2017 Open Conference of Electrical, Electronic and Information Sciences (eStream)最新文献_第2页

Voice based interface for route search system 基于语音的路线搜索系统接口

2017 Open Conference of Electrical, Electronic and Information Sciences (eStream) Pub Date : 2017-04-01 DOI: 10.1109/ESTREAM.2017.7950318

Tomas Rasymas, V. Rudzionis

引用次数: 1

Effective background subtraction algorithm for food inspection using a low-cost near infrared camera 低成本近红外相机食品检测的有效背景减法算法

2017 Open Conference of Electrical, Electronic and Information Sciences (eStream) Pub Date : 2017-04-01 DOI: 10.1109/ESTREAM.2017.7950322

Paulius Tumas, A. Serackis

引用次数: 4

Synthesis of the control system of the robot manipulator of galvanic lines using the Bellman dynamic programming method 利用Bellman动态规划方法综合了电偶线机器人机械手的控制系统

2017 Open Conference of Electrical, Electronic and Information Sciences (eStream) Pub Date : 2017-04-01 DOI: 10.1109/ESTREAM.2017.7950328

V. Saroka, S. Autsou

引用次数: 3

Analysis of data pre-processing influence on intrusion detection using NSL-KDD dataset 基于NSL-KDD数据集的数据预处理对入侵检测的影响分析

2017 Open Conference of Electrical, Electronic and Information Sciences (eStream) Pub Date : 2017-04-01 DOI: 10.1109/ESTREAM.2017.7950325

N. Paulauskas, Juozas Auskalnis

引用次数: 56

Investigation of the transient characteristics of an unmanned aerial vehicle in terms of identifying it as a control object 从识别控制对象的角度研究无人机的瞬态特性

2017 Open Conference of Electrical, Electronic and Information Sciences (eStream) Pub Date : 2017-04-01 DOI: 10.1109/ESTREAM.2017.7950329

A. Shumski

引用次数: 0

Modeling of two-tier DDoS by combining different type of DDoS models 通过组合不同类型的DDoS模型，对两层DDoS进行建模

2017 Open Conference of Electrical, Electronic and Information Sciences (eStream) Pub Date : 2017-04-01 DOI: 10.1109/ESTREAM.2017.7950319

S. Ramanauskaitė, A. Čenys, N. Goranin, J. Janulevicius

引用次数: 2

Control methods for piezomechanical robots moving in trajectories: Software and hardware 在轨迹上运动的压电机器人的控制方法:软件和硬件

2017 Open Conference of Electrical, Electronic and Information Sciences (eStream) Pub Date : 2017-04-01 DOI: 10.1109/ESTREAM.2017.7950305

Eugenijus Macerauskas, Jurate Janutenaite-Bagdoniene, G. Kulvietis

{"title":"Control methods for piezomechanical robots moving in trajectories: Software and hardware","authors":"Eugenijus Macerauskas, Jurate Janutenaite-Bagdoniene, G. Kulvietis","doi":"10.1109/ESTREAM.2017.7950305","DOIUrl":"https://doi.org/10.1109/ESTREAM.2017.7950305","url":null,"abstract":"Practical application of smart materials for moving robots enabled to solve difficult mechatronic positioning and movement problems. Movement in such systems is generated using piezoelectrical devices. Therefore, classical trajectories formation and control methods are not suitable. For these specific problems positioning and piezorobot control methods and algorithms are created. In order to practically realize these algorithms a novel software and hardware is needed. This article presents movement formation methods and movement in predefined trajectory on some plane algorithms for cylindrical piezorobot. It is shown how they can be implemented using Matlab and LabVIEW software. Trajectory movement is controlled using special software and specifically designed motion control system. Control signal is amplified by electronics hardware. It also matches industrial PXI computer to piezorobot's motion actuator which requires high voltage signal and capacitance load. The path of piezorobot is registered using image processing and computer vision technologies. The paper presents experimental results of piezorobot movement when different input data set applied. Piezorobot point-to-point movement on plane without rotation is analyzed. Such movement is created when only one electrode is excited at a time. This generates forces at every segment and their cumulative force ensures precise control of piezorobot movement direction and speed.","PeriodicalId":174077,"journal":{"name":"2017 Open Conference of Electrical, Electronic and Information Sciences (eStream)","volume":"722 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133498487","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

The phoneme set influence for lithuanian speech commands recognition accuracy 音位集对立陶宛语语音识别精度的影响

2017 Open Conference of Electrical, Electronic and Information Sciences (eStream) Pub Date : 2017-04-01 DOI: 10.1109/ESTREAM.2017.7950321

M. Greibus, Ž. Ringelienė, L. Telksnys

引用次数: 6

Selection of fractal dimension features for speech emotion classification 语音情感分类的分形维数选择

2017 Open Conference of Electrical, Electronic and Information Sciences (eStream) Pub Date : 2017-04-01 DOI: 10.1109/ESTREAM.2017.7950316

G. Tamulevicius, R. Karbauskaite, G. Dzemyda

{"title":"Selection of fractal dimension features for speech emotion classification","authors":"G. Tamulevicius, R. Karbauskaite, G. Dzemyda","doi":"10.1109/ESTREAM.2017.7950316","DOIUrl":"https://doi.org/10.1109/ESTREAM.2017.7950316","url":null,"abstract":"Despite numerous studies during the last decade speech emotion recognition is still the task of limited success. Great efforts were made for extending emotional speech feature sets and selecting the most effective ones, proposing multi-stage and multiple classifier based classification schemes, and developing multi-modal speech emotion recognition technique. Nevertheless, the reported emotion recognition rates vary from 70 % up to 90 % depending on the analyzed language, the number of recognized emotions, the speaker mode, and other important factors. Considering the nonlinear and fluctuating nature of the spoken language, we present a feature set, based on a fractal dimension (FD) for emotion classification. Katz, Castiglioni, Higuchi, and Hurst exponent-based FD features were employed in 2–7 emotion classification tasks. The experimental results show a clear superiority of FD based feature sets against acoustic ones. The feature selection enabled us to reduce the initial feature set down to 2–7 order sets and to improve thereby the accuracy of speech emotion classification by 11.4 %. The obtained average classification accuracy for all tasks was 96.6 %.","PeriodicalId":174077,"journal":{"name":"2017 Open Conference of Electrical, Electronic and Information Sciences (eStream)","volume":"28 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115975274","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: 5

Self-identification of permanent magnet synchronous motor inductance for efficient sensorless control 永磁同步电机电感自辨识，实现高效无传感器控制

2017 Open Conference of Electrical, Electronic and Information Sciences (eStream) Pub Date : 2017-04-01 DOI: 10.1109/ESTREAM.2017.7950306

Justas Dilys, A. Baskys

引用次数: 2