The MSDIN family in amanitin-producing mushrooms and evolution of the prolyl oligopeptidase genes by Hong Luo, Qing Cai, Yunjiao Lüli, Xuan Li, Rohita Sinha, Heather E. Hallen-Adams, Zhu L. Yang

“…The toxin MSDIN genes encoding amatoxins or phallotoxins from the three genera were compared, and a phylogenetic tree constructed. …”
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Hybrid Tree Tensor Networks for Quantum Simulation by Julian Schuhmacher, Marco Ballarin, Alberto Baiardi, Giuseppe Magnifico, Francesco Tacchino, Simone Montangero, Ivano Tavernelli

“…Hybrid tensor networks (hTNs) offer a promising solution for encoding variational quantum states beyond the capabilities of efficient classical methods or noisy quantum computers alone. …”
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Primary extranodal NK/T cell lymphoma of stomach: A case report and review of literature by Prashant Mane, Prashant Ramteke, Anand Singh, Ajay Gogia, Saumyaranjan Mallick

“…Partial gastrectomy done and histopathology showed transmural infiltration by intermediate size atypical lymphoid cells which are immunopositive for CD3, CD56, TIA, EBV-encoded RNA (EBER) and negative for CD4, CD8, CD20. …”
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Human activity recognition algorithm based on the spatial feature for WBAN by Chi JIN, Zhijun LI, Dayang SUN, Fengye HU

“…Traditional image-based activity recognition algorithms have some problems,such as high computational cost,numerous blind spots and easy privacy leakage.To solve the problem above,the CCLA (convolution-convolutional long short-term memory-attention) activity recognition algorithm based on the acceleration and gyroscope data was proposed.The convolutional neural network was used to extract spatial features of activity data and got the hidden time series information from the convolutional long short-term memory network.Simulating human brain selecting attention mechanism,attention-encoder was constructed to extract the spatial and temporal features at a higher level.The CCLA algorithm was tested on UCI-HAPT (university of California Irvine-smartphone-based recognition of human activities and postural transitions) public data set,and realized the classification of 12 types of activity with the accuracy of 93.27%.…”
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Data update algorithm based on secure network coding in cloud environment by Hao WU, Cheng-zhe LAI, Jiu-lun FAN, Jian-hua LIU

“…In the cloud environment for data storage,the use of secure network coding technology can be a good solution to the data privacy and reliability issues.However,each coding block usually has a high correlation after network coding,very few updates to the file need to be re-encoded which is extremely easy to cause information leakage and serious consumption of system resources.To solve this problem,a network coding cloud storage data updating algorithm was proposed.Just by sending files change difference matrix,the storage node could update parts of the coding block accordingly which could complete the entire update files.Experimental results show that compared with RS coding and Tornado coding,the algorithm can not only ensure data security,but also greatly improve the efficiency of data update and data reconstruction.…”
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Design of the Gear Fault Test System based on the Method of Transmission Error Detection by Wang Bolei, Cui Yanping, Lu Zhaojing

“…The method of transmission error detection is applied to gear fault diagnosis,the transmission error signal of the gear system is obtained by measuring pulse width time of the gearbox shaft angular encoder output two square wave pulse.Secondly,the transmission error signal is decomposed into a finite number of intrinsic mode components（IMF） by the method of empirical mode decomposition,and then the IMF component containing the most dominant fault information are filtrated to merged into a new signal.Finally,the order analysis and spectrum analysis on the new signal is carried out,the fault characteristics are obtained and gear fault diagnosis is realized.The designed two channel data acquisition card is applied to build up the gear fault analysis test system based on the method of transmission error detection.The experiment results show that the gear fault analysis test system can be effectively diagnose the gear fault.…”
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Fast and low-complexity video down-sizing transcoder by Zhuo-yi LV, Ke-bin JIA, Wan-chi WIU

“…An efficient mode decision scheme for down-sizing video transcoding in H.264 using support vector machines (SVM)was proposed.In order to reduce the high computationa complexity of using conventional mode decision in the H.264 re-encoder,the proposed scheme used SVM to exploit the correlation between coding information extracted from the input high-resolution bit-stream and the coding modes of macro-blocks in down-sized video frames.The key techniques of training and predicting SVM including feature vector and kernel function were studied and then the SVM model was trained.After the hierarchical SVM classifier,improbable modes were eliminated and only a small number of candidate modes were carried out using the RDO operations.Hence,remarkable computing time could be saved,up to 67.31%,while maintaining nearly the same quality of the transcoded pictures.…”
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RESEARCH ON BEARING FAULT DIAGNOSIS UNDER UNBALANCED DATA SET BASED ON IWAE (MT) by LI MengNan, LI Kun, WU Cong

“…Aiming at the low accuracy with unbalanced data sets in existing bearing fault diagnosis methods, we proposed a bearing fault diagnosis method based on importance weighted auto-encoder（IWAE） in unbalanced data sets. It was trained by minority samples, and the generated samples were added into original data sets to obtain balanced data sets. …”
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Opportunistic network coding based on prediction by Wai-xi LIU, Shun-zheng YU, Ying GAO, Xiao HU

“…Since pure theory network coding had some drawbacks in practical network,however current opportunistic network coding fully depends on overheard information.Thus,in a radically different way from network coding optimization,a novel opportunistic network coding scheme was proposed which was based on prediction (ONCP).The main idea of ONCP was firstly,arrival time of next packet in a node was predicted for the self-similarity of network traffic;:secondly,encoding time,waiting time for coding,transmission time and other factors were taken into account together to determine whether this packet was coded in this node.A theorem—maximum waiting time for was proved network coding in order to obtain throughput gain.Simulation results show that ONCP improves throughput by 15% compared to pure theory network coding and by 21% compared to traditional store-forward.ONCP can also effectively reduce energy consumption while improving throughput.…”
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Modeling Multicellular Systems Using Subcellular Elements by T. J. Newman

“…We also discuss efficient algorithms for encoding the model, and give an example of a simulation of an epithelial sheet. …”
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Some Problems in Proving the Existence of the Universal Common Ancestor of Life on Earth by Takahiro Yonezawa, Masami Hasegawa

“…We show that the alignment gives a strong bias for the common ancestor hypothesis, and we provide an example that Theobald's method supports a common ancestor hypothesis for two apparently unrelated families of protein-encoding sequences (cytb and nd2 of mitochondria). …”
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Waveform interpolation speech coding algorithm at 2.4kbit/s based on wavelet transform by WANG Jing, KUANG Jing-ming, XIE Xiang

“…A waveform interpolation speech coding algorithm at 2.4kbit/s based on wavelet transform was proposed,in which characteristic waveform decomposition and reconstruction is processed using biorthogonal wavelet filters.At the encoder,the alignment operation was removed and the amplitude spectrum is decomposed without phase spectrum.Because of the wavelet compression,only the amplitude spectrum of last layer is transmitted.At the decoder,different scale space is reconstructed separately and random or fixed phase was combined to the spectrum based on voice degree at the last.Additionally,based on the time-variable feature of speech,voiced degree flag of each subframe was introduced to indicate the spectrum selection and quantization.Subjective R-A/B listening tests indicated that the synthesis speech quality of the 2.4kbit/s WT-CWI coding algorithm is better than that of standard 2.4kbit/s MELP coder and FS1016 4.8kbit/s CELP coder and is better than traditional 3.8kbit/s CWI coder.…”
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Spatio-temporal error concealment scheme based on H.264/AVC by FENG Bin, ZHU Guang-xi, LIU Wen-yu

“…In order to reduce the influence of transmission errors on the reconstructed image quality in decoder,a novel spatio-temporal error concealment scheme was proposed.A hypothesis was made that the corrupted macro blocks（MB） distributed randomly in the frame which is sufficiently realistic and extensively used in literature.Firstly a directional in-terpolation based spatial error concealment algorithm was used which introduces a method similar with the intra predic-tion in the encoder.Then an 8×8 block based enhanced temporal error concealment algorithm was proposed,which im-proved the ability to deal with the high motions areas.Finally,a switch strategy between spatial and temporal error conceal-ment algorithm was addresse.It chooses an appropriate algorithm based on the adjacent MB coding modes.Experimental results demonstrate that the proposed scheme is prior to the algorithms in H.264/AVC both in objective and subjective quality.…”
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Multi-channel based edge-learning graph convolutional network by Shuai YANG, Ruiqin WANG, Hui MA

“…Usually the edges of the graph contain important information of the graph.However, most of deep learning models for graph learning, such as graph convolutional network (GCN) and graph attention network (GAT), do not fully utilize the characteristics of multi-dimensional edge features.Another problem is that there may be noise in the graph that affects the performance of graph learning.Multilayer perceptron (MLP) was used to denoise and optimize the graph data, and a multi-channel learning edge feature method was introduced on the basis of GCN.The multi-dimensional edge attributes of the graph were encoded, and the attributes contained in the original graph were modeled as multi-channel.Each channel corresponds to an edge feature attribute to constrain the training of graph nodes, which allows the algorithm to learn multi-dimensional edge features in the graph more reasonably.Experiments based on Cora, Tox21, Freesolv and other datasets had proved the effectiveness of denoising methods and multi-channel methods.…”
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On the Principles and Decisions of New Word Translation in Sino-Japan Cross-Border e-Commerce: A Study in the Context of Cross-Cultural Communication by Gaowa Sulun

“…Then, the two modal information are encoded separately, and the proportion of visual information in the whole multimodal information is controlled by a gating network. …”
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Effective retransmission in network coding for TCP by Jing CHEN, Xue-peng SONG, Fang LIU

“…Therefore a novel network coding retransmission scheme which uses the implicit information of seen scheme to acquire the number of packets the receiver needs for decoding packets is proposed, the encoding rules of retransmission to let a part of packets decodable in advance are changed. …”
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A Hybrid Deep Learning Method for the Estimation of the State of Health of Lithium-Ion Batteries by Shuo Cheng

“…The new scheme adopts a VIT to extract features from the battery measured data and incorporates a GRU network to mitigate the limitations of the VIT caused by positional encoding. The resulting VIT-GRU network is designed to comprehensively capture information relevant to the battery SOH. …”
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A social media geolocation method based on comparative learning by Yongchang XU, Shiduo HUANG, Haojun AI

“…Previous work on social media text-based geolocation focused on mapping language semantic space to geospatial space, which ignores the semantic correlation between social media texts and the distance correlation between geographical locations.To take advantage of these correlations, mCLF, a new unsupervised multiple-level contrastive learning framework was proposed, three contrastive learning modules were designed: a semantic learning module, a location learning module, and a cross-learning module.Transformer encoder was used to obtain semantic representation of posts, utilizing unsupervised contrastive learning method to decrease the distance of semantic representations and location representations of posts with near locations, and then fine-tuned the model with supervised method for geographic location regression or classification outputs.Compared with five baseline methods, extensive experiments based on four datasets demonstrate the effectiveness of the proposed framework.…”
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Novel antenna selection algorithm for STBC and VBLAST hybrid coding systems by LI Ren, JIANG Yong-quan, LI Xiao-yan, ZHANG En-zhan

“…Both theoretical analysis and simulation results indicate that the proposed antenna selection algorithm increases the capacity of the STBC and VBLAST hybrid system effectively, and improves the BER remarkably comparing with a VBLAST encoding MIMO system.…”
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Epistasis-Based Basis Estimation Method for Simplifying the Problem Space of an Evolutionary Search in Binary Representation by Junghwan Lee, Yong-Hyuk Kim

“…In this paper, a method is proposed to select an optimum basis can be used to simplify an evolutionary search space in a binary encoding scheme. The basis search method is based on a genetic algorithm and the fitness evaluation is based on the epistasis, which is an indicator of the complexity of a genetic algorithm. …”
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