检索结果-内蒙古大学图书馆

An Uplink Multiple Access Scheme Using Pilot-Free Channel Estimation

IEEE COMMUNICATIONS LETTERS 2020年第6期24卷 1226-1230页

作者： Hsu, Yung-Tsao Yang, Yu-Qin Lee, Shih-Kai Lee, Huang-Chang Lin, Mao-Chao Natl Taiwan Univ Grad Inst Commun Engn Taipei 10617 Taiwan Yuan Ze Univ Dept Elect Engn Taoyuan 33302 Taiwan Chang Gung Univ Dept Elect Engn Taoyuan 33302 Taiwan Natl Taiwan Univ Dept Elect Engn Taipei 10617 Taiwan

In an uplink scenario, a base station can extract messages from multiple users through received symbols according to individual channel gains. There is a multiple access scheme relying on channel gains for separating users which is referred to as gain division multiple access (GDMA). Our goal is to provide channel estimation for the GDMA system without using pilot signals. We first employ a clustering technique to obtain estimates of the possible linear combinations of channel gains of users through a set of received symbols. We then devise algorithms to estimate the channel gain for each user and recover the message sent from each user.

关键词： Channel estimation clustering algorithms Uplink Fading channels Classification algorithms Receivers Electrical engineering Multiple access channel estimation clustering algorithm

来源：评论

学校读者我要写书评

暂无评论

Data Mining Study of Chinese Herbal Fumigation and Washing in the Treatment of Perianal Eczema

International Core Journal of Engineering

引用

International Core Journal of Engineering 2022年第8期8卷 867-876页

作者： Jiyun Wu Yaping Cui Qiangqiang Gao Lu Lin Yan Ou Yanrong Zhan

Objective To explore the law of Chinese herbal fumigation and washing in the treatment of perianal eczema through data mining. Methods China National Knowledge Network (CNKI), VIP Chinese Journal Server (VIP), Wanfang Statistical Information Public Service network platform (Wanfang Statistics), National Biomedical Literature Research Information Service Network Management System (SinoMed) were retrieved from the database construction to May 2020 On the research paper on the treatment of perianal eczema by traditional Chinese medicine fumigating and washing. According to the prescriptions recorded in the collected articles, Microsoft Excel or WPS was used to establish a database to analyze the drug frequency, sexual taste and meridian return, etc. IBM SPSS Statistics 18.0 statistical software was used to analyze the data of association rules based on association rules and Apriori *** 286 articles were included, including 283 prescriptions, including 155 traditional Chinese medicines, 22 of which were more frequently used than 35. Sophora flavescens was the most frequently used drug. The medicinal taste of 155 is mainly bitter cold and simmering temperature, and mainly goes to the liver meridian. The efficacy classification is mainly heat-clearing medicine. In the association rule, the core drug pair of Sophora flavescens and Phellodendron phellodendri was the association rule (support = 73.85).Conclusion TCM fumigating and washing prescription drugs for perianal eczema are mainly heat-clearing drugs, accompanied by poison, insecticide and antipruritic drugs, antipruritic drugs, etc. Sophora flavescens, Phellodendron phellodendri, Cnidium fruit, Difuzi fruit, Fructus diorrhizae, rhizoma dioscoreae, parsnip and so on are frequently used.

关键词： Perianal Eczema Fumigation of Traditional Chinese Medicine Data Mining clustering algorithm

来源：评论

学校读者我要写书评

暂无评论

Automatic Knot Adjustment For B-Spline Smoothing Approximation Using Improved clustering algorithm

Automatic Knot Adjustment For B-Spline Smoothing Approximati...

引用

IEEE International Conference on Fuzzy Systems (FUZZ)

作者： Valenzuela, O. Pasadas, M. Rojas, I. Guillen, A. Pomares, H. Univ Granada Dpt Appl Math E-18071 Granada Spain

ISBN: (纸本)9781479900206

Smoothing b-splines constitute a powerful and popular methodology for performing nonparametric regression with high accuracy. It is well known that the placement of the knots in spline smoothing approximation has an important and considerable effect on the behavior of the final approximation. For this purpose, in this paper a novel methodology is presented for optimal placement and selections of knots, in order to approximate or fit curves to data, using smoothing splines. A new method based on improved clustering algorithm is used to optimally select a reduced number of knots for constructing the base of the b-spline, while ensuring the best accuracy.

关键词： B-spline clustering algorithm knot adjustment smoothing approximation

来源：评论

学校读者我要写书评

暂无评论

algorithm-Switching-Based Last-Level Cache Structure with Hybrid Main Memory Architecture

引用

COMPUTER JOURNAL 2020年第1期63卷 123-136页

作者： Li, Xian-Shu Yoon, Su-Kyung Kim, Jeong-Geun Burgstaller, Bernd Kim, Shin-Dug Yonsei Univ Dept Comp Sci Seoul South Korea

In this research, we designed an algorithm-switching (AS)-based last-level cache (LLC) structure with DRAM-NAND Flash hybrid main memory architecture. In order to take full advantage of previous memory access patterns and achieve high performance in the upper level of memory hierarchy, an AS-based clustering engine that uses k-means, k-medoids and k-center clustering algorithms was applied to LLC. The proposed LLC consists of three major parts, namely a set-divisible cache, and victim and clustering buffers. The victim and clustering buffers efficiently managed the history of cache blocks evicted from the set-divisible cache through the AS-based engine mechanism. The experimental results that were evaluated using Redis application and YCSB benchmark show that compared with conventional LLC structure, the proposed AS-based LLC structure could reduce the total execution time by 19.50%, power consumption by 16.31%, and NAND-Flash memory write count by 8.6%.

关键词： last-level cache management clustering algorithm DRAM-NAND flash hybrid main memory

来源：评论

学校读者我要写书评

暂无评论

An edge-sensitive simplification method for scanned point clouds

引用

MEASUREMENT SCIENCE AND TECHNOLOGY 2020年第4期31卷 045203-045203页

作者： Liu, Shifan Liang, Jin Ren, Maodong He, JingBin Gong, Chunyuan Lu, Wang Miao, Zehua Xi An Jiao Tong Univ State Key Lab Mfg Syst Engn Sch Mech Engn Xian 710049 Shaanxi Peoples R China XTOP 3D Technol Shenzhen Co Ltd Innovat Lab Shenzhen 518060 Peoples R China

Due to the huge number of points on three-dimensional point clouds captured by optical scanning devices, point-based simplification is a crucial step in model reconstruction. However, the loss of edge features of industrial parts after such simplification reduces reconstruction accuracy. This paper presents an edge-sensitive, point-based simplification method to eliminate redundant points and preserve more edge feature details. Firstly, a new geometrical descriptor is created for each point to generate a geometrical domain. A clustering scheme is then designed by applying two different clustering algorithms, to split the point cloud in the geometrical domain and the spatial domain respectively. The proposed method is capable of preserving edge features well, while reducing the original number of points to 10% or even 5%. The proposed method is compared with other simplification methods and the experimental results indicate that it performs better in simplifying industrial parts.

关键词： point cloud simplification edge feature preserving clustering algorithm

来源：评论

学校读者我要写书评

暂无评论

Distributed multi-sensor multi-view fusion based on generalized covariance intersection

引用

SIGNAL PROCESSING 2020年 166卷 107246-107246页

作者： Li, Guchong Battistelli, Giorgio Yi, Wei Kong, Lingjiang Univ Elect Sci & Technol China Sch Informat & Commun Engn Chengdu Sichuan Peoples R China Univ Firenze Dipartimento Ingn Informaz Florence Italy

Distributed multi-target tracking (DMTT) is addressed for sensors having different fields of view (FoVs). The proposed approach is based on the idea of fusing the posterior Probability Hypotheses Densities (PFIDs) generated by the sensors on the basis of the local measurements. An efficient and robust distributed fusion algorithm combining the Generalized Covariance Intersection (GCI) rule with a suitable clustering algorithm (CA) is proposed, named CA-GCI fusion algorithm. The CA is used to decompose each posterior PHD into well-separated components (clusters). For the commonly detected targets, an efficient parallelized GCI fusion strategy is proposed and analyzed in terms of L-1 error. For the remaining targets, a suitable compensation strategy is adopted so as to counteract the GCI sensitivity to independent detections while reducing the occurrence of false targets. Detailed implementation steps using a Gaussian Mixture (GM) representation of the PHDs are provided. Numerical experiments clearly confirm the effectiveness of the proposed CA-GCI fusion algorithm. (C) 2019 Elsevier B.V. All rights reserved.

关键词： Multi-target tracking Multi-view sensors Fields-of-view GCI fusion clustering algorithm GM-PHD filter

来源：评论

学校读者我要写书评

暂无评论

Consensus clustering of single-cell RNA-seq data by enhancing network affinity

引用

BRIEFINGS IN BIOINFORMATICS 2021年第6期22卷 bbab236-bbab236页

作者： Cui, Yaxuan Zhang, Shaoqiang Liang, Ying Wang, Xiangyun Ferraro, Thomas N. Chen, Yong Tianjin Normal Univ Coll Comp & Informat Engn Tianjin 300387 Peoples R China CMSRU Dept Biomed Sci Camden NJ USA Rowan Univ Dept Mol & Cellular Biosci Camden NJ 08028 USA

Elucidation of cell subpopulations at high resolution is a key and challenging goal of single-cell ribonucleic acid (RNA) sequencing (scRNA-seq) data analysis. Although unsupervised clustering methods have been proposed for de novo identification of cell populations, their performance and robustness suffer from the high variability, low capture efficiency and high dropout rates which are characteristic of scRNA-seq experiments. Here, we present a novel unsupervised method for Single-cell clustering by Enhancing Network Affinity (SCENA), which mainly employed three strategies: selecting multiple gene sets, enhancing local affinity among cells and clustering of consensus matrices. Large-scale validations on 13 real scRNA-seq datasets show that SCENA has high accuracy in detecting cell populations and is robust against dropout noise. When we applied SCENA to large-scale scRNA-seq data of mouse brain cells, known cell types were successfully detected, and novel cell types of interneurons were identified with differential expression of gamma-aminobutyric acid receptor subunits and transporters. SCENA is equipped with CPU+GPU (Central Processing Units+Graphics Processing Units) heterogeneous parallel computing to achieve high running speed. The high performance and running speed of SCENA combine into a new and efficient platform for biological discoveries in clustering analysis of large and diverse scRNA-seq datasets.

关键词： single-cell RNA-seq clustering algorithm bioinformatics cell typing

来源：评论

学校读者我要写书评

暂无评论

Cluster-Based Membership Function Acquisition Approaches for Mining Fuzzy Temporal Association Rules

引用

IEEE ACCESS 2020年 8卷 123996-124006页

作者： Chen, Chun-Hao Chou, Hsiang Hong, Tzung-Pei Nojima, Yusuke Natl Taipei Univ Technol Dept Informat & Finance Management Taipei 106 Taiwan Tamkang Univ Dept Comp Sci & Informat Engn Taipei 251 Taiwan Natl Univ Kaohsiung Dept Comp Sci & Informat Engn Kaohsiung 811 Taiwan Natl Sun Yat Sen Univ Dept Comp Sci & Engn Kaohsiung 804 Taiwan Osaka Prefecture Univ Dept Comp Sci & Intelligent Syst Osaka 5998531 Japan

In real-world applications, transactions are typically represented by quantitative data. Thus, fuzzy association rule mining algorithms have been proposed to handle these quantitative transactions. In addition, items generally have certain lifespans or temporal periods in which they exist in a database. Therefore, fuzzy temporal association rule mining algorithms have also been proposed in the literature. A key factor in the acquisition of fuzzy temporal association rules (FTARs) is the design of appropriate membership functions. Because current approaches have been designed to generate membership functions for mining fuzzy association rules (FARs) in market-basket analysis, in this paper, we propose a membership function tuning mechanism for a fuzzy temporal association rule mining algorithm. The proposed approach modifies an existing cluster-based method to generate unique membership functions that are specifically tailored to each item in a dataset. Two factors are utilized to decide the appropriate membership functions of each item: (1) the density similarity among intervals corresponding to the density similarity within intervals, and (2) the information closeness within an interval corresponding to the similarity in the number of data points between intervals. A parameter theta is used to indicate the relative importance of these two factors. As a result, the membership functions are generated based on the quantitative ranges of individual items, and the generated membership functions of items are different in terms of the values of each interval and the number of intervals. The generated membership functions are subsequently used in a fuzzy temporal association rule mining algorithm. Computational experiments were conducted on both a synthetic dataset and a real-world one to demonstrate the effectiveness of the proposed approach.

关键词： clustering algorithm fuzzy association rule fuzzy temporal association rule item lifespan membership functions

来源：评论

学校读者我要写书评

暂无评论

Enhancing the LTE-based intelligent transportation system's performance

引用

DIGITAL SIGNAL PROCESSING 2020年第0期99卷 102677-000页

作者： Daoud, Omar Hamarsheh, Qadri Damati, Ahlam Philadelphia Univ Commun & Elect Engn Dept Amman 19392 Jordan Philadelphia Univ Elect Engn Dept Amman 19392 Jordan

Intelligent transportation system is considered as one of the main features of the new generation wireless systems, where both of high speed data transmission and processing play a crucial role. This work presents two propositions in order to attain the performance improvement for both of data transmission and processing speed. Thus, the presented work consists of deriving a clustering algorithm based on a weighting algorithm for the head assignments processes, and emphasizing the parallel-processing technique based on variety wavelet baby functions, respectively. Accordingly, both of the data transmission speed and power will be examined. In order to verify the findings, a simulation has been done and compared with the following clustering algorithms;namely DMAC, PC, DBC, and Lower-ID DCA. This comparison is based on the following factors;namely efficiency factors involved in this investigation;namely complementary cumulative distributions, bit rates, energy efficiency, the cluster head life time and the ordinary nodes reattaching-head average times. The depicted results for the cluster head duration at 20 km/s show a remarkable system stability based on both the clustering overhead, and the cluster head duration. The attained improvements reach the 53% and 88.4% over the DBC work and the Lowest-ID DCA work, respectively. (C) 2020 Elsevier Inc. All rights reserved.

关键词： clustering algorithm Energy efficiency UWB-MB-OFDM V2V

来源：评论

学校读者我要写书评

暂无评论

Modeling of the development of the fetus cognitive map from the sensorimotor system

引用

EGYPTIAN INFORMATICS JOURNAL 2020年第4期21卷 191-199页

作者： Ahmed, Eman El Khoribi, Reda A. Darwish, Gamal Muzy, Alexandre Bernot, Gilles Cairo Univ Fac Comp & Informat Giza Egypt Univ Cote dAzur CNRS Lab Informat Signaux & Syst Sophia Antipolis I3S UNS Nice France

The human cognitive map formation is still an open question. Based on biological facts, the cognitive map origin goes back to the age of the fetus human. In this paper, our aim is to provide a possible answer to that question. Accordingly, we present a theoretical model of the development of the cognitive map of a fetus human using its sensorimotor data. We define positions of the cognitive map as associations between high-level perceptions created from different sensory sources. We use a proposed method referred to as Frequency-based-means clustering algorithm to develop the perceptions that form the association map. Our proposed theoretical model is tested on simulated data. Results show that our model is a possible candidate for demonstrating how the cognitive map is formed. In addition, comparison with k-means clustering is presented and results show that the frequency-based-means clustering has a better performance than k-means clustering and is more suitable for this application. (C) 2020 Production and hosting by Elsevier B.V. on behalf of Faculty of Computers and Artificial Intelligence, Cairo University. This is an open access article under the CC BY-NC-ND license (http://***/licenses/by-nc-nd/4.0/).

关键词： clustering algorithm k-means Cognitive map Fetus Brain Sensorimotor system

来源：评论

学校读者我要写书评

暂无评论

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案：

请选择收藏分类：

通借通还

建议与咨询 留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案： 新增检索档案 确定 取消

请选择收藏分类： 新增自定义分类 确定 取消

通借通还

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

请选择保存的检索档案：

请选择收藏分类：