given image, in order to optimize the performance. However, the existing optimization manners will lead to the high computational complexity and the unacceptable time cost. This paper proposed a modularized RDH method for JPEG images, to improve the efficiency of the adaptive optimization. The candidate embedding solutions were defined as the existing parameter sets which were verified effective under different cases. Therefore, it generated a so-called universal modification model set that was suitable for different images. Each modification model was defined as the optimal embedding points for the multiple histograms modification mechanism. During the embedding, the appropriate modification model was adaptively selected from the pre-set solution set, based on the given image. Compared with five related works on the USC-SIPI database, the peak signal-to-noise ratio(PSNR) of the proposed method can be improved 0.03~1.81 dB. In the terms of the file size increase, the results of the proposed method can reduce 12.4% and 5.1% respectively, compared with the two typical methods. The experimental results demonstrate that, the proposed method outperforms the mainstream classic methods, in the terms of the quality of the marked image and the file size preservation. Compared with the state-of-the-arts, the proposed method can achieve the similar adaptive performance, while keeping a low computational complexity. [ABSTRACT FROM AUTHOR]

Mobile edge computing (MEC) provides users with low latency and low energy consumption services by unloading computing tasks to MEC servers, overcoming the shortcomings of traditional cloud computing. In mobile edge computing, how to make unloading decision is one of the key technologies to provide low latency and low energy consumption services. In addition, due to the limited bandwidth resources of wireless channel, unreasonable bandwidth allocation will increase the energy consumption and delay of user devices. Therefore, how to reasonably allocate resource is also the key to the implementation of edge computing. To jointly optimize delay, energy consumption, and computational resources, this paper proposes a multi-channel search algorithm based on Monte Carlo tree search (MCS-MCTS). Firstly, with the cost of delay and energy consumption as the optimization objective, the decision on computing resource allocation and transmission power modeling is modeled as a convex optimization problem. The optimal transmission power allocation problem is solved by using gradient descent method, and the optimal computational resource allocation problem is solved by means of Lagrange multiplier method and Karush-Kuhn-Tucker (KKT) condition. Subsequently, the MCS-MCTS algorithm is used to deal with the binary unloading decision problem. Besides, the simulated annealing algorithm is introduced to avoid the search results falling into local optimum. The numerical results show that MCS-MCTS algorithm can obtain near optimal unloading decision and resource allocation decision in linear coherent time. Compared with existing heuristic search algorithms, this algorithm can achieve near optimal performance while reducing time complexity and improving system energy efficiency. [ABSTRACT FROM AUTHOR]

Copyright of Application Research of Computers / Jisuanji Yingyong Yanjiu is the property of Application Research of Computers Edition and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Journal of Computer Engineering & Applications is the property of Beijing Journal of Computer Engineering & Applications Journal Co Ltd. and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Reachability queries of directed graphs are fundamental when studying various network problems, such as querying whether two persons follow each other in a social network. However, with the increasing size of networks, traditional algorithms have become unacceptable due to their huge time or space complexity. Therefore, it is necessary to use a suitable reachability algorithm according to the structural characteristics of the network. A sparse graph consists of several directed spanning trees with a small number of non-tree edges. The GRKPL (graph reachability indexing via key points labeling) algorithm splits the reachability problem in sparse graphs into two parts: the tree reachability problem and the impact of adding non-tree edges. The first part is solved by the interval labeling method, and the second part is solved by constructing a key point set, which transforms all the reachability queries in the original graph into queries in the key point set. The key point set includes all nodes covered by nontree edges and the lowest common ancestors between adjacent nodes after these nodes are sorted in the preorder traversal order. And it is proven that the size of the key point set is of the same order of magnitude as the size of the non-tree edges in the original graph. Finally, GRKPL is tested on ten small- and medium-scale and four large-scale realistic datasets. GRKPL performs well on small- and medium-scale datasets, with an average 49.8% reduction in query processing time and 65.1% reduction in space occupation compared to other algorithms. [ABSTRACT FROM AUTHOR]

The max independent set problem is a well-known NP problem and has applications in many scenarios. Traditional exact algorithms need exponential time complexity to solve the max independent set problem. In order to solve the max independent set problem more efficiently, proposes a quantum circuit solution based on the quantum approximate optimization algorithm. In this scheme, derives the Hamiltonian expression of the max independent set problem from the mathematical model of the max independent set, designes the quantum circuit based on the quantum approximation optimization algorithm. Using the COBYLA classical optimization algorithm to optimize the parameters in the parameter quantum gate, and using the quantum development framework Qiskit provided by IBM to conduct simulation experiments. Simulation results show that the solution of the max independent set problem can be obtained in polynomial time with high probability using the quantum approximate optimization algorithm, achieving an exponential speedup. Quantum approximate optimization algorithm is feasible and effective for solving the max independent set problem. [ABSTRACT FROM AUTHOR]

Copyright of Systems Engineering & Electronics is the property of Journal of Systems Engineering & Electronics Editorial Department and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

In the natural computation method, to solve the optimization problem of high-dimensional data, the population size needs to be increased to obtain higher accuracy, but at the same time, the time complexity is relatively large. If the population size is reduced, the algorithm will fall into local optimization due to the lack of population diversity. In order to solve the problems such as difficult to balance population size, slow convergence rate and easy to fall into local optimum in optimization process, a natural calculation method based on Multiple Competitive Elimination (MCE) strategy is proposed, which is suitable for all kinds of optimization algorithms. It does not depend on the specific steps of algorithm evolution and has universality. First, the original solution space was divided into two types of large Spaces with competitive relations, and each type of large space was decomposed into N-dim small space. Then, two different elimination methods of reverse learning and mixed mutation were carried out respectively in the two types of large Spaces to eliminate the poor individuals. Finally, some better individuals in N-dim small space were selected to carry out competitive exchange across the two types of large Spaces to maintain the diversity of the whole population. Thus, the convergence speed and accuracy of the algorithm are improved. The proposed strategy is applied to particle swarm optimization and genetic algorithm respectively, and compared with standard particle swarm optimization, genetic algorithm and current advanced improved swarm intelligence optimization algorithms, the performance is verified by high-dimensional classical test function. The experimental results show that the improved algorithm of multiple competition elimination has better optimization ability than other comparison algorithms and has universality. [ABSTRACT FROM AUTHOR]

Copyright of Systems Engineering & Electronics is the property of Journal of Systems Engineering & Electronics Editorial Department and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Journal of Computer Engineering & Applications is the property of Beijing Journal of Computer Engineering & Applications Journal Co Ltd. and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Journal of Cryptologic Research (2095-7025) is the property of Editorial Board of Journal of Cryptologic Research and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Machine Tool & Hydraulics is the property of Guangzhou Mechanical Engineering Research Institute (GMERI) and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

The SubSieve algorithm is an efficient algorithm for solving the shortest vector problem (SVP) on lattices which uses a few calls to the GaussSieve algorithm on the (n -- d)-dimensional projected sublattice to solve the SVP on an n-dimensional lattice, where d is the free dimension. The idea of dimensional reduction of the SubSieve algorithm effectively reduces the time complexity of the sieve and narrows the gap in the running efficiency with the enumeration algorithm. This paper briefly reviews the main idea and the mechanisms of the GaussSieve algorithm and the SubSieve algorithm. Subsequently, two methods are proposed to improve the SubSieve algorithm. First, by adjusting the algorithm parameters of the GaussSieve algorithm to change its output, the free dimension d of the SubSieve algorithm can be increased, and the time complexity is reduced. Second, by adding filters to the GaussSieve algorithm which is the most important subroutine of the SubSieve algorithm, the vectors can be sieved more quickly when the list is updated. By this way, the quadratic search can be reduced in the GaussSieve algorithm to a sub-quadratic search process and the runtime is reduced. Finally, the above two methods are applied to optimize the SubSieve algorithm, forming the Filtered α-SubSieve algorithm. According to the experimental results, the above two methods do improve the efficiency of the initial SubSieve algorithm. On random lattices in dimension 70-86, compared with that of the initial SubSieve algorithm, the efficiency of the Filtered α-SubSieve algorithm can be improved by up to 58:8% and 41:7% on average. [ABSTRACT FROM AUTHOR]

Both PFP and SLIM are ultra-lightweight block ciphers having Feistel structure, which have good performance both in software and hardware, especially in resource-constrained environments. So far, the integral analysis of the PFP cipher and SLIM cipher has not yet been conducted thoroughly. In this paper, a mixed integer linear programming (MILP) model is constructed by analyzing the structural characteristics of PFP cipher and SLIM cipher, and combining with the automatic search method of bit division property. The Gurobi optimizer is used to establish the model to determine whether there is an r-round integral distinguisher, and the integral distinguisher is selected to carry out key recovery attack on the cipher. The results show that a 11-round integral distinguisher of the PFP cipher is found, and a 12-round key recovery attack is carried out by using 10-round integral distinguisher to extend 2 rounds backward. The data complexity is 262:39 chosen plaintext, time complexity is 263:12 of 12round encryption, and storage complexity is 240. A 10-round integral distinguisher of SLIM cipher is also found, and a 9-round integral distinguisher is selected to carry out 12-round key recovery attack. The data complexity is 231:81 of chosen plaintext, the time complexity is 262:42 of 12-round encryption, and the storage complexity is 240. [ABSTRACT FROM AUTHOR]

At present, the problem of r-collision in the unbalanced environment has not yet been effectively solved. In this paper, a new efficient algorithm is proposed to find an unbalanced r-collision of r different and unbalanced functions. The new algorithm adopts the techniques from the previous 3-collision algorithm, the parallel collision search (PCS) algorithm and the unbalanced meet-in-themiddle (UMitM) attack. The attack process of the new algorithm can be described as follows: First, the attacker divides r functions into left and right sets. When r is even, the corresponding left and right sets are {fl1, fl2, ???, flr/2} and {ft1, ft2, ???, ftr/2} respectively, and it is necessary to find collisions between two unbalanced functions fli and fti (for 1 ≤ ⌊r/2⌋) at corresponding positions in the left and right sets. Take the i-th function for example, the attacker adopts the PCS algorithm to collect 2mi collisions of two unbalanced functions fli and fti. Note that the attacker needs to repeat the collectioncollision operation for ⌊r/2⌋ pairs of positions in the left and right sets. If r is odd, the attacker also needs to collect 2m0 images of the left function. After the collision-collection phase, the attacker adopts the MitM attack to find a r-collision between these r -- ⌊r/2⌋ lists. The main results of the new algorithm are: (1) The time complexity of the new algorithm is determined by the memory and the chosen grouping methods, which is different from the previous r-collision algorithm. (2) With sufficient storage, the time complexity formula of the new r-collision algorithm is as follows: when r = 2k, the time complexity is .... When r = 2k + 1, the time complexity is ..., where Rlj is the implementation cost of the function with the highest implementation cost in the left set, Rc is the implementation cost of the unpaired function, and Rtx(1 ≤ x ≤ (r -- 1)/2) is the implementation cost of each function in the right set. The attacker first needs to find min (&#931x=1r/2 log2 Rtx/r + log2rlj/2) for r = 2k (or min (log2 Rc + Σx=1(r-1)/2 log 2 Rtx/r + (r-1)log2 Rij/2r) for r = 2k + 1) so as to find the best grouping method and the best time complexity in this case. (3) With limited storage, the attacker cannot find the best time complexity without exhausting the time complexity of all grouping methods. [ABSTRACT FROM AUTHOR]

MIBS is a lightweight block cipher proposed by Izadi et al. in 2009, which has two variants: MIBS-64 and MIBS-80. In 2019, Chen et al. performed a key recovery attack on 15-round MIBS-64 based on a 13-round Rectangle distinguisher, and the time, data, and memory complexity (T;D;M) of the attack equal (259; 245; 245). Based on Chen et al.'s attack, this paper further investigates the ability of MIBS-64 to resist Rectangle and Boomerang attacks. By exploiting the fact that differences propagate through a linear layer deterministically, the time complexity of the 15-round Rectangle attack can be reduced from 259 to 247. In order to make a deeper analysis of MIBS, this paper adopts the new key recovery algorithms recently proposed by Song et al. for Boomerang attacks, and then constructs key recovery attacks on 15 and 16 rounds of MIBS whose complexities are (238; 237; 236) and (260; 260; 230) respectively. The results of this paper updates the cryptanalysis results of MIBS-64 under Boomerang and Rectangle attacks, proposes the first 16-round attack on MIBS-64. [ABSTRACT FROM AUTHOR]

The AES is one of the most widely used block ciphers in the world, the 3D block cipher is a 3-dimensional AES-like cipher proposed at CANS 2008, and the TANGRAM block cipher is an awardwinning algorithm of the recent National Cryptographic Algorithm Design Competition in China. The yoyo tricks is a powerful cryptanalysis technique based on zero difference, and its main idea is based on whether a plaintext pair and a pair generated by this plaintext pair share the same property after several rounds of encryption. This paper uses yoyo tricks to make an attack on 6-round AES with restricted ciphertexts, reducing the best previously published time complexity by 25:6 in the context of yoyo tricks. Second, the yoyo tricks are extended to n-tuple (n ≥ 3) and relations between the yoyo tricks and related differentials are established, more specifically, the related differentials can be represented by yoyo tricks, and 3-tuple yoyo tricks are used to launch a key recovery attack on 11-round 3D. Finally, the early abort technique is used to the exchange attack, where 2126 chosen plaintexts are used to make a distinguishing attack on 25-round TANGRAM with a 128-bit block size (denoted as TANGRAM-128), which is the first 25-round distinguisher for TANGRAM-128. [ABSTRACT FROM AUTHOR]

Copyright of Journal of South China Normal University (Natural Science Edition) / Huanan Shifan Daxue Xuebao (Ziran Kexue Ban) is the property of Journal of South China Normal University (Natural Science Edition) Editorial Office and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

The new trend to design a data center network is to deploy switches and two-port servers on the nodes and edges in an interconnection network, the logic graph of which can be abstracted as a compound graph. Node-independent spanning tree (NIST) is an important structure that can be used to design reliable communication protocols, fault-tolerant broadcasting, and secure message distribution, IP fast rerouting, etc in data center networks. Given a compound graph G (Kn), this paper firstly showed that if the diameter of G was d, then the diameter of G( Kn) was either 2d or 2d + 1. Supposed that there were n NIST rooted at an arbitrary node in an n-regular n-node-connected interconnection network G, this paper presented a unified method to construct n NIST in G (Kn) by proposing an efficient algorithm with time complexity 0 (N), where N was the number of nodes . Ana-lysis of NIST on compound graph Qn(Kn) shows that the maximal height is only the diameter plus 3 . Also, simulation experiments on the augmented based on data center networks show the correctness from another aspect. [ABSTRACT FROM AUTHOR]

While conducting bandwidth allocation over elastic optical data center network EODCN, it is important to balance the revenue of cloud service providers and the connection performance of tenants. This paper proposed a bandwidth allocation algorithms to effectively assign optical bandwidth for multiple connection requests based on subcarriers so as to maximize revenue. Firstly, on the basis of a revenue model and a concept of virtual subcarrier, it constructed an integer linear programming formulation of the studied bandwidth allocation problem. Then, it proposed a dynamic programming-based algorithm and a heuristics-based algorithm correspondingly, which respectively focus on achieving maximum net revenue and gaining better time efficiency. Finally, it conducted simulations to validate the efficiency of the designed algorithms. The simulation results show that both of the proposed algorithms are superior to the existed methods in system revenue obtaining in bandwidth allocation over EODCN. [ABSTRACT FROM AUTHOR]

Copyright of Journal of Guangxi Normal University - Natural Science Edition is the property of Gai Kan Bian Wei Hui and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Engineering Mechanics / Gongcheng Lixue is the property of Engineering Mechanics Editorial Department and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Engineering Mechanics / Gongcheng Lixue is the property of Engineering Mechanics Editorial Department and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Concerning the problems of high time complexity, large storage space requirements and low accuracy when traditional clustering algorithm cluster stream data, this paper proposed a kind of stream data clustering algorithm based on differential sampling. First, it used the differential sampling method sampled stream data, and used sample points to construct kernel matrix. Then it used kernel fuzzy C-means clustering algorithm clustered the data points in the kernel matrix, obtained a marked sample kernel matrix. Finally, it used the marked kernel matrix divided the stream data. Meanwhile, this paper adopted the fading cluster mechanism to update kernel matrix in real time. Experimental results show that compared with the traditional clustering algorithm, the proposed algorithm achieves lower time complexity, real-time clustering at the same time, gets the ideal clustering result. [ABSTRACT FROM AUTHOR]

A study on the structure of ARIA cipher is presented. A new 4-round distinguishing property for the meet-in-the-middle attack on ARIA cipher is presented by making use of the multiset and the truncated differential char-acteristic. The new distinguishing property improves the meet-in-the-middle attack on 7 rounds of ARIA-192 cipher ef-fectively by reducing the 30 parameters to 16. The new attack requires a precomputation complexity of 2135.3and a time complexity of about 2123.

Copyright of Journal of Image & Graphics is the property of Editorial Office of Journal of Image & Graphics and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Journal of Guangdong University of Technology is the property of Journal of Guangdong University of Technology and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

A new 34-round related-key rectangle distinguisher was constructed by exploiting the properties of the round transform of SHACAL-2. Moreover, two new relate-key rectangle attacks on 40-round and 42-round reduced SHACAL-2 were presented by using both the distinguisher and a technique of key-byte guessing. It is shown that related-key rectan- gle attacks with only 2 related keys on 40-round and 42-round reduced SHACAL-2 all require data complexity of about 2235 chosen plaintexts and time complexity of about 2432.6 encryptions on 40-round reduced SHACAL-2, and 2472.6 en- cryptions on 42-round reduced SHACAL-2, respectively. The presented results are better than previous published crypt- analytic results on reduced SHACAL-2 in terms of both the data complexity and the time complexity.

The decision formula based sub-interval elimination algorithm has two major problems to be solved. One is the inconsistency with the decision table results, the other is its difficulty in dealing with the massive sub-interval problems. To solve these problems, this paper proposed a new sub-interval elimination algorithm based on dynamic programming. This algorithm took advantage of dynamic programming superior property in multi-stage decision problem. Based on dynamic programming, it divided the sub-interval elimination problem into two parts： reasonable judgment and new interval generation, which could use dynamic programming to solve. This paper also proved the reasonableness of this sub-problem division, and analyzed the time and space complexity. Meanwhile, in order to test the performance of this new algorithm, this paper made comparisons in both theoretical and experimental aspects. The simulation results show that the proposed method is able to reduce the algorithm's time complexity, overcome the problem of increasing the size of the sub-interval, and improve the flexibility and speed of the algorithm. [ABSTRACT FROM AUTHOR]

Copyright of Journal of Image & Graphics is the property of Editorial Office of Journal of Image & Graphics and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

The cluster-cluster aggregation (CCA) model bridges the study of colloid aggregation by computer simulation and laboratory experiment. Two distinct and limiting regimes of irreversible colloid aggregation have been identified by computer simulation with the CCA model. One regime is diffusion-limited cluster aggregation (DLCA) corresponding to the rapid colloid aggregation. The other is reaction-limited cluster aggregation (RLCA) corresponding to the slow colloid aggregation. The simulations of the two regimes are both start with N non-overlapping identical particles distributed randomly in a cubic box with side-lengths of L. A three dimensional array, hypothetically named Cube[L][L][L], was usually used to represent the cubic box. Each particle in the cubic box occupies an element of the three dimensional array and are labeled with a different integer. When particles and/or clusters collide and aggregate, all particles in the resulting cluster are modified with the same label (one of them). The progression of Brownian movement and aggregation are realized by updating the labels of the corresponding array elements. However, a critical issue in this kind of simulation is how to efficiently distinguish all of the particles in any selected cluster only based on the three dimensional array Cube[L][L][L] when the cluster is to be moved. Similarly, there are difficulties in the process of collision detection to locate all neighboring positions of the cluster. The traditional method must perform exhaustive search in the whole system, what's more, this kind of exhaustive search will repeated over and over again in the simulation progression. In this paper, the traditional on-lattice CCA algorithm is optimized by improving the storage structure to reduce the time complexity, in which the simulation system is represented by a three dimensional array, while the clusters in the system are simultaneously stored by the linked lists respectively in programming. Another one dimensional array Cluster[N] is used to organize the linked lists and store the basic attributes of the clusters in the system. Initially, N linked lists, each only has one node, are created for the N randomly placed particles. After a cluster is moved, its particles is examined to determine whether any other clusters have been contacted via nearest neighbor occupancy. If aggregation does occur after the collision detection, the simple operation is to link the corresponding clusters. After an aggregation, the array Cluster should be indexed simultaneously because there may be some vacant linked lists. In the later random selection for the potential movement, these vacant linked lists should not be in the candidate lists. For the indexing, a one dimensional array Index[N] is used to store the non-vacant linked list subscripts of the array Cluster[N]. The current length of the Index is the number of the remaining clusters in the system. For example, if the new generated random number for the random selection is k, the label of the next moving cluster should be Index [k], and the linked list of this cluster is exactly linked by Cluster [Index[k]]. From this entry, all the particles in the cluster can be easily accessed. And then, the positions of the six neighboring boxes of each particle in the cluster can also be accessed by the element subscripts of the array Cube, which is needed for the collision detection. Brownian motion, collision detection and aggregation as the basic operations in the CCA simulation are all improved based on the compounded data structure. The results show that the new algorithm achieves linear time complexity from three cubed time complexity. This is a great contribution for researchers in large scale simulation of fractal aggregation. [ABSTRACT FROM AUTHOR]

To solve the global path planning problem in narrow and complex environments, the paper presented a new GA-based strategy. The initialization of path planning using the traditional GA in narrow space was difficult. First, base path search used Dijkstra algorithm; then, initial population coding by a new genetic code scheme and improved searching spaces; finally, path optimization used genetic algorithm. For the robots could not be scaled as points in narrow space, the paper proposed the global pass degree and path safety to evaluate the environment and the path. Simulation results show that compared with traditional GA and artificial potential field, this method ensures the path distance is short, increases path safety by more than 50% or reduces the time complexity by more than half. Results demonstrate that the practicality and effectiveness of the proposed method. [ABSTRACT FROM AUTHOR]

The ability to store and analyze big data is a crucial capability of a powerful country in the new century.The current research of big data contains weakness on common scientific questions,general methodology,and theoretical analysis of real-time algorithm.It started from three key features about big data:volume,variety,and velocity,and the measurement and simplification of time complexity,space complexity,and relationship complexity for big data were focused.

For the heterogeneity problem among ontologies, this paper presented an algorithm based on sub-graph approximate isomorphic here. It was an extension of existing methods in ontology matching. Under the comprehensive application of features such as edit distance and hierarchical relations, it calculated the similarity of graph structures between two ontologies. Lastly, it determined the ontology matching on the condition of sub-graph approximate isomorphism based on the alternately mapping of nodes and arcs in the describing graphs of ontologies. It used an example to demonstrate this ontology matching process and analyzed the time complexity to explain its effectiveness. [ABSTRACT FROM AUTHOR]

In order to do further research on routing protocol of OSPF, this paper analyzed and introduced the method of limit arrangement in mathematical principle, and designed a new routing decision algorithm. It showed that this algorithm and Dijkstra algorithm were the same in time complexity when the arrangement of routing was under the condition of single strand. Meanwhile it existed that the time complexity was between O(n²) and O(n³), and it could possibly be a good superiority when the time complexity was O(n³) when the arrangement of routing was in the actual network structure. When the network topology changes, the algorithm always has a good convergence, which show the algorithm expands OSPF and has widely application. [ABSTRACT FROM AUTHOR]

Chinese word segmentation dictionary based on the double-array Trie-tree has higher search efficiency, but the dynamic insertion consumes a lot of time. Therefore, an improved algorithm (iDAT) based on double-array Trie-tree for Chinese word segmentation dictionary is proposed. The nodes with more branches are handled while the original dictionary is being initialized. After the initialization, a Hash process is performed on the index values of empty sequence in base array. The final Hash table stores the sum of the empty sequences before the current empty sequence. After that, the iDAT is used to carry out the dynamic insertion process. This algorithm adopts Sunday jumps algorithm of single pattern matching. With the reasonable increasement of space, it reduces the the average time complexity of the dynamic insertion process in Trie-tree. Practical results show it has good operation performance. [ABSTRACT FROM AUTHOR]