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signal-Digital Conversion of Stepper Motor Used in Ships 3

Signal-Digital Conversion of Stepper Motor Used in Ships

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3rd international conference on Advanced Engineering Materials and Architecture Science (ICAEMAS)

作者： Yu Hai-xia Lin Min Fu Cai Kui Wang Lu-yun Dalian Univ Technol City Inst Sch Elect & Automat Dalian 116000 Peoples R China Dalian maritime Univ Informat Sci & Technol Coll Dalian 116001 Peoples R China

ISBN: (纸本)9783038352679

In this paper, we will select and use stepper motor which is comparatively important and widely used in ships for the study. Through the study, we can propose a method that we can use the synchronous repeater compass for the high-precision digital conversion, and then statistics will be put into SCM AT89C52 with the simple handling of circuit conversion, thus, we can take a series of processes, such as data processing, initial value setting, directional displaying and serial port outputting. Foremost, the precision of this converting circuit can reach 0.1 degrees that can ensure the numbers continuously change behind the decimal point one digit. So it is not only inexpensive, but also flexible and convenient in use.

关键词： ship stepper motor digital conversion

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Unsupervised relevance analysis for feature extraction and selection: A distance-based approach for feature relevance

Unsupervised relevance analysis for feature extraction and s...

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3rd international conference on Pattern Recognition Applications and Methods, ICPRAM 2014

作者： Peluffo, Diego H. Lee, John A. Verleysen, Michel Rodríguez, José L. Castellanos-Domínguez, Germán Machine Learning Group ICTEAM Université catholique de Louvain Place du Levant 3 B-1348 Louvain-la-Neuve Belgium Molecular Imaging Radiotherapy and Oncology IREC Université catholique de Louvain Avenue Hippocrate 55 B-1200 Bruxelles Belgium Grupo de Automática Antigua estacíon del Ferrocarril Universidad Autónoma de Manizales Manizales Colombia Signal Processing and Recognition Group Universidad Nacional de Colombia 7 Via al Magdalena Manizales Colombia

ISBN: (纸本)9789897580185

The aim of this paper is to propose a new generalized formulation for feature extraction based on distances from a feature relevance point of view. This is done within an unsupervised framework. To do so, it is first outlined the formal concept of feature relevance. Then, a novel feature extraction approach is introduced. Such an approach employs the M-norm as a distance measure. It is demonstrated that under some conditions, this method can readily explain literature methods. As another contribution of this paper, we propose an elegant feature ranking approach for feature selection followed from the spectral analysis of the data variability. Also, we provide a weighted PCA scheme revealing the relationship between feature extraction and feature selection. To assess the behavior of the studied methods within a pattern recognition system, a clustering stage is carried out. Normalized mutual information is used to quantify the quality of resultant clusters. Proposed methods reach comparable results with respect to literature methods. Copyright © 2014 SCITEPRESS.

关键词： Extraction

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Detection of Falsification Using Infrared Imaging: Time and Frequency Domain Analysis 3

Detection of Falsification Using Infrared Imaging: Time and ...

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3rd international conference on Advances in Computing, Communications and Informatics (ICACCI)

作者： Azar, Yaniv Campisi, Matthew NYU Polytech Sch Engn New York NY 11201 USA

ISBN: (纸本)9781479930807

Throughout the years many people have tried to master the art of lie detection;however no one was ever able to come up with a method that detects lies in more than 83% accuracy, which is non invasive, mobile, and cost effective. Therefore this article will attempt to show that by measuring temperature changes in the nose area, one could determine whether someone is lying or not better than current polygraph can. First, eleven different subjects were chosen to participate in this project. Then, using a FLIR ThermoVision A40 infrared camera the data was collected from eleven different subjects in three different sets of measurement. This paper presents the results using two different methods of detection. The first method of detection was using a time domain analysis and the second method of detection was using a frequency domain analysis. Each of these methods had an accuracy of 69 % and 84 % in detecting lies, respectively. Finally, the two methods were compared to current polygraph, which has an accuracy of 83%. It was concluded that it is possible to detect lies using an infrared camera and that it is actually better than current polygraph since it has higher accuracy, is non invasive, and cost effective.

关键词： Infrared Imaging Lie Detection Infrared Camera Image processing Digital signal processing Medical Imaging

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An interactive and artistic monitoring system for machine condition

An interactive and artistic monitoring system for machine co...

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2013 3rd international conference on Packaging and Manufacturing Technology, ICCPMT 2013

作者： Luo, Lin Hu, Fu Wen Zhang, Nai Song College of Mechanical and Electrical Engineering North China University of Technology Beijing 100144 China

ISBN: (纸本)9783038350132

Most machine health monitoring techniques are likely to suffer from ineffective selection of state features, and the increasing redundancy of raw signals. As a new strategy, an interactive and artistic monitoring approach is presented. Its basic concept is to transform raw signals into artistic graphs rather than obscure waveforms. The entire procedure includes three steps: signal acquisition, plotting artistic graphs and interactive diagnosis. In the case of numerical control machine tools, an interactive and artistic monitoring prototype system is developed based on the integration of the open-source Arduino platform and the open-source processing language. Experimental results indicate that the artistic visualization of measured data facilitates the identifications of machine condition and the diagnosis of observed symptoms. © (2014) Trans Tech Publications, Switzerland.

关键词： data visualization

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Cognitive brain signal processing: Healthy vs Alzheimer's disease patients

Cognitive brain signal processing: Healthy vs Alzheimer's di...

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8th international conference on Universal Access in Human-Computer Interaction, UAHCI 2014 - Held as Part of 16th international conference on Human-Computer Interaction, HCI international 2014

作者： Kosmidou, Vasiliki Tsolaki, Anthoula Papadaniil, Chrysa Tsolaki, Magdalini Hadjileontiadis, Leontios Kompatsiaris, Ioannis Centre for Research and Technology Hellas Greece Medical Physics Laboratory Medical School Aristotle University of Thessaloniki Greece Department of Electrical and Computer Engineering Aristotle University of Thessaloniki Greece 3rd Department of Neurology Aristotle University of Thessaloniki Greece

processing the brain functionality during certain perceptual stimuli or activities is beneficial to better understanding the lost abilities of a mind of a patient with cognitive impairment. Electroencephalogram (EEG) has been widely used as a tool for brain mapping. In this paper, we discuss the experimental setup and methods of the Cognitive Brain signal processing (CBP) project towards this direction. High spatial resolution EEG (256 channels) is acquired, while the subject perform a series of cognitive tests with known expected response. Four tests from the CANTAB© Battery evaluating visual memory, spatial working memory and attention, a Sudoku puzzle and tasks with external visual and audio stimuli i.e., emotional (Ekman images) and audio event-related potentials (ERP) comprise the experimental protocol. Three groups of subjects are recruited, i.e., 30 healthy young adults 25-40 years old, 30 healthy adults of 65 years and older, and 30 patients with mild Alzheimer's disease (AD) aged 65 years and older. In the CBP project, the 2D vector field tomography (VFT) will be extended to the 3D space to create a novel tool to solve the inverse EEG problem towards source reconstruction and therefore brain mapping. The 3D VFT will be applied to the acquired data in order to facilitate the extraction of the cognitive states and the identification of dysfunctioning areas. The external stimuli will be correlated with the performance of the participants to verify which elements can be assistive and improve their performance. The results can be used to design intelligent assistive environments and help the communication of patients with AD in everyday life. © 2014 Springer international Publishing.

关键词： Electroencephalography

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MRI discrimination by inter-slice similarities and kernel-based centered alignment 3

MRI discrimination by inter-slice similarities and kernel-ba...

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3rd IEEE international Work-conference on Bioinspired Intelligence, IWOBI 2014

作者： Álvarez-Meza, A.M. Cárdenas-Peña, D. Castellanos-Domínguez, G. Signal Processing and Recognition Group Universidad Nacional de Colombia Campus La Nubia km 7 via al Magdalena Manizales Colombia

ISBN: (纸本)9781479961740

Brain structure segmentation from 3D magnetic resonances image (MRI) allows supporting the analysis of physiological and pathological processes. Nonetheless, finding MRI relationships posses a challenge when analyzing in voxel-based highdimensional spaces. We introduce a kernel-based representation approach to support MRI discrimination. In this sense, inherent Inter-Slice Kernel (ISK) relationship is employed to highlight brain structure distributions. Then, a generalized Euclidean metric is estimated by using a kernel-based centered alignment algorithm to code the correlation between MRI dependencies and prior demographic patient information. The proposed approach is tested on MRI data classification by considering patient gender and age categories. Attained results show how proposed methodology improves data interpretability and separability in comparison to state of the art algorithms based on MRI Voxelwise features. Therefore, introduced kernel-based representation can be useful to support MRI clustering and similarity inference tasks that are required on template-based image segmentation and atlas construction. © 2014 IEEE.

关键词： Magnetic resonance

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The EUSO-Balloon instrument 3

The EUSO-Balloon instrument

引用

3rd Technology and Instrumentation in Particle Physics conference, TIPP 2014

作者： Scotti, Valentina Osteria, Giuseppe Università degli Studi di Napoli Federico II Italy INFN Sezione di Napoli Italy

EUSO-Balloon is a pathfinder mission for JEM-EUSO (Extreme Universe Space Observatory on-board the Japanese Experiment Module), the near-UV telescope proposed to be installed on board the international Space Station (ISS) before the end of this decade. The main objective of this pathfinder mission is to perform a full scale end-to-end test of all the key technologies and instrumentation of JEM-EUSO detectors and to prove the entire detection chain. The JEM-EUSO instrument consists of an UV telescope designed to focus the signal of the UV tracks generated by Extreme Energy Cosmic Rays propagating in Earth's atmosphere, onto a finely pixelized UV camera. The EUSO-Balloon instrument, smaller than the one designed for the ISS, is currently developed as a payload of a stratospheric balloon operated by the French Centre National d'Études Spatiales (CNES) and will be launched during the CNES flight campaign in August 2014. This telescope will point towards the nadir from a float altitude of about 40 km. With its Fresnel Optics and Photo-Detector Module, EUSO-Balloon will monitor a 12°×12° wide field of view in a wavelength range between 290 and 430 nm, at a rate of 400'000 frames/sec. In this paper, we will review the main stages of the signal processing of the EUSO-Balloon instrument: the photodetection, the analog electronics, the trigger stages, which select events while rejecting random background, the electronic acquisition system which performs the data management and the monitoring, allowing the instrument control during operation. © Copyright owned by the author(s) under the terms of the Creative Commons Attribution-NonCommercial-ShareAlike Licence.

关键词： signal processing

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A Time Effective Approach for Vector Similarity Measurement Based on Vector Addition

A Time Effective Approach for Vector Similarity Measurement ...

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3rd international conference on Civil and Architecture Engineering (ICCAE’2014);3rd international conference on Automation, Robotics and Mechanical Engineering (ICAMR’2014);3rd international conference on Machine Learning and Computer Science (IMLCS’2014);3rd international conference on Management, Humanity and Economics (ICMHE’2014);3rd international conference on Power, Control and VLSI Engineering (ICPCVE’2014)

作者： Wasiq Khan Ping Jiang Mohammed Bilal Speech Signal Processing University of Bradford Department of computer science intelligent systemsUniversity of HullUnited Kingdom Data Mining University of LeedsUnited Kingdom

Pattern matching is one of the principal methodologies in speech signal processing and isolated word recognition. There are a number of similarity measures to find the similarity between the target words in an acquired speech by matching with template. The retrieved similarity result is dependent both on the feature vectors extraction technique and the distance metric produced by similarity measure. Short Time Fourier Transform is used for spectrogram re- trieval which is used for performance comparison of different simi- larity measures. In this paper, a novel similarity measure is proposed which is based on vector addition. It outperforms in terms of execu- tion time as compared to other similarity measures. We have done a detailed study of the performance of different similarity measurement techniques for a number of spectrograms on a large database of speech recordings. Manhattan distance, Euclidean distance, vector cosine angle distance, Bhattacharyya coefficients and posterior prob- ability measure are used for the performance comparison. The results show that this similarity measure outperforms as compare to all above similarity measures in terms of time complexity and similarity performance.

关键词： signal processing Speech Recognition Pattern Matching PPM Word Identification.

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The comparison between IABC with EGARCH in foreign exchange rate forecasting 1

The comparison between IABC with EGARCH in foreign exchange ...

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1st Euro-China conference on Intelligent data Analysis and Applications, ECC 2014

作者： Chang, Jui-Fang Tsai, Pei-Wei Chen, Jung-Fang Hsiao, Chun-Tsung Department of International Business National Kaohsiung University of Applied Sciences 415 Chien-Kung Road Kaohsiung City80778 Taiwan Department of Marine Information and Technology National Kaohsiung Marine University 482 Jong-Jhou 3rd Road Kaohsiung City80543 Taiwan Department of Business Administration National Kaohsiung University of Applied Sciences 415 Chien-Kung Road Kaohsiung City80778 Taiwan

ISBN: (纸本)9783319077727

Foreign exchange rate forecasting catches many researchers interests in recent years. Problems of the foreign exchange rate forecasting model selection and the improvement on forecasting accuracy are not easy to be solved. In this paper, the forecasting results obtained by conventional time-series models and by the Inter-active Artificial Bee Colony (IABC), which is a young artificial intelligent meth-od, are compared with each other with 4 years historical data. The sliding win-dow strategy is used in the experiment for both the training and the testing phases. In our experiments, we use continuous previous three days data as the training set, and use the training result to forecast the foreign exchange rate on the fourth day. In addition, we evaluate the forecasting accuracy with three criteria, namely, Mean Square Error (MSE), Mean Absolute Error (MAE), and Root Mean Square Error (RMSE). The experimental results indicate that feeding macroeco-nomic factors to IABC as the input data is capable to produce higher accurate data in the foreign exchange rate than the conventional time-series models such as EGARCH. © 2014 Springer international Publishing Switzerland. All rights reserved.

关键词： Mean square error

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Compactly supported graph building for spectral clustering

Compactly supported graph building for spectral clustering

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international Work conference on Bio-inspired Intelligence (IWOBI)

作者： A.E. Castro-Ospina A.M. Álvarez-Meza G. Castellanos-Dominguez Signal Processing and Recognition Group Universidad Nacional de Colombia Manizales Colombia

In spectral clustering approaches is of great importance how is built the graph representation over a data set, being reflected in the achieved clustering performance. In this work is introduced a methodology to build a graph representation of a given data, based on compactly supported radial basis functions which enables to highlight relevant pair-wise sample relationships. To tune such functions, an objective function is proposed, which aims to find a trade-off between a similarity and a sparsity measure, allowing to achieve a suitable local and global data structure representation. Synthetic and real-world data sets are tested. Results shows how proposed method improves clustering results, specially for an image segmentation task.

关键词： Kernel Sparse matrices Image segmentation data structures Buildings Clustering algorithms Particle swarm optimization

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