2020 IEEE 2nd International Conference on System Analysis & Intelligent Computing (SAIC)最新文献_第7页

An Algorithm for Solving the Optimal Set Partitioning Problem with Constraints on the Centers Location 一种具有中心位置约束的最优集划分问题的求解算法

2020 IEEE 2nd International Conference on System Analysis & Intelligent Computing (SAIC) Pub Date : 2020-10-05 DOI: 10.1109/SAIC51296.2020.9239209

Olena I. Kiseleva, O. Prytomanova, Oleksii Serhieiev

引用次数: 0

Complexity Reduced IIR Filter Design for FPGA 降低FPGA复杂度的IIR滤波器设计

2020 IEEE 2nd International Conference on System Analysis & Intelligent Computing (SAIC) Pub Date : 2020-10-05 DOI: 10.1109/SAIC51296.2020.9239119

A. Sergiyenko, A. Serhienko

引用次数: 0

Track 3: Intelligent computing technologies 专场3:智能计算技术

2020 IEEE 2nd International Conference on System Analysis & Intelligent Computing (SAIC) Pub Date : 2020-10-05 DOI: 10.1109/saic51296.2020.9239140

引用次数: 0

SAIC 2020 Table of contents 工商总局2020年目录

2020 IEEE 2nd International Conference on System Analysis & Intelligent Computing (SAIC) Pub Date : 2020-10-05 DOI: 10.1109/saic51296.2020.9239173

引用次数: 0

Assessment of Residual Service Life for the Residential Buildings under Systematical Industrial Explosions 系统工业爆炸作用下住宅建筑剩余使用寿命评估

2020 IEEE 2nd International Conference on System Analysis & Intelligent Computing (SAIC) Pub Date : 2020-10-05 DOI: 10.1109/saic51296.2020.9239172

I. Kaliukh, S. Ivan, Chorna Krystyna, Shokarev Viktor, Shokarev Ievgen, Shokarev Andrii

{"title":"Assessment of Residual Service Life for the Residential Buildings under Systematical Industrial Explosions","authors":"I. Kaliukh, S. Ivan, Chorna Krystyna, Shokarev Viktor, Shokarev Ievgen, Shokarev Andrii","doi":"10.1109/saic51296.2020.9239172","DOIUrl":"https://doi.org/10.1109/saic51296.2020.9239172","url":null,"abstract":"Report deals with issue of the experimental and theoretical assessment of residual service life of reinforced concrete (RC) structures of residential buildings due to permanent acting weak earthquakes in some Ukrainian cities. The recorded values of vibration acceleration in building bases are in diapason from 2,4 cm/s $^{mathbf{2}}$ to 64 cm/s $^{mathbf{2}}$ when explosion and the values of soil vibration velocity are in diapason from 0,03 cm/s to 1,2 cm/s. It is corresponding to 1 – 4 earthquake magnitude on the Richter scale when explosion works. Analysis of soil acceleration specters when passing of impact waves under buildings has permitted to specify the predominate frequencies in diapason 1–48 Hz. This fact confirms a possibility of the building structures oscillation (floors, walls etc.) in regime close to resonance regime. The soil acceleration should be restricted by value 15 cm/s $^{mathbf{2}}$ for prevention of building foundation settlements when explosions. We took in account not only the limitation on physical and mechanical behavior of construction materials but also the systematic seismic actions and other irremovable risk factors at assessment of residual service life of the building RC concrete structures.","PeriodicalId":208407,"journal":{"name":"2020 IEEE 2nd International Conference on System Analysis & Intelligent Computing (SAIC)","volume":"63 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-10-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114497204","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 1

Applications of Fractal Analysis in Science, Technology, and Art: A Case Study on Geography of Ukraine 分形分析在科学、技术和艺术中的应用——以乌克兰地理为例

2020 IEEE 2nd International Conference on System Analysis & Intelligent Computing (SAIC) Pub Date : 2020-10-05 DOI: 10.1109/SAIC51296.2020.9239196

Alexey G. Malishevsky

引用次数: 5

Asymptotics of Control Problem for the Impulse Perturbation Process under Stochastic Optimization Procedure and Levy Approximation Conditions 随机优化过程和Levy近似条件下脉冲扰动过程控制问题的渐近性

2020 IEEE 2nd International Conference on System Analysis & Intelligent Computing (SAIC) Pub Date : 2020-10-05 DOI: 10.1109/SAIC51296.2020.9239121

Y. Chabanyuk, A. Nikitin, U. Khimka

引用次数: 0

Effective Ways to Overcome Classification Limitations for Activities of Daily Livings (ADLs) 克服日常生活活动分类限制的有效方法

2020 IEEE 2nd International Conference on System Analysis & Intelligent Computing (SAIC) Pub Date : 2020-10-05 DOI: 10.1109/SAIC51296.2020.9239238

Mariam Dedabrishvili

{"title":"Effective Ways to Overcome Classification Limitations for Activities of Daily Livings (ADLs)","authors":"Mariam Dedabrishvili","doi":"10.1109/SAIC51296.2020.9239238","DOIUrl":"https://doi.org/10.1109/SAIC51296.2020.9239238","url":null,"abstract":"Development of reliable and precise methods of Human Activity Recognition (HAR) are highly important, since wrong or inaccurate recognition can cause harmful consequences for human health. Scientists working in the field try to find the ways to enhance achievements for recognition accuracy. Taking this into account, it is vital to choose classifiers which make classification of activities with reliable rates. However, limitations of the currently existing algorithms and inherent lack of precision level can put their applicability to the field under the question. In particular, Hidden Markov Model has certain restrictions, which is caused by the principle of random selection of parameters and it is problematic to discriminate between the classes with high accuracy. Other well-known methods also have some drawbacks due to their nature. With the aim to solve these problems and to ensure the required results, we propose a hybrid complex of classifiers that provide adequate models of the study area. This work will deal with the classification of daily living human activities using wearable inertial sensors. Walking, Lying, Standing up, Stair Ascent, Stair Descent, Sitting on the Ground, etc. are examples of these activities. In this study, a dataset including twelve activities is created using three inertial sensors. Two hybrids of classifiers that combines Bayesian Networks with distance based classifier, namely with k Nearest Neighbor and Neural Network with Hidden Markov Model will be presented in the study. The achieved results will be compared in terms of correct classification rate, F-measure, recall, precision, and specificity. Raw data and extracted features will be used separately as inputs of the classifier. The inertial sensor units worn by different healthy subjects are placed at key points of upper/lower body limbs (chest, right thigh and left ankle). In this study, only acceleration data is used, as a modality for estimating the activities.","PeriodicalId":208407,"journal":{"name":"2020 IEEE 2nd International Conference on System Analysis & Intelligent Computing (SAIC)","volume":"22 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-10-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126659306","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0