A Two-Layer Encoding Learning Swarm Optimizer Based on Frequent Itemsets for Sparse Large-Scale Multi-Objective Optimization

Traditional large-scale multi-objective optimization algorithms(LSMOEAs)encounter difficulties when dealing with sparse large-scale multi-objective optimization problems(SLM-OPs)where most decision variables are zero.As a result,many algorithms use a two-layer encoding approach to optimize binary variable Mask and real variable Dec separately.Nevertheless,existing optimizers often focus on locating non-zero variable posi-tions to optimize the binary variables Mask.However,approxi-mating the sparse distribution of real Pareto optimal solutions does not necessarily mean that the objective function is optimized.In data mining,it is common to mine frequent itemsets appear-ing together in a dataset to reveal the correlation between data.Inspired by this,we propose a novel two-layer encoding learning swarm optimizer based on frequent itemsets(TELSO)to address these SLMOPs.TELSO mined the frequent terms of multiple particles with better target values to find mask combinations that can obtain better objective values for fast convergence.Experi-mental results on five real-world problems and eight benchmark sets demonstrate that TELSO outperforms existing state-of-the-art sparse large-scale multi-objective evolutionary algorithms(SLMOEAs)in terms of performance and convergence speed.

A Multi-Stream Scrambling and DNA Encoding Method Based Image Encryption

Information security has emerged as a key problem in encryption because of the rapid evolution of the internet and networks.Thus,the progress of image encryption techniques is becoming an increasingly serious issue and considerable problem.Small space of the key,encryption-based low confidentiality,low key sensitivity,and easily exploitable existing image encryption techniques integrating chaotic system and DNA computing are purposing the main problems to propose a new encryption technique in this study.In our proposed scheme,a three-dimensional Chen’s map and a one-dimensional Logistic map are employed to construct a double-layer image encryption scheme.In the confusion stage,different scrambling operations related to the original plain image pixels are designed using Chen’s map.A stream pixel scrambling operation related to the plain image is constructed.Then,a block scrambling-based image encryption-related stream pixel scrambled image is designed.In the diffusion stage,two rounds of pixel diffusion are generated related to the confusing image for intra-image diffusion.Chen’s map,logistic map,and DNA computing are employed to construct diffusion operations.A reverse complementary rule is applied to obtain a new form of DNA.A Chen’s map is used to produce a pseudorandom DNA sequence,and then another DNA form is constructed from a reverse pseudorandom DNA sequence.Finally,the XOR operation is performed multiple times to obtain the encrypted image.According to the simulation of experiments and security analysis,this approach extends the key space,has great sensitivity,and is able to withstand various typical attacks.An adequate encryption effect is achieved by the proposed algorithm,which can simultaneously decrease the correlation between adjacent pixels by making it near zero,also the information entropy is increased.The number of pixels changing rate(NPCR)and the unified average change intensity(UACI)both are very near to optimal values.

On the sampling strategies and models for measuring diffusion exchange with a double diffusion encoding sequence

Water exchange between the different compartments of a heterogeneous specimen can be characterized via diffusion magnetic resonance imaging(dMRI).Many analysis frameworks using dMRI data have been proposed to describe exchange,often using a double diffusion encoding(DDE)stimulated echo sequence.Techniques such as diffusion exchange weighted imaging(DEWI)and the filter exchange and rapid exchange models,use a specific subset of the full space DDE signal.In this work,a general representation of the DDE signal was employed with different sampling schemes(namely constant b1,diagonal and anti-diagonal)from the data reduction models to estimate exchange.A near-uniform sampling scheme was proposed and compared with the other sampling schemes.The filter exchange and rapid exchange models were also applied to estimate exchange with their own subsampling schemes.These subsampling schemes and models were compared on both simulated data and experimental data acquired with a benchtop MR scanner.In synthetic data,the diagonal and near-uniform sampling schemes performed the best due to the consistency of their estimates with the ground truth.In experimental data,the shifted diagonal and near-uniform sampling schemes outperformed the others,yielding the most consistent estimates with the full space estimation.The results suggest the feasibility of measuring exchange using a general representation of the DDE signal along with variable sampling schemes.In future studies,algorithms could be further developed for the optimization of sampling schemes,as well as incorporating additional properties,such as geometry and diffusion anisotropy,into exchange frameworks.

The Dissemination of Chinese Tea Culture Based on Encoding/Decoding Theory

Tea has a history of thousands of years in China and it plays an important role in the working-life and daily life of people.Tea culture rich in connotation is an important part of Chinese traditional culture,and its existence and development are also of great significance to the diversified development of world culture.Based on Stuart Hall’s encoding/decoding theory,this paper analyzes the problems in the spreading of Chinese tea in and out of the country and provides solutions from the perspective of encoding,communication,and decoding.It is expected to provide a reference for the domestic and international dissemination of Chinese tea culture.

The Dissemination of Intangible Cultural Heritage Along Beijing-Hangzhou Canal Based on Encoding/Decoding Theory

The Beijing-Hangzhou Grand Canal carries a wealth of Chinese cultural symbols,showing the lifestyle and wisdom of working people through ages.The preservation and inheritance of its intangible cultural heritage can help to evoke cultural memories and cultural identification of the Canal and build cultural confidence.This paper applies Stuart Hall’s encoding/decoding theory to analyze the dissemination of intangible heritage tourism culture.On the basis of a practical study of the villages along the Beijing-Hangzhou Grand Canal,this paper analyses the problems in the transmission of its intangible cultural heritage and proposes specific methods to solve them in four processes,encoding,decoding,communication,and secondary encoding,in order to propose references for the transmission of intangible heritage culture at home and abroad.

The Application and Adaptation of the Two Sources of Code and Natural Encoding Method for Designing a Model of Microprogram Control Unit with Base Structure

The article presents a modification to the method which applies two sources of data. The modification is depicted on the example of a compositional microprogram control unit (CMCU) model with base structure implemented in the complex programmable logic devices (CPLD). First, the conditions needed to apply the method are presented, followed by the results of its implementation in real hardware.

On the Manipulation of the Selectivity of Encoding and Decoding overthe Translator's Subjectivity

The translation activity is a process of the interlinguistic transmission of information realized by the information encoding and decoding.Encoding and decoding,cognitive practices operated in objective contexts,are inevitably of selectivity ascribing to the restriction of contextual reasons.The translator as the intermediary agent connects the original author(encoder)and the target readers(decoder),shouldering the dual duties of the decoder and the encoder,for which his subjectivity is irrevocably manipulated by the selectivity of encoding and decoding.

Expression and Chromosomal Mapping of Mouse Gpx2 Gene Encoding the Gastrointestinal Form of Glutathione Peroxidase, GPX-GI

GPX-GI is a cytosolic tetrameric Se-dependent glutathione peroxidase, similar in properties to GPX-1. Unlike the almost ubiquitous GPX-1, GPX-GI is mainly expressed in the epithelium of gastrointestinal tract. GPX-GI contributes to at least fifty percent of GPX activity in rodent small intestmal epithelium. The total GPX activity consists of at least 70% of selenium-dependent GPX activity in this compartment.By analyzing a panel of mouse mterspecies DNA from the Jackson Laboratory's backcross resource,we mapped Gpx2 gene to mouse chromosome 12 between D12Mit4 and D12Mit5, near the Ccs1 locus which contains a colon cancer susceptibility gene. A pseudogene, Gpx2-ps is mapped to mouse chromosome 7.Comparison of Gpx2 gene expression in three pairs of C57BL/6Ha and ICR/Ha mice which are respectively resistant and sensitive to dimethylhydrazine-induced colon cancer, we found a higher Gpx2 mRNA level in C57BL/6Ha colon than ICR/Ha colon. Interestingly, a lower level of GPX activity is found in the resistant strain of mice. Because GPX-1 has three times higher specific activity than GPX GI, our data suggest that the decreased GPX activity may result from a higher level of Gpx2 gene expression in those cells co-express GPx1 gene

New Algorithm for Binary Connected-Component Labeling Based on Run-Length Encoding and Union-Find Sets

Based on detailed analysis of advantages and disadvantages of the existing connected-component labeling （CCL） algorithm,a new algorithm for binary connected components labeling based on run-length encoding （RLE） and union-find sets has been put forward.The new algorithm uses RLE as the basic processing unit,converts the label merging of connected RLE into sets grouping in accordance with equivalence relation,and uses the union-find sets which is the realization method of sets grouping to solve the label merging of connected RLE.And the label merging procedure has been optimized：the union operation has been modified by adding the ＂weighted rule＂ to avoid getting a degenerated-tree,and the ＂path compression＂ has been adopted when implementing the find operation,then the time complexity of label merging is O（nα（n））.The experiments show that the new algorithm can label the connected components of any shapes very quickly and exactly,save more memory,and facilitate the subsequent image analysis.

ANALYSIS OF SPECTRAL PHASE ENCODING OCDMA SYSTEM WITH PSEUDORANDOM CODING

Multiple access interference (MAI) is the most serious interference in spectral phase encoding optical code division multiple access (SPE OCDMA) systems. This paper focuses on the behavior of MAI in SPE OCDMA systems with pseudorandom coding. The statistical expectation of multi access interference (MAI) is derived and plotted. The results confirm that MAI can be suppressed effectively by pseudorandom coding with m sequences.

Position Encoding Based Convolutional Neural Networks for Machine Remaining Useful Life Prediction

Accurate remaining useful life(RUL)prediction is important in industrial systems.It prevents machines from working under failure conditions,and ensures that the industrial system works reliably and efficiently.Recently,many deep learning based methods have been proposed to predict RUL.Among these methods,recurrent neural network(RNN)based approaches show a strong capability of capturing sequential information.This allows RNN based methods to perform better than convolutional neural network(CNN)based approaches on the RUL prediction task.In this paper,we question this common paradigm and argue that existing CNN based approaches are not designed according to the classic principles of CNN,which reduces their performances.Additionally,the capacity of capturing sequential information is highly affected by the receptive field of CNN,which is neglected by existing CNN based methods.To solve these problems,we propose a series of new CNNs,which show competitive results to RNN based methods.Compared with RNN,CNN processes the input signals in parallel so that the temporal sequence is not easily determined.To alleviate this issue,a position encoding scheme is developed to enhance the sequential information encoded by a CNN.Hence,our proposed position encoding based CNN called PE-Net is further improved and even performs better than RNN based methods.Extensive experiments are conducted on the C-MAPSS dataset,where our PE-Net shows state-of-the-art performance.

Therapeutic effect of intravesical or intratumoral injection of oncolysate transfected with recombinant vaccinia virus encoding human IL-2 gene on murine melanoma model

Oncolysate, a debris of tumor cells, has been provento be effective in tumor active immunotherapy, it wasreported that the vaccinia virus, especially recombinantvaccinia viruses encoding human IL-2 (rVV-IL-2 ),enhanced the immunogenicity of transfected tumor cells.In this experiment, the murine melanoma cell B16-F10oncolysates trans fected by rVV-IL-2 (IL-2VBO) wereused as vaccine. The IL-2VBO or TK-VBO was preparedby incubating B16-F10 cells with rVV-IL-2 or rVV-TK

Fast encoding algorithm for vector quantization based on subvector L_2-norm

A fast encoding algorithm based on the mean square error （MSE） distortion for vector quantization is introduced. The vector, which is effectively constructed with wavelet transform （WT） coefficients of images, can simplify the realization of the non-linear interpolated vector quantization （NLIVQ） technique and make the partial distance search （PDS） algorithm more efficient. Utilizing the relationship of vector L2-norm and its Euclidean distance, some conditions of eliminating unnecessary codewords are obtained. Further, using inequality constructed by the subvector L2-norm, more unnecessary codewords are eliminated. During the search process for code, mostly unlikely codewords can be rejected by the proposed algorithm combined with the non-linear interpolated vector quantization technique and the partial distance search technique. The experimental results show that the reduction of computation is outstanding in the encoding time and complexity against the full search method.

Structured Light 3D Vision Based on Laser Scanning Space-encoding and Its Synchro Control

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Encoding Methods of Spectral Vector in Hyperspectral Romote Sensing Image

Taking into account the demands of hyperspectral remote sensing(RS) image retrieval and processing, some encoding methods of spectral vector including direct encoding, feature-based encoding and tree-based encoding methods are proposed and compared. In direct encoding, based on the analysis of binary encoding and quad-value encoding, decimal encoding is proposed. It is proved that quad-value encoding and decimal encoding are suitable to fast processing and retrieval. In absorption feature-based encoding method, five common metrics are compared. Because locations of reflection/absorption features are sensitive to noise, this method is not very effective in retrieval. In tree-based encoding methods, bitree, quadtree, octree and hextree are proposed and discussed. It is proved that 2-level octree and 2-level hextree are more effective than bitree and quadtree. Finally, quad-value encoding, decimal encoding, 2-level octree and 2-level hextree are proposed in spectral vectors encoding, similarity measure and hyperspectral RS image retrieval.

Construction of Plasmids Expressing Sars-CoV Encoding Proteins and Their Effects on Transcription of Hfgl2 Prothrombinase

SARS coronavirus （SARS-CoV） is the etiologic agent of severe acute respiratory syndrome. The aim of this study was to construct Sars-CoV membrane （M）, nucleocapsid （N） and spike 2 （$2） gene eukaryotic expression plasmids, and identify their expression in vitro. Gene fragments encoding N protein, M protein and $2 protein of SARS-CoV were amplified by PCR using cDNA obtained from lung samples of SARS patients as template, and subcloned into pcDNA3.1 vector to form eukaryotic expression plasmids. SARS-CoV protein eukaryotic expression plasmids were transfected respectively into CHO cells. Immunohistochemistry was employed to detect the expression of the structural proteins of SARS-CoV in transfected cells. SARS-CoV protein eukaryotic expression plasmids were successfully constructed by identification with digestion of restriction enzymes and sequencing. M, N and S2 proteins of SARS-CoV were detected in the cytoplasm of transfected CHO cells. It was concluded that these recombinant eukaryotic expression plasmids were constructed successfully, and SARS-CoV encoding proteins could activate transcription and expression of hfgl2 gene.

Improve Fractal Compression Encoding Speed Using Feature Extraction and Self-organization Network

Image compression consists of two main parts: encoding and decoding. One of the important problems of the fractal theory is the long encoding implementation time, which hindered the acceptance of fractal image compression as a practical method. The long encoding time results from the need to perform a large number of domain-range matches, the total encoding time is the product of the number of matches and the time to perform each match. In order to improve encoding speed, a hybrid method combining features extraction and self-organization network has been provided, which is based on the feature extraction approach the comparison pixels by pixels between the feature of range blocks and domains blocks. The efficiency of the new method was been proved by examples.

Cloning and Characterization of a Tau Glutathione S-transferase Subunit Encoding Gene in Gossypium hirsutum

A predicted tau glutathione S-transferase(GST) subunit encoding gene,named GhGST,was isolated from Gossypium hirsutum with RACE method from SSH library based on Verticillium

Factors involved in memory encoding and their implications for the memory performance of older adults and people with mild cognitive impairment

Rehabilitation of episodic memory declines typically focuses on alleviating the demand for recall and improving the retrieval process. Modulating the encoding is not commonly practiced, but may nevertheless be important. Seventeen event-related potential (ERP) studies interpreted using the subsequent memory effect, an index of successful encoding, are reviewed and the factors involved in encoding are discussed. The nature of the materials used for testing, modes of encoding, and the nature of the retrieval task are highlighted as important factors. Meaningful materials and processing information semantically enhance encoding to episodic memory. The stud-ies reviewed reveal that older persons process information more uniformly without elaboration compared with their younger counterparts. Although people with mild cognitive impairment have encoding and retrieval deficits, an elaborative type of encoding training that draws on successful encoding factors may help to improve memory performance.

Aerial Video Encoding Optimization Based On x264

x264 video codec uses lots of new video encoding technology based on H.264/AVC video encoding standard which enhances compression efficiency. However this results in so heavy computation that the x264 codec is not fit for real-time encoding application of high resolution video. This paper analyses the character of aerial video and then opti-mizes the inter-frame mode decision and motion estimation in x264 codec according to its character by reducing a lot of unnecessary computation. In the result, about 19% computation and encoding time is reduced with total bits and PSNR decreasing lightly.