Lempel-Ziv complexity (LZC) is extensively utilized in the identification of bearing faults. The present enhancement in LZC encoding relies on time-domain information. When the magnitude of fluctuation is minimal, LZC...
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Lempel-Ziv complexity (LZC) is extensively utilized in the identification of bearing faults. The present enhancement in LZC encoding relies on time-domain information. When the magnitude of fluctuation is minimal, LZC utilizing time-domain information encoding is unable to properly differentiate signals with varying frequency components. Thus, an improved LZC based on the time-frequency encoding method is proposed. Initially, the time-domain encoding is obtained according to the quartile of the amplitude. Then, the frequency-domain encoding is calculated based on the statistic value at each frequency along the frequency direction of the Wigner Trispectrum. Finally, the ultimate encoding is derived from both time-domain encoding and frequency-domain encoding. The proposed method is validated through the actual data of bearing. The time-frequency encoding technique can significantly augment the capacity of encoding sequences to depict signal variations and boost the LZC representation of signal complexity.
In the realm of lightweight materials in architecture, knitting as a discrete additive method has enabled the creation of functionally graded material (FGM). For the current research in encoding methods for knitting F...
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ISBN:
(纸本)9789887891833
In the realm of lightweight materials in architecture, knitting as a discrete additive method has enabled the creation of functionally graded material (FGM). For the current research in encoding methods for knitting FGM materials, researchers tend to focus on a limited number of surface transitions to study localized material traits. However, designing at an architectural scale demands multiple hierarchical structures for smooth transitions due to amplified performance differences, resulting in a complex system. Thus, organizing knitting units during encoding becomes crucial. This paper proposes a modulus-based encoding method for architectural knitting FGM materials, accommodating various surface types to create continuous gradient patterns. Based on the Grasshopper platform and STOLL machines, the method translates 3D models into machine encoding by using BMP (Bitmap) graphics. The method was successfully applied in a workshop in Tongji University. This research explores the fabrication of knitting FGM materials with multi-patterns in architecture, aiming to inspire innovative applications of fabrics in architecture.
Neural network models, such as BP, LSTM, etc., support only numerical inputs, so data preprocessing needs to be carried out on the categorical variables to convert them into numerical data. For unordered multi-categor...
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Neural network models, such as BP, LSTM, etc., support only numerical inputs, so data preprocessing needs to be carried out on the categorical variables to convert them into numerical data. For unordered multi-categorical variables, existing encoding methods may produce dimensional catastrophes and may also introduce additional order misrepresentation and distance bias in neural network computation. To solve the above problems, this paper proposes an unordered multi-categorical variable encoding method O-AE using orthogonal matrix for encoding and encoding representation learning and dimensionality reduction via an autoencoder. Bayesian optimization is used for hyperparameter optimization of the autoencoder. Finally, seven experiments were designed with the basic O-AE, Bayesian optimization of the hyperparameters of the autoencoder for O-AE, and other encoding methods to encode unordered multi-categorical variables in five datasets, and they were input into a BP neural network to carry out target prediction experiments. The results show that the experiments using O-AE and O-AE-b have better prediction results, proving that the method proposed in this paper is highly feasible and applicable and can be an optional method for the data processing of unordered multi-categorical variables.
In this paper, a new encoding method for single-track absolute shaft encoder is introduced based on the analysis of the characteristics of the code. This code using the new method has the characteristics of customizab...
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ISBN:
(数字)9781510646483
ISBN:
(纸本)9781510646483;9781510646476
In this paper, a new encoding method for single-track absolute shaft encoder is introduced based on the analysis of the characteristics of the code. This code using the new method has the characteristics of customizable code length and good code balance, which solves the problem that the traditional code length can only be some discrete value and the problem of poor code balance. The new code has abundant redundant information, based on which, it is easy to distinguish whether there is fault in the code recognition.
We developed a ready-to-read on-bead peptide encoding method for high-throughput screening bioassays. With two-dimensional surface-enhanced Raman scattering nano-identifiers (2D-SERS IDs) which are concurrently labell...
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We developed a ready-to-read on-bead peptide encoding method for high-throughput screening bioassays. With two-dimensional surface-enhanced Raman scattering nano-identifiers (2D-SERS IDs) which are concurrently labelled with two SERS codes (coupling steps and kinds of amino acid), we could possibly generate more than 10 trillion codes with only 30 Raman label compounds.
In recent years, many online health communities (OHCs) are established to provide the patients with the services of disease prevention and self-management. Patients in those online health communities discuss their hea...
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ISBN:
(纸本)9781538616451
In recent years, many online health communities (OHCs) are established to provide the patients with the services of disease prevention and self-management. Patients in those online health communities discuss their health conditions and share their experiences with other patients using narrative texts in the posts. Those posts contain a vast amount of patients' information, including drugs, symptoms, conditions, etc. They are really valuable for clinical research. However, it is hard for information systems to automatically extract the clinical knowledge from those posts to provide knowledge-based services to online patients. This paper investigates the characteristics of those post contents and accordingly proposes an encoding method with Systematized Nomenclature of Medicine - Clinical Terms (SNOMED CT) to process the texts into encoded and structured contents to help the analytic system in the OHCs to discover the biomedical knowledge. Based on our experimental result, the proposed method can effectively extract the biomedical knowledge from the posts and enhance the ability of clinical knowledge discovery online to improve the patient support.
This paper presents the structured Fisher vector encoding method, a new video representation which yields an improved model to classical FV for human action recognition. Our proposed representation is based on local s...
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ISBN:
(纸本)9781467387095
This paper presents the structured Fisher vector encoding method, a new video representation which yields an improved model to classical FV for human action recognition. Our proposed representation is based on local structural organization of features by building graphs of trajectories. It preserve more information in feature encoding process by local spatial pooling and refining the representation in the global pooling. Local spatio-temporal information are exploited by presenting the relationships among video trajectories as local graphs of trajectories using a multi-scale Delaunay triangulation. Experiments using the human action recognition datasets (Hollywood2 and HMDB51) show the effectiveness of the proposed approach.
Globally-coupled low-density parity check (GC-LDPC) codes have shown great application potential in the error correction of NAND Flash memories. However, the existing LDPC encoder architectures cannot fully use the st...
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Globally-coupled low-density parity check (GC-LDPC) codes have shown great application potential in the error correction of NAND Flash memories. However, the existing LDPC encoder architectures cannot fully use the structure characteristic of GC-LDPC codes. In this letter, focusing on the particular globally-coupled structure, we propose a memory-efficient multiplex-parallel GC-LDPC encoding method and corresponding efficient GC-LDPC encoder architecture. By reusing the local submatrices and optimizing the operation order of piecewise parity bits, the proposed encoding method has low storage overhead and encoding complexity. Then, based on the designed extended shift-register-adder-accumulator (E-SRAA) unit and barrel shifter, we optimize the operator scheduling of the proposed GC-LDPC encoding method when its local encoding is different. The implementation results under various FPGA technologies show that the proposed GC-LDPC encoder architecture achieves a markedly higher throughput-to-resource overhead ratio than existing similar LDPC encoder architectures. Meanwhile, it can meet the bandwidth requirement of ONFI 6.0.
Lempel-Ziv complexity (LZC) is an algorithm used to quantify the complexity of a data sequence by calculating the number of independent substrings contained in the sequence. LZC succeeds in detecting abnormal patterns...
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Lempel-Ziv complexity (LZC) is an algorithm used to quantify the complexity of a data sequence by calculating the number of independent substrings contained in the sequence. LZC succeeds in detecting abnormal patterns in signals and is widely employed for identifying anomalies and recognizing patterns in several fields, such as medical science, natural science, social science, and engineering. The objective of this study is to investigate the theory, improvement, and application of LZC in different fields. Firstly, a brief overview of the areas where LZC is utilized is provided. Next, the principle and process of signal complexity characterization are examined, along with a comparison of its advantages to entropy. Following this, we will present a detailed review of the improvement techniques and uses of LZC, focusing on three key areas: encoding methods, multiscale methods, and noise reduction methods. Lastly, this paper presents the unresolved matters and potential areas for further investigation LZC.
Background WOBAN is a high-speed network and hence any kind of failure results in huge data loss. Using the proposed network coding technique with parallel path protection can handle multiple link failures, the perfor...
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Background WOBAN is a high-speed network and hence any kind of failure results in huge data loss. Using the proposed network coding technique with parallel path protection can handle multiple link failures, the performance of the network can be *** This study aims to improve network performance using network coding with parallel path protection routing algorithm (NC-PPR) for multiple link failures in *** We investigated the multiple link failures in WOBAN by the proposed approach namely Coded Path Protection Algorithm, which enhances the survivability of the WOBAN against multiple link failures in the front end and eliminates the need of backup *** Extensive simulation is carried out to implement proposed work. A simulation model and code is developed in MATLAB to get the performance enhancement of *** We compared the performance of proposed algorithm with existing algorithm. The obtained results show that the proposed algorithm has superior performance than the existing *** In this paper, a new routing approach, which works in three phases namely path finding, encoding, and decoding, using random linear network coding (RLNC) is introduced to address the survivability issue of the WOBAN. The proposed approach also enhances the network performance in terms of PDR, overhead, and delay.
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