Rearrangement Operations Research Articles

Image encryption scheme based on improved four-dimensional chaotic system and evolutionary operators

To enhance the security of image data transmission, and address the weaknesses of existing image encryption schemes based on chaotic systems, particularly concerning resistance to differential attacks and the unstable performance of chaotic systems, this article introduces an improved four-dimensional chaotic system and integrates evolutionary operators to propose an image encryption scheme. Firstly, a method for generating pseudo-random sequences associated with the plaintext is designed. The change rate of the ciphertext pixel value exceeds 0.9967 after a slight modification of the plaintext pixel value, significantly improving the plaintext sensitivity and the scheme's ability to resist selected plaintext attacks. Secondly, an individual rearrangement operation is introduced to achieve bit-level scrambling, and pixel-level scrambling is achieved by selection strategy. Subsequently, crossover and mutation operations are incorporated into image encryption. To reflect the randomness of the pairing, we adopt the pseudo-random sequence generated by the chaotic system to control the crossover and mutation operators, and a diffusion operation is performed on selected pixel pairs. Finally, ciphertext feedback is applied. Experimental results and performance analysis demonstrate that the proposed scheme not only enhances the security of encrypted images but also effectively resists noise and cropping attacks. This method effectively meets the high-security requirements of images in network transmission and provides new ideas for further research in the field of image encryption.

FAVOR: Full-Body AR-Driven Virtual Object Rearrangement Guided by Instruction Text

Rearrangement operations form the crux of interactions between humans and their environment. The ability to generate natural, fluid sequences of this operation is of essential value in AR/VR and CG. Bridging a gap in the field, our study introduces FAVOR: a novel dataset for Full-body AR-driven Virtual Object Rearrangement that uniquely employs motion capture systems and AR eyeglasses. Comprising 3k diverse motion rearrangement sequences and 7.17 million interaction data frames, this dataset breaks new ground in research data. We also present a pipeline FAVORITE for producing digital human rearrangement motion sequences guided by instructions. Experimental results, both qualitative and quantitative, suggest that this dataset and pipeline deliver high-quality motion sequences. Our dataset, code, and appendix are available at https://kailinli.github.io/FAVOR.

Time-difference reassigned transform with application to time difference of arrival for impulsive signal

Time difference of arrival (TDOA) is essential in localization, communication, and navigation. Under ambient noise interference, the impulsive signal is transmitted over a long distance and reaches the sensor with a low signal-to-noise ratio (SNR). Aiming to achieve a precise time delay estimation in scenarios with low SNR, this paper extends the time-reassigned extracting transform (TRET) theory to TDOA and proposes a time difference rearrangement extracting transform (TDRT) algorithm. The implementation process of the proposed algorithm comprises three steps. Initially, a rough two-dimensional time delay estimation is obtained by calculating the partial derivative of the short-time cross-power spectrum with respect to the frequency variable. Secondly, a rearrangement operation separates the signal's time-frequency (TF) points from the noise. Thirdly, a refined TDOA estimation is obtained by inverse Fourier transforming TF points extracted from the time-delay energy ridge. Simulation results show that the TDRT algorithm is effective in time delay estimation. Furthermore, experimental results prove that the performance of the TDRT algorithm outperforms comparable algorithms in low SNR environments.

Multi-Objective Multi-Skill Resource-Constrained Project Scheduling Considering Flexible Resource Profiles

This paper addresses a novel multi-skill resource-constrained project scheduling problem with flexible resource profiles (F-MSRCPSP), in which the resource allocation of each activity consists of a certain number of discrete resources and is allowed to be adjusted over its duration. The F-MSRCPSP aims, therefore, to determine the flexible resource profile of each activity to minimize the make-span and total cost simultaneously. Then, a hybrid multi-objective fruit fly optimization algorithm is proposed to handle the concerned problem. In the proposed algorithm, two flexible parallel and serial schedule generation schemes are introduced, aiming to schedule activities and adjust allocated resource combinations. Additionally, two heuristic strategies are proposed to effectively select suitable resource combinations for activities. Moreover, a series of operators has been developed, including the rejoining operator, empirical re-arrangement operator, and empirical re-selection operator. These operators aim to accelerate the convergence speed and enhance the exploration of the proposed algorithm. Finally, the orthogonal test is used to select the optimal parameter combination, and comparative experiments based on tests with different scales are conducted, along with a t-test. The experimental results demonstrate that MOFOA-HS is effective in solving the F-MSRCPSP.

Ranked Subtree Prune and Regraft

Phylogenetic trees are a mathematical formalisation of evolutionary histories between organisms, species, genes, cancer cells, etc. For many applications, e.g. when analysing virus transmission trees or cancer evolution, (phylogenetic) time trees are of interest, where branch lengths represent times. Computational methods for reconstructing time trees from (typically molecular) sequence data, for example Bayesian phylogenetic inference using Markov Chain Monte Carlo (MCMC) methods, rely on algorithms that sample the treespace. They employ tree rearrangement operations such as SPR\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$\ extrm{SPR}$$\\end{document} (Subtree Prune and Regraft) and NNI\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$\ extrm{NNI}$$\\end{document} (Nearest Neighbour Interchange) or, in the case of time tree inference, versions of these that take times of internal nodes into account. While the classic SPR\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$\ extrm{SPR}$$\\end{document} tree rearrangement is well-studied, its variants for time trees are less understood, limiting comparative analysis for time tree methods. In this paper we consider a modification of the classical SPR\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$\ extrm{SPR}$$\\end{document} rearrangement on the space of ranked phylogenetic trees, which are trees equipped with a ranking of all internal nodes. This modification results in two novel treespaces, which we propose to study. We begin this study by discussing algorithmic properties of these treespaces, focusing on those relating to the complexity of computing distances under the ranked SPR\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$\ extrm{SPR}$$\\end{document} operations as well as similarities and differences to known tree rearrangement based treespaces. Surprisingly, we show the counterintuitive result that adding leaves to trees can actually decrease their ranked SPR\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$\ extrm{SPR}$$\\end{document} distance, which may have an impact on the results of time tree sampling algorithms given uncertain “rogue taxa”.

Genome Rearrangement Analysis : Cut and Join Genome Rearrangements and Gene Cluster Preserving Approaches.

Genome rearrangements are mutations that change the gene content of a genome or the arrangement of the genes on a genome. Several years of research on genome rearrangements have established different algorithmic approaches for solving some fundamental problems in comparative genomics based on gene order information. This review summarizes the literature on genome rearrangement analysis along two lines of research. The first line considers rearrangement models that are particularly well suited for a theoretical analysis. These models use rearrangement operations that cut chromosomes into fragments and then join the fragments into new chromosomes. The second line works with rearrangement models that reflect several biologically motivated constraints, e.g., the constraint that gene clusters have to be preserved. In this chapter, the border between algorithmically "easy" and "hard" rearrangement problems is sketched and a brief review is given on the available software tools for genome rearrangement analysis.

Improving the Robustness of Time Difference of Arrival Estimation Based on the Energy Center of Gravity Rearrangement.

An accurate estimation of the time difference of arrival (TDOA) is crucial in localization, communication, and navigation. However, a low signal-to-noise ratio (SNR) can decrease the reliability of the TDOA estimation result. Therefore, this study aims to improve the performance of the TDOA estimation of dual-channel sensors for single-sound sources in low-SNR environments. This study introduces the theory of time rearrangement synchrosqueezing transform (TRST) into the time difference of arrival estimation. While the background noise TF points show random time delays, the signal time-frequency (TF) points originating from uniform directions that exhibit identical lags are considered in this study. In addition, the time difference rearrangement synchrosqueezing transform (TDST) algorithm is developed to separate the signal from the background noise by exploiting its distinct time delay characteristics. The implementation process of the proposed algorithm includes four main steps. First, a rough estimation of the time delay is performed by calculating the partial derivative of the short-time cross-power spectrum. Second, a rearrangement operation is conducted to separate the TF points of the signal and noise. Third, the TF points on both sides of the time-delay energy ridge are extracted. Finally, a refined TDOA estimation is realized by applying the inverse Fourier transformation on the extracted TF points. Furthermore, a second-order-based time difference reassigned synchrosqueezing transform algorithm is proposed to improve the robustness of the TDOA estimation by enhancing the TF energy aggregation. The proposed algorithms are verified by simulations and experiments. The results show that the proposed algorithms are more robust and accurate than the existing algorithms.

Super oriented cycles in permutations

The degree of dissimilarity between genome sequences of homologous species is a measure of the evolutionary distance between them. It serves as a metric in the construction of phylogenetic trees, which depict the evolutionary relationships and common ancestry among different species. Given two genome sequences, evolutionary distance is determined by estimating the number of global mutations that transform one sequence to the other. The computation of the evolutionary distance is done by modelling a genome with the corresponding permutation. Global rearrangement operations such as transposition that model a particular genomic mutation are studied by employing a combinatorial structure known as a cycle graph of the corresponding permutation. A cycle in a cycle graph that has odd length is called an odd cycle. In the context of the problem of sorting by transpositions (SBT), a valid 2-move is a transposition that increases the number of odd cycles in the cycle graph by two. A super oriented cycle (SOC) is an odd cycle C where C and one of the resultant cycles admit valid 2-moves. The minimum number of mutations required to transform a species S into a related species T is the distance from S to T under that mutation. Christie opined that characterizing SOCs will improve the lower bound of the transposition distance. We characterize super oriented cycles. Equivalent transformations on permutations like reduction and (g,b)-split preserve the transposition distance of a given permutation and map SBT to the corresponding SBT on a transformed simpler permutation. We introduce merge, a novel equivalent transformation. These results have applications in computing transposition and other distances between related species.

Algorithms for the genome median under a restricted measure of rearrangement

Ancestral reconstruction is a classic task in comparative genomics. Here, we study thegenome median problem, a related computational problem which, given a set of three or more genomes, asks to find a new genome that minimizes the sum of pairwise distances between it and the given genomes. Thedistancestands for the amount of evolution observed at the genome level, for which we determine the minimum number of rearrangement operations necessary to transform one genome into the other. For almost all rearrangement operations the median problem is NP-hard, with the exception of thebreakpoint medianthat can be constructed efficiently for multichromosomal circular and mixed genomes. In this work, we study the median problem under a restricted rearrangement measure calledc4-distance, which is closely related to the breakpoint and the DCJ distance. We identify tight bounds and decomposers of thec4-median and develop algorithms for its construction, one exact ILP-based and three combinatorial heuristics. Subsequently, we perform experiments on simulated data sets. Our results suggest that thec4-distance is useful for the study the genome median problem, from theoretical and practical perspectives.

A Fast 3-D Chirp Scaling Imaging Technique for Millimeter-Wave Near-Field Imaging

In this article, a novel 3-D imaging method based on the chirp scaling algorithm (CSA) is proposed for millimeter-wave near-field imaging. We deduce the theoretical formula of CSA applied to multiple-input–multiple-output (MIMO)/single-input–single-output (SISO) array imaging and then analyze the computational complexity and phase error. Compared to the classical Fourier-based algorithm, such as range migration algorithm (RMA), they can replace the redundant interpolation with the phase multiplication. Meanwhile, it can handle the large relative bandwidth system compared with frequency scaling algorithm (FSA). It greatly improves imaging speed and broadens the application scenarios. The rearrangement operation of the MIMO wavenumber spectrum is also accelerated by the sparse matrix multiplication. To further reduce the computation time, we perform the direct rearrangement of the MIMO wavenumber spectrum before phase compensation. It works well but also sacrifices part of the signal-to-noise ratio (SNR), so it may not be suitable for the weakly scattering targets. The simulation data of a 2-D uniform array with the large number of antennas and a published dataset are used to verify the effect of the proposed algorithm. The simulation and experiment results show that the proposed method can effectively improve the computational efficiency.

A new RFID ultra-lightweight authentication protocol for medical privacy protection in smart living

The widespread application of Radio Frequency Identification (RFID) technology in smart living, especially in smart healthcare, has greatly facilitated patient management, reduced the labor cost of medical services, and provided patients with better medical services. However, improper use of RFID tags is highly likely to threaten the safety and privacy of hospitals and even patients, which may not only cause physical and mental harm to patients but also damage the reputation of hospitals. Medical monitoring system based on RFID technology plays a significant role in guaranteeing the security of medical records as well as the privacy of patients. Nevertheless, due to the resource constraint of RFID tags/readers, it is also challenging to design an efficient and effective authentication protocol for RFID medical monitoring system. Aiming to reduce the resource overhead and meet security requirements of the RFID system, in this paper, we propose an ultra-lightweight RFID security authentication protocol utilizing a cloud server named CRUSAP, which is based on Bit-Crossing XOR rearrangement operations that can effectively resist forgery attacks, replay attacks, desynchronization attacks, and denial of service attacks while certifying the cloud server. The formal logic of BAN proves the safety and feasibility of the protocol. Additionally, the security analysis and experimental results show that the proposed authentication protocol can realize higher security goals at a lower cost and is more suitable for scaling to large-scale authentication.

Second-order Iterative Time-rearrangement Synchrosqueezing Transform and its application to rolling bearing fault diagnosis

Rolling bearings are key components in rotating machines, and their health condition is an important guarantee for the safety of the whole machine. In order to extract fault features of rolling bearings more accurately, a novel signal processing method named Second-order Iterative Time-rearrangement Synchrosqueezing Transform (2-ITSST) with a fast algorithm is proposed in this paper. Firstly, based on Time-reassigned SynchroSqueezing Transform (TSST), the approximation order is increased from the first order to the second order. Then, multiple iterations are conducted to calculate a more accurate group delay (GD) estimation operator. After that, the rearrangement operation is carried out to maximize the concentration of energy near the time-frequency (TF) ridgeline and obtain the result with higher TF aggregation. Lastly, the fast algorithm for 2-ITSST is introduced to overlap TF matrices into segments, which effectively reduced the computational complexity and ensured the TF aggregation of impact signal energy. Meanwhile, in order to make 2-ITSST more efficiently applied in bearing fault diagnosis, impulse extraction method is introduced to extract useful impulse features from the signal processed by 2-ITSST algorithm, and then the bearing fault frequency can be accurately extracted by envelope spectrum analysis. The effectiveness of the proposed method is verified by simulation and experimental studies.

Small parsimony for natural genomes in the DCJ-indel model.

The Small Parsimony Problem (SPP) aims at finding the gene orders at internal nodes of a given phylogenetic tree such that the overall genome rearrangement distance along the tree branches is minimized. This problem is intractable in most genome rearrangement models, especially when gene duplication and loss are considered. In this work, we describe an Integer Linear Program algorithm to solve the SPP for natural genomes, i.e. genomes that contain conserved, unique, and duplicated markers. The evolutionary model that we consider is the DCJ-indel model that includes the Double-Cut and Join rearrangement operation and the insertion and deletion of genome segments. We evaluate our algorithm on simulated data and show that it is able to reconstruct very efficiently and accurately ancestral gene orders in a very comprehensive evolutionary model.

Improved upper bound for sorting permutations by prefix transpositions

Modelling of chromosomes with permutations has triggered the research of sorting permutations using global rearrangement operations in computational molecular biology. One such rearrangement is transposition which swaps two adjacent substrings. If one of the substrings is restricted to be the prefix of the permutation then that operation is called a prefix transposition. The symmetric prefix transposition distance between two permutations is defined to be the minimum number of prefix transpositions required to transform one into another. Group theory dictates that an upper bound for prefix transposition distance between any pair of permutations in the symmetric group Sn is equivalent to the upper bound for sorting any permutation with prefix transpositions. In this paper, we improve the upper bound for sorting permutations with prefix transpositions to n−log2⁡n.

Parametric Doppler correction analysis for wayside acoustic bearing fault diagnosis

Wayside acoustic system plays a crucial role in monitoring and diagnosing the status of train wheel bearings. However, due to the signal distortion caused by Doppler effect, the diagnosis accuracy will be seriously disturbed. In this manner, this paper proposes a model-driven Doppler distortion self-tuning method in theory, named as parametric Doppler correction analysis (PDCA). Different from traditional methods, such as instantaneous frequency tracking and Doppler distortion sparse representation, the proposed method aims to abstractly construct a physical model of acoustic signal distortion propagation based on Morse acoustic theory, where the acoustic forward propagation model and reverse reconstruction model are simultaneously built. The scheme consists of four basic steps. Firstly, the physical model with amplitude modulation operator and frequency shift operator is described for the distortion process. Secondly, the pseudo transition signal with the characteristics of energy accumulation and no distortion is obtained via a construction of frequency rearrangement operator and amplitude demodulation operator. Then, pseudo Doppler correction (PDC) is presented to solve the frequency distortion of the received signal, where a high energy accumulation for frequency distribution is designed as optimization function. Especially, quasi Newton algorithm L-BFGS is used to realize the adaptive learning for distortion parameters. Finally, through time-domain interpolation resampling (TIR) technique, the corrected signal can be analytically reconstructed with the optimal parameters. Applying the PDCA scheme to simulated signals and experimental signals, its validity is verified. The comparison with the instantaneous frequency ridge extraction approach further indicates the proposed model-driven method can reach a more accurate correction result in a faster and adaptive process.

Short-Time Fourier Transform Based on Metaprogramming and the Stockham Optimization Method.

The extension for high-performance STFT (Short-Time Fourier Transform) algorithm written entirely in Java language for non-parallel computations is presented in the current paper. This solution could compete with the best available and most common algorithms supplied by libraries such as FFTW or JTransform. The main idea was to move complex computations and expensive functions to the program generation phase. Thus, only core and essential operations were executed during the runtime phase. Furthermore, new approach allows to eliminate the necessity for a rearrangement operation that uses the bit-reversal permutation technique. This article presents a brief description of the STFT solution that was worked out as an extension for the original application, in order to increase its efficiency. The solution remains a Stockham algorithm adapted using metaprogramming techniques and entails an additional reduction its execution time. Performance tests and experiments were conducted using a Java Platform and JMH library, which allowed for accurate execution time measurements. Major aspects of the Java VM like warm-up effects were also taken into consideration. Solution was applied into Electrical Capacitance Tomography measurement system in order to measure the material changes during the silo discharging industrial process.

Computing nearest neighbour interchange distances between ranked phylogenetic trees

Many popular algorithms for searching the space of leaf-labelled (phylogenetic) trees are based on tree rearrangement operations. Under any such operation, the problem is reduced to searching a graph where vertices are trees and (undirected) edges are given by pairs of trees connected by one rearrangement operation (sometimes called a move). Most popular are the classical nearest neighbour interchange, subtree prune and regraft, and tree bisection and reconnection moves. The problem of computing distances, however, is {mathbf {N}}{mathbf {P}}-hard in each of these graphs, making tree inference and comparison algorithms challenging to design in practice. Although ranked phylogenetic trees are one of the central objects of interest in applications such as cancer research, immunology, and epidemiology, the computational complexity of the shortest path problem for these trees remained unsolved for decades. In this paper, we settle this problem for the ranked nearest neighbour interchange operation by establishing that the complexity depends on the weight difference between the two types of tree rearrangements (rank moves and edge moves), and varies from quadratic, which is the lowest possible complexity for this problem, to {mathbf {N}}{mathbf {P}}-hard, which is the highest. In particular, our result provides the first example of a phylogenetic tree rearrangement operation for which shortest paths, and hence the distance, can be computed efficiently. Specifically, our algorithm scales to trees with tens of thousands of leaves (and likely hundreds of thousands if implemented efficiently).

Task Scheduling Problem of Double-Deep Multi-Tier Shuttle Warehousing Systems

Double-deep multi-tier shuttle warehousing systems (DMSWS) have been increasingly applied for store-and-retrieval stock-keeping unit tasks, with the advantage of a reduced number of aisles and improved space utilization. Scheduling different devices for retrieval tasks to increase system efficiency is an important concern. In this paper, a Pareto optimization model of task operations based on the cycle time and carbon emissions is presented. The impact of the rearrangement operation is considered in this model. The cycle time model is converted into a flow-shop scheduling model with parallel machines by analyzing the retrieval operation process. Moreover, the carbon emissions of the shuttle in the waiting process, the carbon emissions of the lift during the free process, and the carbon emissions of the retrieval operation are considered in the carbon emissions model, which can help us to evaluate the carbon emissions of the equipment more comprehensively during the entire retrieval task process. The elitist non-dominated sorting genetic algorithm II (NSGA-II) is adopted to solve the non-linear multi-objective optimization function. Finally, a real case is adopted to illustrate the findings of this study. The results show that this method can reduce carbon emissions and improve system efficiency. In addition, it also help managers to reduce operational costs and improve the utilization of shuttles.

Sorting permutations by fragmentation-weighted operations

One of the main problems in Computational Biology is to find the evolutionary distance among species. In most approaches, such distance only involves rearrangements, which are mutations that alter large pieces of the species' genome. When we represent genomes as permutations, the problem of transforming one genome into another is equivalent to the problem of Sorting Permutations by Rearrangement Operations. The traditional approach is to consider that any rearrangement has the same probability to happen, and so, the goal is to find a minimum sequence of operations which sorts the permutation. However, studies have shown that some rearrangements are more likely to happen than others, and so a weighted approach is more realistic. In a weighted approach, the goal is to find a sequence which sorts the permutations, such that the cost of that sequence is minimum. This work introduces a new type of cost function, which is related to the amount of fragmentation caused by a rearrangement. We present some results about the lower and upper bounds for the fragmentation-weighted problems and the relation between the unweighted and the fragmentation-weighted approach. Our main results are 2-approximation algorithms for five versions of this problem involving reversals and transpositions. We also give bounds for the diameters concerning these problems and provide an improved approximation factor for simple permutations considering transpositions.

A New Reinforcement Learning for Multi-Train Marshaling with Time Evaluation

In this paper, a new reinforcement learning method is proposed to solve a train marshaling problem for assembling several outgoing trains simultaneously. In the addressed problem, the order of the incoming freight cars is assumed to be random. Then, the freight cars are classified into several sub-tracks. The cars on sub-tracks are rearranged to the main track by a certain desirable order. In the proposed method, each set of freight cars that have the same destination make a group, and the desirable group layout constitutes the best outgoing trains. When a rearrangement operation is conducted, the best number of sub-tracks used in the operation is obtained by a reinforcement learning system, as well as the best layout of groups in the trains, the best order to rearrange cars by the desirable order, and the best sub-track for the car to be removed. The marshaling plan that consists of series of removal and rearrangement operations are generated based on the processing time of movements of freight cars. The total processing time required to assemble outgoing trains can be minimized by the proposed method.