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Anti-Motion Interference Wearable Device for Monitoring Blood Oxygen Saturation Based on sliding window algorithm

IEEE ACCESS 2020年 8卷 124675-124687页

作者： Jiao, Bin Zhengzhou Univ Aeronaut Sch Art & Design Zhengzhou 450000 Peoples R China

Wearable multi-physiological parameter monitoring technology can realize non-intrusive, non-invasive daily health monitoring of the human body. It has the characteristics of convenient operation, long-term continuous work, display of results, abnormal physiological condition alarm and wireless data transmission. First, an improved sliding window confidence propagation algorithm is proposed, which reduces the inefficient iterative process in the decoding process by correlation coefficients and reduces the running time of the algorithm by more than 1.5 times;designing a channel noise estimation method based on sliding window confidence propagation algorithm, and The source coding is similar. In order to estimate the local statistical parameters of the channel noise, the confidence propagation, the decoder uses the local partial probability of the adjacent accompanying child nodes to estimate the noise parameters of the channel noise. Secondly, the design and research of the blood oxygen saturation monitor, including filtering out high-frequency glitch noise, low-frequency baseline drift noise, and mixing and sudden motion interference noise, also achieved rapid and accurate extraction of pulse wave feature points, and calculated the blood oxygen value and pulse rate value. Compared with the traditional oximeter, the filtering algorithm and pulse wave feature point extraction algorithm on the oximeter software have less calculation amount and higher real-time performance. Finally, the relevant test experiment of the blood oxygen saturation monitor proves that the blood oximeter has good stability, accuracy and sensitivity. The practical use of anti-motion interference wearable devices not only shows that the wearable PPG sensor in this paper can stably obtain high-quality PPG signals, but also reflects its many applications in the field of real-time blood.

关键词： sliding window algorithm blood oxygen saturation anti-motion interference wearable

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SWIMRT: A graphical user interface using the sliding window algorithm to construct a fluence map machine file

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JOURNAL OF APPLIED CLINICAL MEDICAL PHYSICS 2006年第2期7卷 69-85页

作者： Chow, James C. L. Grigorov, Grigor N. Yazdani, Nuri Univ Toronto Princess Margaret Hosp Hlth Network Radiat Med Program Toronto ON M5G 2M9 Canada Univ Toronto Princess Margaret Hosp Hlth Network Dept Radiat Oncol Toronto ON M5G 2M9 Canada Univ Waterloo Dept Phys Waterloo ON N2L 3G1 Canada Grand River Hosp Grand River Reg Canc Ctr Kitchener ON N2G 1G3 Canada

A custom-made computer program, SWIMRT, to construct "multileaf collimator (MLC) machine" file for intensity-modulated radiotherapy (IMRT) fluence maps was developed using MATLAB (R) and the sliding window algorithm. The user can either import a fluence map with a graphical file format created by an external treatment-planning system such as Pinnacle3 or create his or her own fluence map using the matrix editor in the program. Through comprehensive calibrations of the dose and the dimension of the imported fluence field, the user can use associated image-processing tools such as field resizing and edge trimming to modify the imported map. When the processed fluence map is suitable, a "MLC machine" file is generated for our Varian 21 EX linear accelerator with a 120-leaf Millennium MLC. This machine file is transferred to the MLC console of the LINAC to control the continuous motions of the leaves during beam irradiation. An IMRT field is then irradiated with the 2D intensity profiles, and the irradiated profiles are compared to the imported or modified fluence map. This program was verified and tested using film dosimetry to address the following uncertainties: (1) the mechanical limitation due to the leaf width and maximum traveling speed, and (2) the dosimetric limitation due to the leaf leakage/transmission and penumbra effect. Because the fluence map can be edited, resized, and processed according to the requirement of a study, SWIMRT is essential in studying and investigating the IMRT technique using the sliding window algorithm. Using this program, future work on the algorithm may include redistributing the time space between segmental fields to enhance the fluence resolution, and readjusting the timing of each leaf during delivery to avoid small fields. Possible clinical utilities and examples for SWIMRT are given in this paper.

关键词： IMRT sliding window algorithm MLC computer programming fluence map

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An Efficient sliding window algorithm Using Adaptive-Length Guard window for Turbo Decoders

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JOURNAL OF COMMUNICATIONS AND NETWORKS 2012年第2期14卷 195-198页

作者： Lim, Hyuntack Kim, Yongsang Cheun, Kyungwhoon Pohang Univ Sci & Technol POSTECH Div Elect & Comp Engn Pohang 790784 South Korea POSTECH Div Informat Technol Convergence Engn Pohang South Korea

An efficient sliding window algorithm employing an adaptive-length guard window for turbo decoders is proposed. The proposed algorithm results in significant complexity reductions, especially for small sliding window ... 详细信息

关键词： Iterative maximum a posteriori decoder (MAP) sliding window algorithm turbo code

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Efficient Speaker Embedding Extraction Using a Twofold sliding window algorithm for Speaker Diarization 25

Efficient Speaker Embedding Extraction Using a Twofold Slidi...

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25th Interspeech Conference

作者： Choi, Jeong-Hwan Jeoung, Ye-Rin Kim, Ilseok Chang, Joon-Hyuk Hanyang Univ Dept Elect Engn Seoul South Korea

This paper proposes an efficient speaker embedding (SE) extraction method that employs a twofold sliding window algorithm (SWA) for speaker diarization (SD) systems. Nonoverlapping short segments are obtained through the first SWA and fed into the frame-level neural networks of a pre-trained SE model to extract frame-level representations. The neighboring frame-level representations are concatenated along the time axis through the second SWA, which enables an overlap between representations. The concatenated representations are used to extract multiple SEs. Additionally, we propose a fine-tuning strategy that employs a residual adapter and knowledge distillation techniques on a pre-trained SE model to refine the frame-level representation. Experimental results using two SD benchmarks show the effectiveness of the proposed extraction method with a fine-tuned SE model in terms of floating-point operations while maintaining the diarization error rate.

关键词： speaker diarization speaker embedding segmentation sliding window algorithm

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Prediction of Temperature for next three days using Decision Tree algorithm by comparing sliding window algorithm for better Accuracy 1

Prediction of Temperature for next three days using Decision...

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1st International Conference on Technologies for Smart Green Connected Society 2021, ICTSGS 2021

作者： Yaswanth Reddy, G. Saravanan, M.S. Saveetha University Tamil Nadu Chennai602105 India

ISBN: (纸本)9781607685395

Aim: The aim of this study is to predict the temperature for the next three days using a machine learning algorithm and the objective of this research is to improve the accuracy of temperature prediction. Materials and methods: The study used 36 samples with two groups of algorithms with the g-power value of 80%. To predict the temperature the sliding window algorithm (SLA) machine learning algorithm has found 89% of accuracy and this study will find better accuracy for temperature prediction with the Decision Tree (DT) algorithm. Results: This research study found 92% of accuracy for temperature prediction using a DT algorithm. Conclusion: This study concludes that the DT algorithm on temperature prediction is significantly better than the SLA. © The Electrochemical Society

关键词： Decision Tree algorithm Innovative weather prediction Machine learning sliding window algorithm

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A global grid model for the correction of the vertical zenith total delay based on a sliding window algorithm

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GPS SOLUTIONS 2021年第3期25卷 98-98页

作者： Huang, Liangke Zhu, Ge Liu, Lilong Chen, Hua Jiang, Weiping Guilin Univ Technol Coll Geomat & Geoinformat Guilin 541004 Peoples R China Guangxi Key Lab Spatial Informat & Geomat Guilin 541004 Peoples R China Wuhan Univ Sch Geodesy & Geomat Wuhan 430079 Peoples R China Wuhan Univ GNSS Res Ctr Wuhan 430079 Peoples R China

Reanalysis products have been applied to calculate the tropospheric delay for Global Navigation Satellite System (GNSS) positioning purposes widely. It is necessary to obtain high-precision tropospheric delay information from GNSS users with a high-precision tropospheric vertical stratification model because the height of the grids of the atmospheric reanalysis data is inconsistent with that of GNSS users, especially in regions with high terrains. In addition, the variation of the tropospheric delay in the vertical direction is much higher than that in the horizontal direction. The zenith total delay (ZTD) vertical stratification model is also key to the development of real-time and high-precision ZTD models. A new approach, the sliding window algorithm, is proposed to develop a ZTD vertical stratification model. In this work, a ZTD vertical stratification model considering spatiotemporal factors is developed based on the second Modern-Era Retrospective analysis for Research and Applications (MERRA-2) data, which is named the GZTD-H model. Radiosonde and International GNSS Service (IGS) data are treated as reference values to evaluate the performance of the GZTD-H model, which is compared to the model GPT2w. The results show that the GZTD-H model realizes the highest performance in ZTD layered vertical interpolation against ZTD layered profiles obtained at radiosonde sites, which achieves an improvement of 10% over the model GPT2w. Compared to model GPT2w, the GZTD-H model attains a spatial interpolation improvement of 8% for the Global Geodetic Observing System (GGOS) Atmosphere gridded ZTD over the surface ZTD calculated from radiosonde profiles. Furthermore, compared to model GPT2w, the model GZTD-H also attains improvements of 11% over the precise ZTD products acquired at IGS sites. In terms of model parameters, the GZTD-H model is greatly reduced and optimized over model GPT2w. Hence, the applicability of this model is enhanced in terms of GNSS atmospheric soun

关键词： sliding window algorithm Tropospheric delay model Zenith total delay Vertical stratification

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Ship Spatiotemporal Key Feature Point Online Extraction Based on AIS Multi-Sensor Data Using an Improved sliding window algorithm

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SENSORS 2019年第12期19卷 2706.-2706.页

作者： Gao, Miao Shi, Guo-You Dalian Maritime Univ Nav Coll Dalian 116026 Peoples R China Dalian Maritime Univ Collaborat Innovat Res Inst Autonomous Ship Dalian 116026 Peoples R China Key Lab Nav Safety Guarantee Liaoning Prov Dalian 116026 Peoples R China

Large volumes of automatic identification system (AIS) data provide new ideas and methods for ship data mining and navigation behavior pattern analysis. However, large volumes of big data have low unit values, resulting in the need for large-scale computing, storage, and display. Learning efficiency is low and learning direction is blind and untargeted. Therefore, key feature point (KFP) extraction from the ship trajectory plays an important role in fields such as ship navigation behavior analysis and big data mining. In this paper, we propose a ship spatiotemporal KFP online extraction algorithm that is applied to AIS trajectory data. The sliding window algorithm is modified for application to ship navigation angle deviation, position deviation, and the spatiotemporal characteristics of AIS data. Next, in order to facilitate the subsequent use of the algorithm, a recommended threshold range for the corresponding two parameters is discussed. Finally, the performance of the proposed method is compared with that of the Douglas-Peucker (DP) algorithm to assess its feature extraction accuracy and operational efficiency. The results show that the proposed improved sliding window algorithm can be applied to rapidly and easily extract the KFPs from AIS trajectory data. This ability provides significant benefits for ship traffic flow and navigational behavior learning.

关键词： big data mining spatiotemporal ship behavior key feature point feature online extraction AIS sliding window algorithm

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Exploring general memory structures in turbo decoders using sliding-window MAP algorithm

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IEICE TRANSACTIONS ON COMMUNICATIONS 2003年第11期E86B卷 3163-3173页

作者： Wu, CM Shieh, MD Wu, CH Natl Cheng Kung Univ Dept Elect Engn Tainan 70101 Taiwan

Turbo coding is a powerful coding technique that can provide highly reliable data transmission at extremely low signal-to-noise ratios. Owing to the computational complexity of the employed decoding algorithm, the realization of turbo decoders usually takes a large amount of memory space and potentially long decoding delay. Therefore, an efficient memory management strategy becomes one of the key factors toward successfully implementing turbo decoders. This paper focuses on the development of general structures for efficient memory management of turbo decoders employing the sliding-window (Log-)MAP algorithm. Three different structures and the associated mathematic representations are derived to evaluate the required memory size, average decoding rate, and latency based on the speed and the number of the adopted processors. Comparative results show the dependency of the resulting performance based on a set of parameters;thus provide useful and general information on practical implementations of turbo decoders.

关键词： turbo code BCJR algorithm MAP algorithm sliding window algorithm memory management

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Identification of growth-related genes based on BSA in Pacific white shrimp Litopenaeus vannamei

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AQUACULTURE 2025年 596卷

作者： Bao, Zhenning Yu, Yang Lin, Pengfei Li, Fuhua Chinese Acad Sci Inst Oceanol Key Lab Breeding Biotechnol & Sustainable Aquacult Qingdao 266071 Peoples R China Univ Chinese Acad Sci Beijing 100049 Peoples R China Qingdao Marine Sci & Technol Ctr Lab Marine Biol & Biotechnol Qingdao 266071 Peoples R China Chinese Acad Sci Inst Oceanol Shandong Prov Key Lab Expt Marine Biol Qingdao 266071 Peoples R China

The development of SNP genotyping techniques has facilitated the application of genome-wide association studies (GWAS) and genomic selection (GS) in plants and animals. However, the cost of high-throughput SNP genotyping is particularly high in the case of aquaculture animals which can produce a large number of offspring. Consequently, a cost effective method for trait-associated SNP identification and application was urgently needed in aquaculture breeding. In this study, a Bulk Segregation Analysis sequencing (BSA-seq) method was employed to identify growth-related single nucleotide polymorphisms (SNPs) and genes in the Pacific white shrimp Litopenaeus vannamei. Two independent families were used for this analysis to reduce the false positive. The DNA of individuals with the highest and lowest body weights was pooled separately. Two methods including the ED (Euclidean distance) method and the chi-square test were applied to calculate the allele differences between high and low growth rate individuals. A total of 24,325,437 SNPs were identified and consequently 1,299 SNPs and 163 genes were identified to be associated with growth traits. KEGG enrichment analysis showed that these genes were significantly enriched in phosphatidylinositol signaling system and phospholipase D signaling pathway. The diacylglycerol kinase genes, phosphatidylinositol 3-kinase genes, inositol polyphosphate 5-phosphatase genes, mitogen-activated protein kinase genes, myotubularin-related protein genes and epidermal growth factor receptor genes in these pathways were considered as candidate growth genes. This study demonstrated that the BSA-seq based on whole genome resequencing is cost-effective and useful in aquaculture. The results not only provide useful information for understanding the genetic basis of growth traits, but also offer a source of SNPs for marker-assisted selection (MAS) and genomic selection (GS) in shrimp.

关键词： Litopenaeus vannamei Bulk segregation analysis (BSA) Growth trait Single nucleotide polymorphisms (SNPs) sliding window algorithm

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New Regular sliding window algorithms for Elliptic Curve Scalar Point Multiplication

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AUTOMATIC CONTROL AND COMPUTER SCIENCES 2021年第8期55卷 1029-1038页

作者： Shenets, N. N. Petushkov, A. S. Peter Great St Petersburg Polytech Univ St Petersburg 195251 Russia

Simple side channel attacks on the implementation of elliptic curves scalar point multiplication algorithms are considered. New regular sliding window algorithms for calculating multiple points are proposed. Their opt... 详细信息

关键词： side channel attack point multiplication on elliptic curves regular algorithm sliding window algorithm

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