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International Conference on Mechatronics and Industrial Informatics (ICMII 2013)

作者： An Chunming Li Yinxing Beihua Univ Sch Econ Management Jilin Peoples R China

ISBN: (纸本)9783037856949

The right panel drawing direction is an important prerequisite for generating qualified parts, an important step before the panel forming simulation is to determine the reasonable direction of the drawing. Manually adjust parts in order to overcome rely on experience, the drawbacks to the drawing direction, the direction of the drawing punch and forming the contact area of the sheet as the goal of automatic determination algorithm. Objective function of the direction of the drawing for the variable contact area in the drawing direction of the feasible region, the use of heritage algorithms to optimize the objective function of the contact area and, ultimately feasible within the contact area corresponding to the drawing direction, that is the best drawing direction. The measured results show that the direction of the drawing based on genetic algorithm, the automatic algorithm can fast and accurate to obtain the optimal direction of drawing.

关键词： automatic algorithm Automotive Covering Stamping Direction Genetic algorithm

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automatic algorithm of Automotive Stamping Direction based on GA

Automatic Algorithm of Automotive Stamping Direction based o...

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International Conference on Mechatronics and Industrial Informatics (ICMII 2013)

作者： Liu Ruijun Beihua Univ Coll Transportat & Civil Engn Jilin Peoples R China

ISBN: (纸本)9783037856949

关键词： automatic algorithm Automotive Covering Stamping Direction Genetic algorithm

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Morphometric analysis of atypical glandular cells correctly classifies normal, reactive, and atypical cells in cervical smears

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DIAGNOSTIC CYTOPATHOLOGY 2020年第1期48卷 10-16页

作者： Vicari, Marco Guidobaldi, Leo Perrella, Eleonora Bianchi, Antonella Ferrari, Simona Martucci, Mariarosaria Petitti, Tommasangelo Rabitti, Carla Crescenzi, Anna Univ Hosp Campus Biomed Rome Pathol Unit Rome Italy Sandro Pertini Hosp Microbiol & Virol Unit Cytodiagnost Serv Rome Italy Campus Biomed Univ Hyg Publ Hlth & Stat Res Unit Rome Italy

The 2014 Bethesda System diagnostic criteria for atypical glandular cells (AGC) aid in the classification of atypical cells in cervical cytology. Anyway, AGC diagnosis remains challenging, due to low frequencies of this finding (approximately 0.5%-1% of Pap test results), abundance of AGC mimics, and significant interobserver variability. We developed an algorithm based on nuclear areas parameter that can help to differentiate AGC from Normal and Reactive glandular cells. Nuclear areas and perimeters were measured on 16 Pap smears with AGC and 18 with Reactive glandular cells of women aged between 30 and 77. Glandular cells from nonpathological Pap smears were used as controls. For each case, the means, medians, standard deviations, and the minimum and maximum values of both nuclear areas and perimeters of the cells of interest were calculated. The nuclear area analysis showed a 100% specificity in discriminating Normal from Altered cells (either Reactive or AGC), whereas the nuclear perimeter analysis showed a lower specificity (87.5%). Both nuclear area and perimeter variability analysis resulted in high specificity values in distinguishing Reactive cells from AGC. Therefore, a stepwise two-step algorithm using nuclear areas to discriminate Normal from Altered cells, and nuclear area variability to distinguish Reactive from AGC, allowed us to reliably classify the cells into these three categories. The morphometric analysis of nuclear area is a valuable and reliable aid in AGC diagnosis and standardization, easily integrable into common automatic algorithms.

关键词： AGC automatic algorithm interobserver variability morphometry pap test

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Robust and effective automatic parameter choice for medical image filtering.

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COMPUTER METHODS IN BIOMECHANICS AND BIOMEDICAL ENGINEERING-IMAGING AND VISUALIZATION 2020年第2期8卷 152-168页

作者： Joao, Ana Gambaruto, Alberto Pereira, Ricardo Sequeira, Adelia Univ Tecn Lisboa Inst Super Tecn Dept Matemat Lisbon Portugal Univ Tecn Lisboa Inst Super Tecn CEMAT IST Lisbon Portugal Univ Bristol Dept Mech Engn Queens Bldg Bristol BS8 1TR Avon England Univ Coimbra Coimbra Univ Hosp Ctr Fac Med Dept Neurosurg Coimbra Portugal

The analysis of medical image data currently requires the interpretation of a trained and experienced user. The technological advances in imaging machinery and the understanding of disease onset, as well as medical planning, all favour the need for ever more automatic and robust methods for evaluating the health state of a subject. Here, we concentrate on methods for processing medical image data, as currently provided by existing imaging technologies, in particular the effectiveness of automatic image filtering in order to remove noise and improve the sharpness of distinct objects. The filtering approach is based on a partial differential equation, namely the Perona-Malik anisotropic diffusion equation. The approach adopted for terminating the iterative filtering procedure is based on image quality descriptors. In specific, we observe the rate of change of these to infer the transient effects of the filtering process. The entire pipeline is demonstrated to work effectively on different sets of medical image data, including MRI, CTA and CT, both in individual 2-D images in a stack, as well as treating the complete 3D volumetric dataset.

关键词： Medical imaging processing image quality Perona-Malik filtering automatic algorithm object segmentation

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Using neural networks for change detection and classification of COSMO-SkyMed Images

Using neural networks for change detection and classificatio...

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IEEE Radar Conference (RadarConf)

作者： Benedetti, Alessia Porzio, Ludovica Schiavon, Giovanni Latini, Daniele Fasano, Luca Del Frate, Fabio Univ Roma Tor Vergata Rome Italy GEO K SRL Rome Italy ASI Agenzia Spaziale Italiana Rome Italy

ISBN: (纸本)9781728189420

In this paper advanced neural networks (NNs) based techniques are presented to detect and classify changes in multi-temporal SAR COSMO-SkyMed images. The core and more innovative algorithm of the methodology is based on PCNNs (Pulse Couple Neural Networks), which perform the change detection task, while a standard Multi-Layer Perceptron (MLP) topology is considered to identify the type of changes occurred. The paper aims at providing a complete automatic processing chain usable also for extended areas. In fact, the PCNNs, being unsupervised networks, are inherently automatic. On the other hand, MLPs, which are supervised networks, are assumed to be learned off-line and plugged into the workflow without further training. The experimental results, which have been obtained over various urban areas in the city of Rome, are encouraging and confirm the validity of the considered approach.

关键词： COSMO-SkyMed change detection global monitoring automatic algorithm neural networks

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Improving fuzzy clustering algorithm for probability density functions and applying in image recognition

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Model Assisted Statistics and Applications 2020年第3期15卷 249-261页

作者： Phamtoan, Dinh Vovan, Tai Faculty of Engineering Van Lang University College of Natural Science Can Tho University Can Tho City Viet Nam

This study introduces a measure called coefficient of within-cluster proximity (CWP) to evaluate the similarity of probability density functions (DFs) within clusters. After surveying the under and upper, and the computational problems of CWP, a fuzzy clustering algorithm for DFs is proposed. This algorithm can determine the suitable number of clusters and find the probability for each DF to belong to specific cluster. The convergence of the algorithm is considered in theory and illustrated by the numerical examples. The algorithm is applied to image recognition. The results show strong advantages of it in comparison to other algorithms. They also indicate the potential of the proposed approach in application to the data of different types. © 2020 - IOS Press and the authors. All rights reserved.

关键词： automatic algorithm density function fuzzy cluster analysis image recognition

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The automatic algorithm of Filling Hole based-Mesh Panel Information based-System Management

The Automatic Algorithm of Filling Hole based-Mesh Panel Inf...

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International Conference on Mechatronics and Industrial Informatics (ICMII 2013)

作者： Ren FeiYan Beihua Univ Sch Econ Management Jilin Peoples R China

ISBN: (纸本)9783037856949

One of the most important factors of management in obtaining organization targets is effectiveness of financial management structures, and user of the financial management structures have more important role in the effectiveness of the structures. The purpose of this research is to study the influence of human factors including personal and individual characteristics of user of financial management structures based on effectiveness PC. For this target, a sample includes 2354 offices, organizations, private companies and organizations than apply financial management structure based-PC. Has been selected randomly and the investigative data has been counting using questionnaires. In order to find personal characteristics of users, the particular questionnaires which are designed according to four factor model of personality, has been done. In order to research the relation between effectiveness of the structure and personality, four hypotheses based on four features of personality. Moreover, in order to find the relationship between expertise (educational level, educational field and amount of training curriculum of PC knowledge), job satisfaction and experience of users, and effectiveness of the accountancy management structure based-PC, some hypotheses have been studied and written. The study results indicates that personal characteristics including Agreeableness, openness, Conscientiousness and experience working, is efficient on the financial management structures based-PC.

关键词： automatic algorithm Filling Hole Information System Management

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The automatic algorithm of Cause and Effect of Finace Information Systems based on Management Capabilities

The Automatic Algorithm of Cause and Effect of Finace Inform...

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International Conference on Mechatronics and Industrial Informatics (ICMII 2013)

作者： Ren FeiYan Beihua Univ Sch Econ Management Jilin Peoples R China

ISBN: (纸本)9783037856949

关键词： automatic algorithm Finace Information Cause and Effect Management Capabilities

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automatic phase space generation for Monte Carlo calculations of intensity modulated particle therapy

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BIOMEDICAL PHYSICS & ENGINEERING EXPRESS 2020年第2期6卷 025001页

作者： Wang, Qianxia Zhu, Cong Bai, Xuemin Deng, Yu Schlegel, Nicki Adair, Antony Chen, Zhi Li, Yongqiang Moyers, Michael Yepes, Pablo Rice Univ Dept Phys & Astron MS3156100 Main St Houston TX 77005 USA Univ Texas MD Anderson Canc Ctr Unit 1420 Dept Radiat Phys 1515 Holcombe Blvd Houston TX 77030 USA Univ Texas Hlth Sci Ctr Houston Sch Publ Hlth Houston TX 77030 USA Univ Houston Dept Ind Engn Houston TX 77204 USA Shanghai Proton & Heavy Ion Ctr Shanghai 201315 Peoples R China

Monte Carlo (MC) is generally considered as the most accurate dose calculation tool for particle therapy. However, a proper description of the beam particle kinematics is a necessary input for a realistic simulation. Such a description can be stored in phase space (PS) files for different beam energies. A PS file contains kinetic information such as energies, positions and travelling directions for particles traversing a plane perpendicular to the beam direction. The accuracy of PS files plays a critical role in the performance of the MC method for dose calculations. A PS file can be generated with a set of parameters describing analytically the beam kinematics. However, determining such parameters can be tedious and time consuming. Thus, we have developed an algorithm to obtain those parameters automatically and efficiently. In this paper, we presented such an algorithm and compared dose calculations using PS automatically generated for the Shanghai Proton and Heavy Ion Center (SPHIC) with measurements. The gamma-index for comparing calculated depth dose distributions (DDD) with measurements are above 96.0% with criterion 0.6%/0.6 mm. For each single energy, the mean difference percentage between calculated lateral spot sizes at 5 different locations along beam direction and measurements are below 3.5%.

关键词： automatic algorithm phase space Monte Carlo particle therapy measurement dose calculation

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automatic Sleep and Wake State Detection in Rats Using EEG

Automatic Sleep and Wake State Detection in Rats Using EEG

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作者： Sevak, Brinda Nishith University of Illinois at Chicago

学位级别：M.S., Master of Science/Master of Surgery

Epilepsy is one of the leading neurological disorders characterized by recurrent seizures. These epileptic seizures are often associated with sleep stages. The longitudinal EEG studies in animal model of epilepsy have voluminous data, which is difficult to mark sleep stages manually. This demands an automated way to detect sleep and active states. We used continuous video-EEG recordings as the gold standard to characterize sleep-wake states in animals. We implemented frequency band power-based thresholding approach to detect sleep stages in 600 hours of 5 epileptic and naïve animal data. We observed that the conventional delta and theta band powers were prominently higher than the other frequency bands in the sleep-wake states however not efficient enough to detect sleep. We considered a set of novel frequency bands for their ability to robustly differentiate individual sleep states by using EEG only. We implemented k-nearest neighbor, logistic regression and brute force threshold approach. The KNN was the best predictor of sleep and wake states with 94% accuracy where the brute force was significantly similar accuracy (92%). We further characterized the sleep in epileptic animals and found that the epileptic animals sleep longer compared to naïve animals and also individual sleep durations are significantly longer than the naive animals. Such efficient algorithms can improvise and expedite sleep studies and understanding relationship between and epilepsy.

关键词： Sleep-wake states Video-EEG recordings Epilepsy automatic algorithm KNN

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