Traversal Sequences Research Articles

A novel approach to visual image encryption: 2D hyperchaos, variable Josephus, and 3D diffusion

Abstract With the development of the Internet, image encryption technology has become critical for network security. Traditional methods often suffer from issues such as insufficient chaos, low randomness in key generation, and poor encryption efficiency. To enhance performance, this paper proposes a new encryption algorithm designed to optimize parallel processing and adapt to images of varying sizes and colors. The method begins by using SHA-384 to extract the hash value of the plaintext image, which is then processed to determine the chaotic system’s initial value and block size. The image is padded and divided into blocks for further processing. A novel two-dimensional infinite collapses hyperchaotic map (2D-ICHM) is employed to generate the intra-block scrambling sequence, while n improved variable Joseph traversal sequence is used for inter-block scrambling. After removing the padding, 3D forward and backward shift diffusions, controlled by the 2D-ICHM sequences, are applied to the scrambled image, producing the ciphertext. Simulation results demonstrate that the proposed algorithm outperforms others in terms of entropy, anti-noise resilience, correlation coefficient, robustness, and encryption efficiency.

Research on Path Planning for Industrial Cleaning Robots in Complex Environments: An Enhanced Immunogenetic Algorithm Approach

As industrial automation advances, cleaning robots in complex environments have demonstrated significant value in enhancing efficiency and reducing labor costs. This paper presents a path planning method based on an improved Immune Genetic Algorithm (IGA) for comprehensive coverage path planning in complex industrial settings. Initially, the Boustrophedon Cellular Decomposition (BCD) method is employed to effectively segment the complex scene, identifying key areas for cleaning tasks. Subsequently, the path planning efficiency and adaptability are enhanced through an optimized genetic algorithm that integrates immune memory, Inver-Over operators, and 3-opt operators to refine the traversal sequence between regions. Moreover, this study incorporates the A* algorithm and the Biologically Inspired Neural Network (BINN) algorithm for efficient inter-regional path transitions and precise intra-regional traversal, respectively. A series of simulation experiments validate the superiority of the proposed algorithm in terms of path length, coverage rate, and computational time. The results demonstrate that this method not only effectively addresses the challenges of path planning in complex industrial environments but also significantly improves cleaning efficiency, offering high practical value and potential for broader application.

Semantic enrichment of BIM with IndoorGML for quadruped robot navigation and automated 3D scanning

Planning scan routes with prior knowledge can improve scan data quality and completeness. This paper presents a BIM-enabled approach to optimize quadruped robot navigation for automated 3D scanning. The BIM data schema is enriched with IndoorGML, integrating building geometry with spatial data to establish an indoor navigation model describing multi-scale spatial topological networks. This navigation model, which includes an enhanced greedy algorithm, optimizes quadruped robot scanning positions and traversal sequences. The scan planning optimization outperforms existing heuristic algorithms in computational efficiency, coverage, and scan point count. The BIM-enabled approach is validated on ROS and in real-world conditions with a 3D LiDAR sensor integrated with a quadruped robot. The robotic scans achieve visible coverage of 70–90% of the structure, with a fluctuation of 0.006–0.021 mm compared to traditional laser scans. The findings demonstrate robotic scans as a viable way of obtaining complete and accurate point clouds, reducing human effort in traditional scanning.

Vision-based investigation of road traffic and violations at urban roundabout in India using UAV video: A case study

In the past decade, the number of vehicles in India has increased exponentially; however, road infrastructure has not scaled proportionately. As a result, road traffic problems such as congestion on urban roads, dangerous traffic violations, and road accidents have increased significantly. Due to limited road infrastructure, traffic violations (human errors) have intensified in densely populated urban areas. This paper presents a case study (at a multi-lane urban roundabout in Ahmedabad city, India) and the methodology based on computer vision to investigate road traffic and violations using drone/UAV-based aerial video. You Only Look Once-YOLOv7 is used for vehicle detection, and Simple Online and Real Time Tracking-SORT for tracking vehicles. Our methodology divides the road scene (roundabout) into certain zones. We then formulated the dictionary, which maps the traffic violations under Motor Vehicle Driving Regulations - MVDR/ Motor Vehicle Act - MVA and the movement of the vehicle (zone traversal sequences). Using the zone-based methodology, we could also probe other road traffic data such as the count of vehicles, speed of vehicles, rate of traffic flow, and congestion. Based on our results, we also infer some of the possible causes of traffic violations in terms of problems/limitations of road infrastructure. As per our analysis, around 23.26% of vehicles committed traffic violations. We detected traffic violations related to lane indiscipline, driving against the authorized flow of traffic, parking violations, and over-speeding within the roundabout. Our methodology of investigating road traffic and violations can be used for road infrastructure improvement, law enforcement drives, and policy making, for road traffic safety, in developing and densely populated countries.

Genetic Algorithms for Coverage Path Planning using Mobile Robots

Using the grid method to establish the environmental model, the map is divided into several sub-regions according to the environmental characteristics, and the connection between the sub-regions is established. Next, the Genetic Algorithm encodes all sub-regions, and the base point information between and within each region is established to obtain the optimal coverage sequence. Partial coverage is achieved in each sub-region by means of reciprocating motion, which turns the complete coverage problem into a traveling salesman problem (TSP). Finally, the Genetic Algorithm is used to conduct an experimental simulation to obtain the correlation between the fitness and the number of iterations, and obtain the optimal traversal sequence, which proves that the method is effective and feasible.

Research on mathematical expressions matching algorithms for computer algebra systems

For the interactive computer algebra system (CAS), to solve the matching problem of different mathematical expressions between students and CAS, this paper proposes a mathematical expression matching algorithm to achieve exact matching of different mathematical expressions between students and CAS. First, according to the MathML representation markup coding of the mathematical expression, the markup coding is parsed into the linear string representation of the expression by the back-end program, and the binary tree is generated after preprocessing it and then normalizing its tree structure and calculating the structured coding of the binary tree. For the two mathematical expressions to be matched, if their structure codings are the same, then compare their postorder and in-order traversal sequences. If they are the same, the two expressions are matched in the structure; go to the next step of the algorithm: matching the content of the mathematical expressions. For the binary tree of expressions with the same structure, the above traversal sequence is repeated to compare the obtained traversal sequence. The two expressions match if they are the same; otherwise, they do not match. The algorithm can realize exact matching between two mathematical expressions from the experimental results. When faced with mathematical expressions containing a large number of large integers, the matching of its structure is judged first. If it does not match, it can interrupt and exit and save time. It improves the running efficiency of the algorithm and is a convenient, fast, and practical algorithm.

An image encryption algorithm based on spatiotemporal chaos and middle order traversal of a binary tree

This paper proposes an image encryption algorithm based on spatiotemporal chaos and middle order traversal of a binary tree. Firstly, other programming software is used to perform the middle order traversal, and the plaintext image is sorted according to the middle order traversal sequence on the permutation. Secondly, the chaotic sequence is generated using the coupled map lattice to set the chaotic interference value. Finally, the XOR operation between the adjacent pixel values of the replacement image is completed to generate the ciphertext matrix. The simulation and experimental results show that the proposed algorithm can resist typical attacks and has good robustness.

Multi-scale coal and gangue dual-energy X-ray image concave point detection and segmentation algorithm

The premise of identifying, locating, and sorting coal and gangue using photoelectric sorting technology is that independent image targets should be obtained. In this study, concave point detection and segmentation algorithm are proposed to segment overlapping particles. First, the edge coordinate sequence is obtained for the overlapping part of the concave defect area of the adhesion target and the binary image of the adhesion target. Subsequently, the initial linear equation passing through the beginning and ending points of the sequence is built. The traversal sequence updates the new linear equation parallel to the initial linear equation, and the positional relationship between the front and back points of the search point and the linear equation is determined. The concave point detection is transformed into the positional relationship between pixels and linear equations. Lastly, the segmentation line segmentation image is generated based on concave points, and the segmentation accuracy reaches 93.15%.

Symmetric Image Encryption Algorithm Based on a New Product Trigonometric Chaotic Map

In the present work, a neotype chaotic product trigonometric map (PTM) system is proposed. We demonstrate the chaotic characteristics of a PTM system by using a series of complexity criteria, such as bifurcation diagrams, Lyapunov exponents, approximate entropy, permutation entropy, time-series diagrams, cobweb graphs, and NIST tests. It is proved that the PTM system has a wider chaotic parameter interval and more complex chaotic performance than the existing sine map system. In addition, a novel PTM based symmetric image encryption scheme is proposed, in which the key is related to the hash value of the image. The algorithm realizes the encryption strategy of one-graph-one-key, which can resist plaintext attack. A two-dimensional coordinate traversal matrix for image scrambling and a one-dimensional integer traversal sequence for image pixel value transformation encryption are generated by the pseudo-random integer generator (PRING). Security analysis and various simulation test results show that the proposed image encryption scheme has good cryptographic performance and high time efficiency.

A System for Optimizing the Process of Straw Bale Retrieval

During a baling operation, the operator of the baler should decide when and where to drop the bales in the field to facilitate later retrieval of the bales for transport out of the field. Manually determining the time and place to drop a bale creates extra workload on the operator and may not result in the optimum drop location for the subsequent front loader and transport unit. Therefore, there is a need for a tool that can support operators during this decision process. The key objective of this study is to find the optimal traversal sequence of fieldwork tracks to be followed by the baler and bale retriever to minimize the non-working driving distance in the field. Two optimization processes are considered for this problem. Firstly, finding the optimal sequence of fieldwork tracks considering the constraints of the problem such as the capacity of the baler and the straw yield map of the field. Secondly, finding the optimal location and number of bales to drop in the field. A simulation model is developed to calculate all the non-productive traversal distances by baler and bale retrieval in the field. In a case study, the collected positional and temporal data from the baling process related to a sample field were considered. The output of the simulation model was compared with the conventional method applied by the operators. The results show that application of the proposed method can increase efficiency by 12.9% in comparison with the conventional method with edited data where the random movements (due to re-baling, turns in the middle of the swath, reversing, etc.) were removed from the data set.

A Top-K QoS-Optimal Service Composition Approach Based on Service Dependency Graph

With the development of internet of things (IoT) technology, servitization of IoT device functions has become a trend. The cooperation between IoT devices can be equivalent to web service composition. However, current service composition approaches applied in the internet cannot work well in IoT environments due to weak adaptability, low accuracy, and poor time performance. This paper, based on service dependency graph, proposes a top-k QoS-optimal service composition approach suitable for IoT. It aims to construct the relationship between services by applying the service dependency model and to reduce the traversal space through effective filtering strategies. On the basis of a composition path traversal sequence, the generated service composition can be represented directly to avoid backtracking search. Meanwhile, the redundant services can be removed from the service composition with the help of dynamic programming. Experiments show that the approach can obtain the top-k QoS-optimal service composition and better time performance.

Application of chaotic Josephus scrambling and RNA computing in image encryption

This article describes the application of chaotic Josephus scrambling and RNA computing in image encryption. The algorithm uses the classical ‘scrambling-diffusion’ process, and the pseudo-random sequences used in each stage are generated by the hyper-chaotic Lorenz system. Firstly, during the scrambling phase, the randomness of the traditional Josephus traversal sequence is improved by using chaotic mapping, which makes the image scrambling effect better. Then during the diffusion phase, the gray value of the pixel is modified by using RNA modular operation and random substitution of RNA codons. The research results prove the feasibility of the encryption system.

An Accelerated U-Shapelet Time Series Clustering Method with LSH

The clustering method of time series is based on the measurement of the whole time series, and the traditional clustering method is used for direct clustering. It was only recently that Keough came up with the concept of Shapelet. He later applied this concept to unsupervised time series clustering. This is a time series clustering method based on the feature of sub-series. This method has good clustering accuracy and stability. However, due to the fact that traversal sequences are all sub-sequences, the original violent search algorithm is very complex and difficult to be applied to a large number of time series data sets. In this paper, on the basis of the original method, you introduce the idea of data retrieval in the data preprocessing stage to quickly screen candidate subsequences. Then we introduce a position-aware hashing algorithm -LSH. The method is used to match the sub-sequences of the pre-processed time series data, and the wide representativeness of the high-quality u-Shapelet is used for selection. Therefore, LSH-us is proposed in this paper to speed up the extraction process of feature sub-sequences. Experimental results show that this algorithm can improve the speed of u-Shapelet time series clustering algorithm and ensure the accuracy of clustering.

A new method for business process retrieval using breadth-first traversal

ABSTRACTDue to the increasing of complex services in the deployed cloud platforms, business process retrieval has become a challenge for enterprises. However, traditional methods mostly focus on single attribute of business processes, rather than considering the attribute relationship and the loop structure. In this paper, we propose a breadth-first traversal (BFT) similarity calculation approach to overcome these drawbacks. First, we transform business process models into breadth-first traversal sequences (BFTS) using breadth-first traversal. Next, the BFTSs are divided into behavior sequences and structure sequences. Finally, the similarity values are calculated by weighting the two parts. The experimental results demonstrate our proposed method is accurate and time-saving in searching business processes.

Solving mazes with single-molecule DNA navigators.

Molecular devices with information-processing capabilities hold great promise for developing intelligent nanorobotics. Here we demonstrate a DNA navigator system that can perform single-molecule parallel depth-first search on a ten-vertex rooted tree defined on a two-dimensional DNA origami platform. Pathfinding by the DNA navigators exploits a localized strand exchange cascade, which is initiated at a unique trigger site on the origami with subsequent automatic progression along paths defined by DNA hairpins containing a universal traversal sequence. Each single-molecule navigator autonomously explores one of the possible paths through the tree. A specific solution path connecting a given pair of start and end vertices can then be easily extracted from the set of all paths taken by the navigators collectively. The solution path laid out on origami is illustrated with single-molecule imaging. Our approach points towards the realization of molecular materials with embedded computational functions operating at the single-molecule level.

Concealed in web surfing: Behavior-based covert channels in HTTP

Application-layer covert channels have been extensively studied in recent years. Ubiquitous application packets serving as covert carriers contain a considerable potential channel capacity. However, undetectability is still a challenging task to be resolved for practicability, as almost all existing covert channels are frustrated by specific detection methods. In this paper, we focus on the problem of undetectable application-layer covert channels. We found a natural HTTP behavior that distribution relationships between HTTP requests and flows are dynamic when opening a webpage. Motivated by this finding, we present a behavior-based covert channel, Lost in HTTP Behaviors (LiHB). LiHB embeds secret messages into request-flow distributions using combinatorics without changing any packet contents. Furthermore, LiHB achieves automatic coding with no need for a codebook. In particular, LiHB is able to penetrate web proxy to transmit information stealthily. To overcome limitations of LiHB, we propose an enhanced secure HTTP behavior-based covert channel (HBCC), which is statistically undetectable by shape and regularity tests. HBCC employs an independent and identically distributed (i.i.d.) inter-request delay (IRD) generator to maintain the request distribution of legitimate traffic, and mimics normal browsing patterns based on the frequent traversal sequences. Experimental results show LiHB and HBCC have a good performance and reliability, and HBCC outperforms LiHB in terms of channel capacity and undetectability.

Succinct Indices for Path Minimum, with Applications

In the path minimum problem, we preprocess a tree on n weighted nodes, such that given an arbitrary path, the node with the smallest weight along this path can be located. We design novel succinct indices for this problem under the indexing model, for which weights of nodes are read-only and can be accessed with ranks of nodes in the preorder traversal sequence of the input tree. We presentan index within O(m) bits of additional space that supports queries in $$O(\varvec{\alpha }(m, n))$$O(ź(m,n)) time and $$O(\varvec{\alpha }(m, n))$$O(ź(m,n)) accesses to the weights of nodes, for any integer $$m \ge n$$mźn; andan index within $$2n + o(n)$$2n+o(n) bits of additional space that supports queries in $$O(\varvec{\alpha }(n))$$O(ź(n)) time and $$O(\varvec{\alpha }(n))$$O(ź(n)) accesses to the weights of nodes. Here $$\varvec{\alpha }(m, n)$$ź(m,n) is the inverse-Ackermann function, and $$\varvec{\alpha }(n) = \varvec{\alpha }(n, n)$$ź(n)=ź(n,n). These indices give us the first succinct data structures for the path minimum problem. Following the same approach, we also develop succinct data structures for semigroup path sum queries, for which a query asks for the sum of weights along a given query path. One of our data structures requires $$n\lg \sigma + 2n + o(n\lg \sigma )$$nlgź+2n+o(nlgź) bits of space and $$O(\varvec{\alpha }(n))$$O(ź(n)) query time, where $$\sigma $$ź is the size of the semigroup. In the path reporting problem, queries ask for the nodes along a query path whose weights are within a two-sided query range. Using the succinct indices for path minimum queries, we achieve three different time/space tradeoffs for path reporting by designingan O(n)-word data structure with $$O(\lg ^\epsilon n + occ \cdot \lg ^\epsilon n)$$O(lg∈n+occ·lg∈n) query time;an $$O(n\lg \lg n)$$O(nlglgn)-word data structure with $$O(\lg \lg n + occ \cdot \lg \lg n)$$O(lglgn+occ·lglgn) query time; andan $$O(n \lg ^\epsilon n)$$O(nlg∈n)-word data structure with $$O(\lg \lg n + occ)$$O(lglgn+occ) query time. Here occ is the number of nodes reported and $$\epsilon $$∈ is an arbitrary constant between 0 and 1. These tradeoffs match the state of the art of two-dimensional orthogonal range reporting queries (Chan et al. 2011), which can be treated as a special case of path reporting queries. When the number of distinct weights is much smaller than n, we further improve both the query time and the space cost of these three results.

A novel extreme learning fault diagnosis based supervision applied to mathematical formula contrastive analysis

Focusing on the issue of few contrastive analysis technologies existing on mathematical formula in literatures, two methods of mathematical formula contrastive analysis subject to PDF and XML document formats are proposed. First, a novel extreme learning machine (ELM) fault diagnosis based supervision is presented and applied to mathematical formula contrastive analysis subject to PDF document. The strategy employs its merits such as fast learning speed, ease of implementation high efficiency and minimal human intervention, and not rely on the hidden neurons tuned. At the same time, the supervision mechanism is combined to realize the novel mathematical formula contrastive analysis based ELM supervision (ELMS). Second, a new mathematical formula contrastive analysis based MathML subject to XML document formats is presented. The idea first recognizes and extracts mathematical formulas in the detected XML document, normalizing the markup code of mathematical formulas. And then creating the tree presentation of mathematical the formula according to its presentation markup code, normalizing the tree structure by rule base, level traversing the tree to normalize the variable names and to get structure code of the tree. At last, searching the formula information table that named by the structure code. If the table exist, then searching the preorder traversal sequence of the tree in the table. If the records exist, then searching the postorder traversal sequence of the tree in the records. The searching result confirm if the mathematical formula belong to plagiarism. The experimental results reveal that the proposed algorithms can complete the contrastive analysis accurately of mathematical formula in XML documents whatever it existings PDF or XML format and has high performance on detection accuracy and speed.

Quantifying the benefits of alternative fieldwork patterns in a potato cultivation system

The fieldwork pattern, which is the ordered traversal sequence of in-field tracks by the machine, plays an important role in operational efficiency. A sub-optimal fieldwork pattern is a main reason for lost time in fieldwork operations due to excessive non-working distance and time. Even though algorithms exist that can calculate an optimal route plan of a specific operation that covers the field with minimum non-working distance and time, so far no commercial navigation-aiding system for agricultural vehicles exist that can implement this type of patterns. Yet, the implementation of applicable standard fieldwork pattern in real life operations can provide near-optimal solutions compared to the simple fieldwork patterns generally selected by operators.In this paper, the potential savings from following an alternative fieldwork pattern instead of the one selected by an experienced operator are assessed. We simulate the distance and time corresponding to five selected common fieldwork patterns and compare them with the operators’ selected fieldwork pattern. In order to simulate the fieldwork patterns, four standard turn models, which are formulas for calculating the turning distance of various types of turns, are fitted to actual turns recorded in field experiments, and the turn models together with a model of in-field transport and material reloading are evaluated. As a case study three sequential operations of potato cultivation (bed forming, stone separation and planting) were recorded and analysed in three different fields. The simulation results showed significant potential savings of both distance and time in all three operations and all three case study fields by selecting the best fieldwork pattern instead of the actual selected pattern: For bed forming the savings were up to 18.4% in distance and 32.7% in time; For stone separation the savings of distance and time were up to 35.0% and 60.9%; For the planting the savings were up to 22.6% in distance and 24.8% in time. The increase in time-based field efficiency was up to 2.7%, 7.2% and 7.1% for bed forming, stone separation and planting, respectively.

Multiple Binary Trees Encryption Principle

Through block cipher method, this paper demonstrates using preorder and post traversal sequence of a binary tree with 64 nodes to implement symmetric encryption/decryption. The different traversal sequences may determine a binary tree, so the method is vulnerable to be attacked. The paper’s further deduction involves improvement using multiple binary trees, so that more secure and efficient symmetric encryption algorithms can be obtained.