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Sentiment analysis algorithm Based on Dance Rhythmic and Melodic Features

EAI ENDORSED TRANSACTIONS ON SCALABLE INFORMATION SYSTEMS 2024年第3期11卷 1-11页

作者： Chen, Zhe Shandong Art Inst Dance Acad Jinan 250000 Peoples R China

INTRODUCTION: Dance is not only able to strengthen the body but also an expression of art. It can not only express the culture of a nation or a country but also express the emotions of a country. Therefore, it is essential to utilize algorithms for the study of dance rhythm and melodic characteristics in today's world, and introduces a sentiment analysis algorithm for the study. OBJECTIVES: To disseminate our traditional dance culture, carry forward the spirit of our traditional art, enhance the creative level of our dance art, improve the current dance art in our country can not better apply the algorithm, and solve the problem that our current sentiment analysis algorithm can not be combined with art disciplines. METHODS: Use the neural network and deep learning in sentiment analysis to establish a sentiment analysis algorithm adapted;then use the sentiment analysis algorithm to calculate the in-depth filtering of the dance rhythm and melodic characteristics of the research object;finally, the heat map of the dance rhythm and melodic characteristics of the SRD is calculated according to the experiment of the algorithm. RESULTS: The core influencing factors of dance rhythm and melodic features are found to be attention mechanism and LMT through heat analysis (knowledge map);the experimental results using the sentiment analysis algorithm can be found to have a significant mediating effect on the joint enhancement of dance rhythm and melodic sense. CONCLUSION: The development of dance art not only lies in communication and integration but also combination with contemporary computer technology;using sentiment analysis algorithms can better analyze the dance rhythm and melodic characteristics;therefore, the level of algorithm application in the field of dance art should be improved.

关键词： dance rhythm melodic characteristics sentiment psychology analysis algorithm

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Optical and geometric property classification of natural aerosol types with a large open chamber system and multi-wavelength elastic polarized LiDAR

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ENVIRONMENTAL POLLUTION 2025年 372卷 125977页

作者： Shin, Juseon Kim, Dukhyeon Ku, Hyeyun Noh, Youngmin Pukyong Natl Univ Div Earth Environm Syst Sci 45 Yongso Ro Busan 48513 South Korea Hanbat Natl Univ Sch Basic Sci Daejeon South Korea Agcy Def Dev R&D Inst 3 Directorate 5 Daejeon South Korea

Natural aerosols, originating from uncontrollable processes, are widely distributed and often interfere with the remote sensing of anthropogenic aerosols. This interference occurs because distinguishing between particle types is challenging when they coexist. Despite their significant impact on radiative forcing and climate, research on natural aerosols remains limited due to their unpredictable nature. To address this, we implemented a pilot-scale open chamber system coupled with multi-wavelength elastic polarized LiDAR. This system enables the separation of target particles from ambient aerosols, enabling the development of a specialized analysis algorithm that calculates optical parameters-such as the Angstrodm Exponent (AE) and depolarization ratio (delta)- which serve as unique "fingerprints" for distinguishing aerosol types. Our experiments included some natural particles, such as yeast, whey protein, fly ash, flour, pine tree pollen, and kaolinite. Distinct optical properties were observed, with yeast exhibiting high delta values at 532 nm (0.31 +/- 0.09) and 1064 nm (0.06 +/- 0.01). Whey protein and fly ash were distinguishable based on AE values of -0.23 +/- 1.16 and 0.31 +/- 0.59, respectively. Pollen, another key natural aerosol, showed delta values of 0.33 +/- 0.03 at 532 nm and 0.04 +/- 0.01 at 1064 nm, enabling clear differentiation from other aerosol types. By incorporating infrared wavelengths into our LiDAR system, we enhanced the accuracy of aerosol characterization. This study highlights the approach for distinguishing natural aerosols and lays the groundwork for continuous monitoring systems to understand their atmospheric and climatic impacts better.

关键词： Angstrom exponent Depolarization ratio Optical fingerprint analysis algorithm

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Using ABC algorithm for Classification and analysis on Effects of Control Parameters

Using ABC Algorithm for Classification and Analysis on Effec...

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18th National Biomedical Engineering Meeting (BIYOMUT)

作者： Dilmac, Selim Korurek, Mehmet Istanbul Tech Univ Fen Bilimleri Enstitusu Maslak Sariyer Is Turkey

ISBN: (纸本)9781479975723

In this study, Artificial Bee Colony (ABC) algorithm based classifier is used. Also, in order to improve the effectiveness of ABC algorithm, some modifications are done. New method is called MABC algorithm. Both methods are applied on various real life data sets such as IRIS, WINE, PIMA, BUPA, ECG and results are compared. Those datasets are obtained from UCI Machine Learning Repository and MITBIH ECG database. In addition to it, validity indices and effects of some control parameters such as MCN, Limit are examined. It is observed that, selected features have significiant effect on classification success rate of classifier. If there is high overlap between the classes, success rate of classifier decreases. However observed results indicate that ABC algorithm can successfully be used for classification of multi dimensional datasets. By means of SCTR control parameter, MABC algorithm based classifier provides higher classification success rates versus ABC algorithm, independent from Limit and MCN values.

关键词： classification data analysis electrocardiography feature extraction feature selection learning (artificial intelligence) medical information systems medical signal processing signal classification swarm intelligence ABC algorithm effectiveness BUPA IRIS MABC algorithm based classifier MCN parameter MITBIH ECG database PIMA SCTR control parameter UCI Machine Learning Repository WINE analysis algorithm artificial bee colony algorithm based classifier class overlap classification algorithm classification success rate control parameter effect feature effect limit parameter multidimensional dataset classification validity index Classification algorithms Educational institutions Electrocardiography Indexes Iris Machine learning algorithms Particle swarm optimization Feature extraction Sorting algorithm Electrocardiography Particle swarm optimization Wine medical information systems control parameter INTEGRATED RISK INFORMATION SYSTEM Machine learning algorithms medical signal processing signal classification Educational institutions Classifiers activity based costing Iris

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Kinematic analysis of geared linkage mechanisms

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MECHANISM AND MACHINE THEORY 2005年第12期40卷 1394-1413页

作者： Li, TJ Cao, WQ Xidian Univ Sch Electromech Engn Xian 710071 Shaanxi Peoples R China Xian Univ Technol Dept Mech Engn Xian 710048 Peoples R China

A general approach to the kinematic analysis of planar geared linkage mechanisms (GLMs) is presented based on their structural topological characteristics. Firstly, a systematic method for decomposing a GLM into a series of sequential independent kinematic units, such as the simple links and the dyad link groups is proposed. The concept of tricolored graph and its mathematic expressions are introduced to describe the topological relationship between the kinematic pairs and the links in a GLM. The criteria and process for the structural decomposition and for choosing circuits using the theory of type transformation are established. Then the kinematic equations and the analytic solutions for the kinematic units are derived, and the method for the kinematic analysis of position, velocity and acceleration of GLMs is obtained in an algorithmic fashion. Finally, an application program has been developed, by which the whole work from the structural decomposition to the kinematic analysis can be accomplished automatically for any one of the GLMs. Some examples are used to illustrate the procedures. (c) 2005 Elsevier Ltd. All rights reserved.

关键词： geared linkage mechanism kinematic analysis tricolored graph structural decomposition kinematic unit analysis algorithm

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Large scale, unbiased analysis of elementary calcium signaling events in cardiac myocytes

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JOURNAL OF MOLECULAR AND CELLULAR CARDIOLOGY 2019年 135卷 79-89页

作者： Tian, Qinghai Schroeder, Laura Schwarz, Yvonne Flockerzi, Aline Kaestner, Lars Zeug, Andre Bruns, Dieter Lipp, Peter Saarland Univ Inst Mol Cell Biol Ctr Mol Signaling PZMS Res Ctr Mol Imaging & ScreeningMed Fac Kirrberger Str 100 D-66421 Homburg Germany Saarland Univ Med Fac Dept Physiol Homburg Germany Hannover Med Sch Cellular Neurophysiol Hannover Germany Saarland Univ Fac NT Expt Phys Saarbrucken Germany

The identification of spatiotemporally restricted Ca2+ signals, Ca2+ sparks, was instrumental for our understanding of cardiac Ca2+ homeostasis. High-speed 2D confocal imaging enables acquisition of such Ca2+ sparks with high-content information but their full appreciation is constrained by the lack of unbiased and easy-to-use analysis tools. We developed a software toolset for unbiased and automatic Ca2+ spark analysis for huge data sets of subcellular Ca2+ signals. iSpark was developed to be scanner and detector independent. In myocytes from hearts subjected to various degrees of hypertrophy we acquired > 5.000.000 Ca2+ sparks from 14 mice. The iSpark-enabled analysis of this large Ca2+ spark data set showed that the highly organized distribution of Ca2+ sparks present in healthy cells disarrayed concomitant with the development of aberrant transverse tubules and disease severity. Thus, iSpark represents a versatile and universal tool for analyzing local Ca2+ signaling in healthy as well as diseased, aberrant local Ca2+ signal transduction. The results from the unbiased analysis of large data sets provide a deeper insight into possible mechanisms contributing to the onset and progression of cardiac diseases such as hypertrophy.

关键词： Ca2+ spark Ultrafast 2D confocal scanning Active RyR cluster registration analysis algorithm Cardiac hypertrophy

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Current analysis platforms and methods for detecting copy number variation

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PHYSIOLOGICAL GENOMICS 2013年第1期45卷 1-16页

作者： Li, Wenli Olivier, Michael Med Coll Wisconsin Biotechnol & Bioengn Ctr 8701 Watertown Plank Rd Milwaukee WI 53226 USA

Copy number variation (CNV), generated through duplication or deletion events that affect one or more loci, is widespread in the human genomes and is often associated with functional consequences that may include changes in gene expression levels or fusion of genes. Genome-wide association studies indicate that some disease phenotypes and physiological pathways might be impacted by CNV in a small number of characterized genomic regions. However, the pervasiveness and full impact of such variation remains unclear. Suitable analytic methods are needed to thoroughly mine human genomes for genomic structural variation, and to explore the interplay between observed CNV and disease phenotypes, but many medical researchers are unfamiliar with the features and nuances of recently developed technologies for detecting CNV. In this article, we evaluate a suite of commonly used and recently developed approaches to uncovering genome-wide CNVs and discuss the relative merits of each.

关键词： copy number variation SNP array next generation sequencing detection method analysis algorithm

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Software-hardware Interaction analysis Based on Petri Net

Software-hardware Interaction Analysis Based on Petri Net

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26th Chinese Control and Decision Conference (CCDC)

作者： Yi Zhaoxiang Mu Xiaodong Zhao Peng Yi Yaqiao Xian Res Inst Hitech Hongqing Town Xian 710025 Peoples R China

ISBN: (纸本)9781479937066

As software and hardware have grown in functionality and complexity, the existing computer systems are confronting serious challenges with safety, dependability and reliability. Being one of the primary causes with responsibility for these challenges, the software-hardware interaction is advanced and widely studied in recent years. Unfortunately, none of the state-of-art researches has achieved widespread applicability in analyzing software-hardware interaction. Due to a lack of general model to describe the process, we present a software-hardware interaction model based on Petri Net(SHIPN), and also propose the systemic analysis method and process for software-hardware interaction. Indicating as a six-ttiple Petri Net, SHIPN is a logic model of system events, and denote the cause and effect between the software events and hardware events, as well as the process of system events. Especially. SHIPN has non-conflict, non-collision and non-competition of resources, and is essentially different from the traditional Petri Net. Subsequently, we define formalized software-hardware interaction events on the basis of SHIPN, and designed an analysis algorithm based on the incident matrix to deduce causations and propagation paths of each software-hardware interaction. An application case in the communication control system demonstrates that SHIPN is an accurate and practicable model, and the proposed method provides an effective approach to analyze software-hardware interaction.

关键词： Software-hardware Interaction Petri Net Propagation Process analysis algorithm Communication Control System

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Towards automated analysis of connections network in distributed stream processing system

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13th International Conference on Database Systems for Advanced Applications

作者： Gorawski, Marcin Marks, Pawel Silesian Tech Univ Inst Comp Sci PL-44100 Gliwice Poland

ISBN: (纸本)9783540785675

Not so long ago data warehouses were used to process data sets loaded periodically during ETL process (Extraction, Transformation and Loading). We could distinguish two kinds of ETL processes: full and incremental. Now we often have to process real-time data and analyse them almost on-the-fly, so the analyses are always up to date. There are many possible applications for real-time data warehouses. In most cases two features are important: delivering data to the warehouse as quick as possible, and not losing any tuple in case of failures. In this paper we describe an architecture for gathering and processing data from geographically distributed data sources and we define a method for analysing properties of the connections structure, finding the weakest points in case of single and multiple node failures. At the end of the paper our future plans are described briefly.

关键词： stream processing fault-tolerance analysis algorithm

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Research and analysis of Statistical Characteristics of Internet Exchange Points 6

Research and Analysis of Statistical Characteristics of Inte...

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6th International Symposium on Computing and Networking (CANDAR) - Across Practical Development and Theoretical Research

作者： Lv, Ting Qin, Donghong Ge, Lina Guangxi Univ Nationalities Sch Informat Sci & Engn Nanning Peoples R China

ISBN: (纸本)9781538691847

With the rapid development of the Internet, Internet exchange point (IXP) is deployed more and more around the world. As IXPs play an increasingly important role in the global Internet structure, IXPs are becoming more and more worthy of attention. However, the researches on IXPs' characteristics and their impacts on the Internet are very of shortage. This paper conducts experimental analysis of IXP based on actual network data. The experimental results show that IXP can improve the network environment and benefit to the overall development of the Internet.

关键词： inter-domain routing Internet exchange points network measuring analysis algorithm

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Efficient OLAP algorithms on GPU-accelerated Hadoop clusters

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DISTRIBUTED AND PARALLEL DATABASES 2019年第4期37卷 507-542页

作者： Wang, Hongzhi Wang, Zheng Li, Ning Kong, Xinxin Harbin Inst Technol Harbin Heilongjiang Peoples R China

In the time of big data, on-line analytical processing (OLAP) is an important method to process massive data. In order to realize a system with the capacity of both high storage and high computing power, Hadoop and GPU are both applied in OLAP. In general, three cores of OLAP determines the efficiency of OLAP analysis, which are aggregation of multi-dimensional data, pre-calculation of multi-dimensional data set (Cube) and connection of dimension table and fact table. For the purpose of boosting efficiency, this paper presents optimizing algorithms for each core. Beginning with aggregation on single machine, this paper firstly designs the GPU-based aggregation algorithm. Then, GPU-based Cube algorithm is introduced to accelerate pre-calculation, using inverted index to shrink computation amount. Finally, with new-designed dimension table connecting algorithm and query algorithm, GPU-based OLAP analysis algorithm is presented. Along with corresponding experiments and results, each algorithm shows their ability of boosting efficiency, optimizing GPU-based OLAP analysis on Hadoop.

关键词： OLAP GPU MapReduce Aggregation algorithm Cube algorithm analysis algorithm

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