Decoding Rule Research Articles

Spelling-to-pronunciation transparency ratings for the 20,000 most frequently written English words.

Given English orthography's quasi-regular nature, applying common decoding rules to a word does not always result in a correct pronunciation matching the stored phonological form (e.g., the word tongue). To arrive at a correct pronunciation, developing readers must make the match between a decoded pronunciation and a word's correct pronunciation stored in memory. Developmentally, this matching process varies as a function of child skill (e.g., decoding, vocabulary) and word characteristics (e.g., spelling-to-pronunciation transparency, concreteness), with each being continuously distributed. Spelling-to-pronunciation transparency ratings represent a global measure of the ease of arriving at a word's correct pronunciation from its decoded pronunciation and in experimental studies has been shown to be a critical dimension in assessing the difficulty of a word for developing readers (e.g., Steacy et al., 2022a, 2022b). This study aimed to create a database of spelling-to-pronunciation transparency ratings for the 23,282 most frequently written English words, made available in the supplemental materials for future analyses. We asked adults to rate words' spelling-to-pronunciation transparency on a scale of 1-6 (1 = very easy to match, 6 = very difficult). Results of multiple regression analyses revealed variance in ratings to be unaccounted for by other word features, demonstrating the uniqueness of these ratings. Furthermore, words that are considered irregular, classified previously as strange, or contained at least one schwa received higher ratings, demonstrating strong associations between transparency and regularity. Lastly, these ratings significantly predicted both adult word naming time and child word reading accuracy above and beyond other word features known to predict reading.

Evolutionary multitasking for bidirectional adaptive codec: A case study on vehicle routing problem with time windows

The vehicle routing problem (VRP), an NP-hard problem of considerable complexity, pertains to the determination of optimal sequences of customer visits in an effort to minimize the total operational cost of vehicles. Conventional approaches to tackling VRP have primarily focused on optimizing each task independently, utilizing mathematical methodologies or evolutionary algorithms. Nevertheless, research exploring the application of the advanced concept of evolutionary multitasking (EMT) to address VRP remains limited. To enrich the body of knowledge in this field, our study presents an innovative EMT algorithm, dubbed EMT-RD. This algorithm employs a bidirectional adaptive codec to facilitate the transfer of information between real and discrete solutions. The EMT-RD algorithm permits the transfer of real and discrete solutions across varying tasks, utilizing an encoding rule that transforms information from real to discrete solutions for each task. Further, a decoding rule from discrete to real solutions generates search experiences, facilitating the transfer of knowledge between real solutions. The mechanism is capped off with an adaptive transfer strategy that instigates transfer operations across different tasks. Each task is tackled using a single-task optimization algorithm that employs an artificial bee colony algorithm. Through comprehensive experimentation, we found that our proposed EMT-RD algorithm outperforms competitors on 168 VRP with time windows multitasking instance pairs and four real-world problem pairs that were developed for this study. These results underscore the efficacy of the adaptive transfer strategy and bidirectional adaptive codec in addressing inter-task correlations when solving the VRP.

A Variant Iterated Greedy Algorithm Integrating Multiple Decoding Rules for Hybrid Blocking Flow Shop Scheduling Problem

This paper studies the hybrid flow shop scheduling problem with blocking constraints (BHFSP). To better understand the BHFSP, we will construct its mixed integer linear programming (MILP) model and use the Gurobi solver to demonstrate its correctness. Since the BHFSP exists parallel machines in some processing stages, different decoding strategies can obtain different makespan values for a given job sequence and multiple decoding strategies can assist the algorithm to find the optimal value. In view of this, we propose a hybrid decoding strategy that combines both forward decoding and backward decoding to select the minimal objective function value. In addition, a hybrid decoding-assisted variant iterated greedy (VIG) algorithm to solve the above MILP model. The main novelties of VIG are a new reconstruction mechanism based on the hybrid decoding strategy and a swap-based local reinforcement strategy, which can enrich the diversity of solutions and explore local neighborhoods more deeply. This evaluation is conducted against the VIG and six state-of-the-art algorithms from the literature. The 100 tests showed that the average makespan and the relative percentage increase (RPI) values of VIG are 1.00% and 89.6% better than the six comparison algorithms on average, respectively. Therefore, VIG is more suitable to solve the studied BHFSP.

A Novel Chaotic Image Encryption Scheme Armed with Global Dynamic Selection

Due to the equivalent keys revealed by a chosen-plaintext attack or a chosen-ciphertext attack, most of the existing chaotic image encryption schemes are demonstrated to be insecure. In order to improve security performance, some scholars have recently proposed the plaintext-related chaotic image encryption scheme. Although the equivalent effect of a one-time pad is achieved, an additional secure channel is required to transmit the hash values or other parameters related to the plaintext before the ciphertext can be decrypted at the receiving end. Its main drawback is that an absolutely secure channel is needed to transmit the information related to the plaintext, which is not feasible in practical applications. To further solve this problem, this paper proposes a chaotic image encryption scheme based on global dynamic selection of a multi-parallel structure. First, a chaotic sequence is employed to dynamically select DNA encoding rules. Secondly, the permutation with a multi-parallel structure is performed on the DNA-encoded matrix, and the DNA decoding rules are dynamically selected according to another chaotic sequence. Finally, the diffusion rules obtained by the ciphertext feedback mechanism are introduced to determine the dynamic diffusion. Compared with the existing local dynamic encryption schemes, the main advantage of this scheme is that it can realize global dynamic selection, so as to ensure that there is no equivalent key, and it can resist the chosen-ciphertext attack or chosen-plaintext attack and does not need an additional secure channel to transmit parameters related to plaintext, which is practical. A theoretical analysis and numerical experiments demonstrate the feasibility of the method.

Environmentally friendly strategy for hybrid flow shop scheduling with the unrelated parallel machines

With the increasing environmental pressure, reducing the environmental impact on hybrid flow shops (HFS) has attracted extensive attention because of its broad industrial applications. The selection of machines in the implementation of HFS is a complex decision-making process that hinders the optimization efficiency in shops. However, this issue has not been addressed thoroughly. In light of this, a multi-objective mathematical model is formulated for the minimization of makespan and energy consumption of the hybrid flow shop scheduling problem (HFSP). The environmental performance of machines is calculated by the proposed evaluation index and is ranked on the basis of the integrated entropy and fuzzy technique for order performance by similarity to ideal solution method. Moreover, to solve the multi-objective model of HFSP, an improved differential evolution algorithm with a heuristic active decoding rule that incorporates the ranking of environmental performance of machines into the iterative process of the algorithm is presented. Finally, a case study is presented to evaluate the effectiveness of the proposed method and to prove the feasibility of the ranking-based differential evolution algorithm (RBDE). The result shows that the proposed RBDE outperforms RBNSGA-II and RBPSO in searching for non-dominated solutions that can solve the environmental production of HFSP effectively.

Multilevel security for medical image using heterogeneous chaotic map and deoxyribonucleic acid sequence operations

SummaryIn telemedicine and e‐health system, the medical images are transmitted through telecommunication. In telecommunication, medical images are transmitted through open source networks. The hackers can tamper or add noise to medical images. Diagnosing the correct disease from the altered medical images is highly impossible. Hence indulge with security, confidentiality and integrity for medical images. In this work, heterogeneous hyper chaotic maps, deoxyribonucleic acid (DNA) cryptography and SHA‐512 is proposed in a new multilevel cryptosystem. The multilevel permutation is performed using heterogeneous chaotic map and zigzag transform. The multilevel diffusion is performed using DNA multiplication and DNA ADD operation. To verify the integrity the SHA‐512 is employed. All DNA coding, and DNA decoding rules are employed dynamically to generate the encrypted medical image. The introduced multilevel cryptosystem provide better security analysis for medical image transmission. The proposed method is implemented in MATLAB software. The performance of proposed approach is associated with existing approaches in terms of evaluating parameters like NPCR (number of pixel changing rate), UACI (unified average changed intensity), correlation coefficient and time taken in seconds. Hence it proves the performance and efficiency of the proposed method are high as compared to the existing methods. The proposed approach also improves the security level and offers integrity and confidentiality, and provide better medical image for encryption with less time complexity.

A Two-Population Cooperative Multiobjective Differential Evolution Algorithm for Batching Scheduling Problem

Batch processing machine (BPM) scheduling problem is a NP hard problem for it includes machine allocation, job grouping, and batch scheduling. In this paper, to address the BPM scheduling problem with unrelated parallel machine, a multiobjective algorithm based on multipopulation coevolution is proposed to minimize the total energy consumption and the completion time simultaneously. Firstly, the mixed integer programming model of the problem is established, and four heuristic decoding rules are proposed. Secondly, to improve the diversity and convergence of the algorithm, the population is divided into two populations: each of the populations evolves independently by using different decoding rules, and the two populations will communicate through a common external archive set every certain number of generations. Thirdly, an initialization strategy and a variable neighborhood search algorithm (VNS) are proposed to improve the overall performance of the algorithm. Finally, in order to evaluate the proposed algorithm, a large number of comparative experiments with the state-of-the-art multiobjective algorithms are carried out, and the experimental results proved the effectiveness of the proposed algorithm.

A discrete animal migration algorithm for dual-resource constrained energy-saving flexible job shop scheduling problem

This paper presents a discrete animal migration optimization (DAMO) to solve the dual-resource constrained energy-saving flexible job shop scheduling problem (DRCESFJSP), with the aim of minimizing the total energy consumption in the workshop. A job-resource-based two-vector encoding method is designed to represent the scheduling solution, and an energy-saving decoding approach is given based on the left-shift rule. To ensure the quality and diversity of initial scheduling solutions, a heuristic approach is employed for the resource assignment, and some dispatching rules are applied to acquire the operation permutation. In the proposed DAMO, based on the characteristics of the DRCESFJSP problem, the search operators of the basic AMO are discretized to adapt to the problem under study. An animal migration operator is presented based on six problem-based neighborhood structures, which dynamically changes the search scale of each animal according to its solution quality. An individual updating operator based on crossover operation is designed to obtain new individuals through the crossover operation between the current individual and the best individual or a random individual. To evaluate the performance of the proposed algorithm, the Taguchi design of experiment method is first applied to obtain the best combination of parameters. Numerical experiments are carried out based on 32 instances in the existing literature. Computational data and statistical comparisons indicate that both the left-shift decoding rule and population initialization strategy are effective in enhancing the quality of the scheduling solutions. It also demonstrate that the proposed DAMO has advantages against other compared algorithms in terms of the solving accuracy for solving the DRCESFJSP.

Construction and Characterization of Optical Orthogonal Codes (n,w,1) for Fast Frequency Hopping-Optical Code Division Multiple Access

This paper investigates a new combinatorial construction approach based on cyclic difference packings for the construction of an optical orthogonal code that is suitable as a time spreading sequence for fast frequency hopping optical code division multiple access (OCDM) systems. The proposed construction provides a solution to the electrical decoding delay problem when compared to its optical counterpart, as well as other optimization issues. The criteria for optimizing the performance of such an OCDMA system are provided, namely: the flexibility and simplicity in constructing the optimal code for any length and weight, a reduction in the encoding/decoding complexity that complies with changes in the fast frequency hopping system, and the provision of system transfer transparency, a decoding rule that exploits the embedded asymmetric error correcting capability of the code. Our neighbor difference approach refers to the partition of different solutions into sub-classes, given in the correlation matrix form. It takes into account both direct and recursive combinatorial code construction methods, and the resulting characteristics are evaluated accordingly. A performance analysis based on the OCDMA channel is given, and a comparison with other difference family solutions is performed.

A Non-Dominated Genetic Algorithm Based on Decoding Rule of Heat Treatment Equipment Volume and Job Delivery Date

This paper investigated the flexible job-shop scheduling problem with the heat treatment process. To solve this problem, we built an unified mathematical model of the heat treatment process and machining process. Up to now, this problem has not been investigated much. Based on the features of this problem, we are intended to minimize Cmax, maximize the space utilization rate of heat treatment equipment, and minimize the total delay penalty to optimize the scheduling. By taking the dynamic process arrival under consideration, this paper proposed a set of decoding rules based on the heat treatment equipment volume and job delivery date to achieve a hybrid dynamic scheduling solution during one scheduling procedure. When the utilization rate of heat treatment equipment volume is maximized, and the job delivery date is taken under consideration, it is preferred to minimize the number of workpiece batches in the same job, and reduce the waiting time of the pending job. In combination with the improved adaptive non-dominated genetic algorithm, we worked out the solution. Furthermore, we verified the effectiveness of the proposed decoding rules and improved algorithm through algorithm comparison and calculation results. Finally, a software system for algorithm verification and algorithm comparison was developed to verify the validity of our proposed algorithm.

Chaos-based image encryption strategy based on random number embedding and DNA-level self-adaptive permutation and diffusion

Some image encryption algorithms are difficult to resist the chosen-plaintext attack against special images, in order to solve this problem and improve the security of the algorithm, this paper proposes a novel image encryption scheme based on the chaotic system, random number embedding and DNA-level self-adaptive permutation and diffusion. The architecture of preprocessing, permutation and diffusion is adopted. Firstly, an image preprocessing based on random number embedding (IPRNE) is presented, specifically, embed random numbers into the plain image, and then perform partition XOR operation on random numbers and their surrounding pixels to preprocess plain image. The random numbers are generated by a 4D memristive hyperchaotic system, and their embedding positions are controlled by the pixel sums of plain images. Secondly, the obtained image is encoded into a DNA matrix by use of a DNA encoding rule, and then a DNA-level self-adaptive permutation and diffusion processes are successively performed on it. Further, after decoding the diffused matrix, the cipher image is obtained. Besides, the feature information of DNA sequences of plain image is applied for disturbing the permutation and diffusion phases, which may be extracted automatically in the decryption process, and thus additional transmission and storage are avoided. Moreover, the plain image information and hyperchaotic system are integrated to design the DNA encoding /decoding rule for the plain image and mask matrix, and this can enhance the ability of the algorithm to resist chosen-plaintext attack. Experimental results and security analyses demonstrate that the proposed encryption is secure and effective, and it can be applied for image secure communication.

Stochastic multi-objective integrated disassembly-reprocessing-reassembly scheduling via fruit fly optimization algorithm

Remanufacturing end-of-life (EOL) products is an important approach to yield great economic and environmental benefits. A remanufacturing process usually contains three shops, i.e., disassembly, processing and assembly shops. EOL products are dissembled into multiple components in a disassembly shop. Reusable components are reprocessed in a processing shop, and reassembled into their corresponding products in an assembly shop. To realize an overall optimization, we have to integrate them together when making decisions. In practice, a decision-maker usually has to optimize multiple criteria such as cost-related and service-oriented objectives. Additionally, we cannot accurately acquire the detail of EOL products due to their various usage processes. Therefore, multi-objective and uncertainty need to be considered simultaneously in an integrated disassembly-reprocessing-reassembly scheduling process. This work investigates a stochastic multi-objective integrated disassembly-reprocessing-reassembly scheduling problem to achieve the expected makespan and total tardiness minimization. To handle this problem, this work develops a multi-objective discrete fruit fly optimization algorithm incorporating a stochastic simulation approach. Its search techniques are designed according to this problem’s features from five aspects, i.e., solution representation, heuristic decoding rules, smell-searching, vision-searching, and genetic-searching. Simulation experiments are conducted by adopting twenty-five instances to verify the performance of the proposed approach. Nondominated sorting genetic algorithm II, bi-objective multi-start simulated annealing method, and hybrid multi-objective discrete artificial bee colony are chosen for comparisons. By analyzing the results with three performance metrics, we can find that the proposed approach performs better on all the twenty-five instances than its peers. Specifically, it outperforms them by 6.45%–9.82%, 6.91%–17.64% and 1.19%–2.76% in terms of performance, respectively. The results confirm that the proposed approach can effectively and efficiently tackle the investigated problem.

An image encryption algorithm based on 3-D DNA level permutation and substitution scheme

In this paper, an image encryption algorithm based on 3-D DNA level permutation and substitution scheme is proposed. In order to improve the security level of the image encryption, a 3-D DNA level hybrid permutation scheme using chaotic sequence sorting and 3-D cat map is presented to effectively shuffle the element positions, a novel 3-D DNA level substitution method based on random number is given to directly change the elements of the 3-D DNA matrix, and dynamic and random DNA encoding rules and DNA decoding rules are designed to upgrade the randomness of the encryption results. Moreover, a 6-D hyperchaotic system is used to generate the chaotic sequence for all the encryption processes, and SHA 256 hash value of the plain image is utilized to compute the initial values of chaotic system and system parameters of the 3-D cat map. Simulation results and performance analyses demonstrate that the proposed encryption scheme has large key space, high key sensitivity and may resist against some typical attacks, and it may effectively secure the secret image information.

A new color image encryption scheme based on DNA encoding and spatiotemporal chaotic system

In this paper, a new color image encryption scheme based on DNA operations and spatiotemporal chaotic system is presented. Firstly, to hide the distribution information of the plain image, we convert the plain image into three DNA matrices based on the DNA random encoding rules. Then, the DNA matrices are combined into a new matrix and is permutated by a scramble matrix generated by mixed linear-nonlinear coupled map lattices (MLNCML) system. In which, the key streams are associated with the secret keys and plain image, which can ensure our cryptosystem plain-image-dependent and improve the ability to resist known-plaintext or chosen-plaintext attacks. Thereafter, to resist statistical attacks, the scrambled matrix is decomposed into three matrices and diffused by DNA deletion-insertion operations. Finally, the three matrices are decoded based on DNA random decoding rules and recombined to three channels of the cipher image. Simulation results demonstrate that the proposed image cryptosystem has good security and can resist various potential attacks.

Paradoxical Rules of Spike Train Decoding Revealed at the Sensitivity Limit of Vision

All sensory information is encoded in neural spike trains. It is unknown how the brain utilizes this neural code to drive behavior. Here, we unravel the decoding rules of the brain at the most elementary level by linking behavioral decisions to retinal output signals in a single-photon detection task. A transgenic mouse line allowed us to separate the two primary retinal outputs, ON and OFF pathways, carrying information about photon absorptions as increases and decreases in spiking, respectively. We measured the sensitivity limit of rods and the most sensitive ONand OFF ganglion cells and correlated these results with visually guided behavior using markerless head and eye tracking. We show that behavior relies only on the ON pathway even when the OFF pathway would allow higher sensitivity. Paradoxically, behavior does not rely on the spike code with maximal information but instead relies on a decoding strategy based on increases in spiking.

Gaussian Intersymbol Interference Channels With Mismatch

This paper considers the problem of channel coding over Gaussian intersymbol interference (ISI) channels with a given decoding rule. Specifically, it is assumed that the mismatched decoder has an incorrect assumption on the channel impulse response. The mismatch capacity is the highest achievable rate for a given decoding rule. The existing achievable rates for channels and decoding metrics with memory (as in our model) are currently available only in the form of multi-letter expressions that cannot be calculated. Consequently, they provide little insight on the mismatch problem. In this paper, we derive the computable formulas of achievable rates and discuss some implications of our results. Our achievable rates are based on two ensembles: the ensemble of codewords generated by an autoregressive process and the ensemble of codewords drawn uniformly over a “type class” of real-valued sequences. We provide a few numerical results of our achievable rates, as functions of the mismatched ISI parameters. Finally, we compare our results with universal decoders which are designed outside the true class of channels that we consider in this paper.

A color image cryptosystem based on dynamic DNA encryption and chaos

• A color image cryptosystem based on dynamic DNA encryption and a four-wing hyperchaotic system is presented. • Dynamic DNA encoding and decoding rules for all the pixels are generated and dependent on the plain image. • A novel diffusion mechanism based on random numbers related to plaintext (DMRNRP) is introduced to diffuse the DNA sequences of the plain image. • The image encryption method is highly sensitive to the plain image. • Experimental results demonstrate that the proposed encryption algorithm has good security performance. This paper presents a color image cryptosystem based on dynamic DNA encryption and chaos. The color plain image is firstly decomposed into red, green and blue components, and then a simultaneous intra-inter-component permutation mechanism dependent on the plaintext (SCPMDP) is introduced to shuffle them. Secondly, convert the recombined permutated components into a DNA matrix by a DNA encoding rule, and subsequently, different from the traditional DNA sequence operations according to the law of binary calculation, a diffusion mechanism based on random numbers related to plaintext (DMRNRP) is presented to diffuse it. Further, transform the diffused DNA matrix into a decimal one according to a DNA decoding rule, and divide it into three equal images. Finally, to enhance security of the image cryptosystem, the second confusion scheme is applied to respectively scramble images, and the color cipher image is gotten. A four-wing hyperchaotic system is used to provide pseudo-random chaotic sequences, SHA 384 hash function of the plain image and external parameters are combined to compute its initial values, and one-time-pad encryption policy makes the proposed encryption effectively resist plaintext attacks. Experimental results and security analysis demonstrate that our encryption algorithm has good performance and may resist against various typical attacks.

Mismatched Multi-Letter Successive Decoding for the Multiple-Access Channel

This paper studies channel coding for the discrete memoryless multiple-access channel with a given (possibly suboptimal) decoding rule. A multi-letter successive decoding rule depending on an arbitrary non-negative decoding metric is considered, and achievable rate regions and error exponents are derived both for the standard MAC (independent codebooks), and for the cognitive MAC (one user knows both messages) with superposition coding. In the cognitive case, the rate region and error exponent are shown to be tight with respect to the ensemble average. The rate regions are compared with those of the commonly considered decoder that chooses the message pair maximizing the decoding metric, and numerical examples are given for which successive decoding yields a strictly higher sum rate for a given pair of input distributions.

Color image DNA encryption using NCA map-based CML and one-time keys

In this paper, we introduce a novel color image encryption algorithm based on DNA sequence operations, one-time keys and the spatiotemporal chaos. Firstly, the key streams are generated by the NCA map-based CML, where the hash function SHA-256 is used to update the system parameters and initial conditions combining with the plain-image and the secret keys. Secondly, decompose the plain-image into the red, green, blue components, and convert them randomly into three DNA matrices by the DNA encoding rules. Further, combine three DNA matrices into a new DNA matrix, and then perform the row-wise and column-wise permutations on it. Thirdly, divide the shuffled DNA matrix into three equal blocks and implement the DNA addition, subtraction and XOR operations on these DNA blocks. Finally, transform the DNA matrices into the decimal matrices separately according to the DNA decoding rules. To enhance the security of the cryptosystem, a diffusion process is further carried out by using the key streams. Thus, the resulting cipher-image is attained. Experimental results and security analysis show that the presented encryption algorithm has a good encryption effect and can resist various typical attacks.

Lossless chaotic color image cryptosystem based on DNA encryption and entropy

Based on deoxyribonucleic acid (DNA) coding and two excellent low-dimensional chaotic systems, a new color image cryptosystem is proposed in this paper. The presented image cryptosystem consists of four processes: key streams generation process, DNA sequences confusion process, DNA sequences diffusion process and pixel-level diffusion process. In the first stage, two simple improved chaotic systems and the information entropy of the plain-image are together employed to generate the pseudorandom key streams. Then, the original image is converted into the DNA sequence matrices by the DNA encoding rules, and the binary key streams are used to permute the DNA matrices. The third process performs a row and column diffusion processes on the scrambled DNA matrices by the key streams and DNA XOR operation. Finally, the DNA matrices are transformed into the encrypted image via the DNA decoding rules, and a ciphertext diffusion in crisscross pattern is further adopted to strengthen the security and sensitivity of the cryptosystem. Thus, the resulting cipher-image is obtained. Experimental results and security analysis have demonstrated the excellent performance of our proposed algorithm in image encryption.