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Evaluating the diagnostic utility of applying a machine learning algorithm to diffusion tensor MRI measures in individuals with major depressive disorder

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PSYCHIATRY RESEARCH-NEUROIMAGING 2017年 264卷 1-9页

作者： Schnyer, David M. Clasen, Peter C. Gonzalez, Christopher Beevers, Christopher G. Univ Texas Austin Dept Psychol A8000 Austin TX 78712 USA Univ Washington Sch Med Dept Psychiat & Behav Sci Seattle WA 98195 USA Univ Calif San Diego Dept Psychol San Diego CA 92103 USA

Using MRI to diagnose mental disorders has been a long-term goal. Despite this, the vast majority of prior neuroimaging work has been descriptive rather than predictive. The current study applies support vector machine (SVM) learning to MRI measures of brain white matter to classify adults with Major Depressive Disorder (MDD) and healthy controls. In a precisely matched group of individuals with MDD (n = 25) and healthy controls (n = 25), SVM learning accurately (74%) classified patients and controls across a brain map of white matter fractional anisotropy values (FA). The study revealed three main findings: 1) SVM applied to DTI derived FA maps can accurately classify MDD vs. healthy controls;2) prediction is strongest when only right hemisphere white matter is examined;and 3) removing FA values from a region identified by univariate contrast as significantly different between MDD and healthy controls does not change the SVM accuracy. These results indicate that SVM learning applied to neuroimaging data can classify the presence versus absence of MDD and that predictive information is distributed across brain networks rather than being highly localized. Finally, MDD group differences revealed through typical univariate contrasts do not necessarily reveal patterns that provide accurate predictive information.

关键词： DIAGNOSIS of mental depression MAGNETIC resonance imaging of the brain MACHINE learning computer algorithms SUPPORT vector machines

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Performance Analysis and Comparison for High Maneuver Target Track Based on Different Jerk Models

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JOURNAL OF CONTROL SCIENCE AND ENGINEERING 2018年第6-11期2018卷 1-6页

作者： Meng, Qinghai Hou, Bowen Li, Dong He, Zhangming Wang, Jiongqi PLA 91550 Dalian 116024 Peoples R China Natl Univ Def Technol Coll Liberal Arts & Sci Changsha 410073 Hunan Peoples R China China Acad Space Technol Beijing Inst Spacecraft Syst Engn Beijing 100086 Peoples R China

The Jerk model is widely used for the track of the maneuvering targets. Different Jerk model has its own state expression and is suitable to different track situation. In this paper, four Jerk models commonly used in the maneuvering target track are advanced. The performances of different Jerk models for target track with the state variables and the characters are compared. The corresponding limit conditions in the practical applications are also analyzed. Besides, the filter track is designed with UKF algorithm based on the four different models for the high-maneuvering target. The simplified dynamic model is used to gain the standard trajectory with Runge-Kutta numerical integration method. The mathematical simulations show that Jerk model with self-adaptive noise variance has the best robustness while other models may diverge when the initial error is much larger. If the process noise level is much lower, the track accuracy for four Jerk models is similar and stationary in the steady track situation, but it will be descended greatly in the much highly maneuvering situation.

关键词： MANEUVERING boards computer algorithms RUNGE-Kutta formulas NUMERICAL integration DYNAMIC models

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Numerical Study of Random Periodic Lipschitz Shadowing of Stochastic Differential Equations

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DISCRETE DYNAMICS IN NATURE AND SOCIETY 2018年第1期2018卷 10-10页

作者： Zhan, Qingyi Xie, Xiangdong Fujian Agr & Forestry Univ Coll Comp & Informat Sci Fuzhou 350002 Peoples R China Ningde Normal Univ Ningde 352100 Fujian Peoples R China

This paper is devoted to a new numerical approach for the possibility of (omega,L delta)-periodic Lipschitz shadowing of a class of stochastic differential equations. The existence of (omega,L delta)-periodic Lipschitz shadowing orbits and expression of shadowing distance are established. The numerical implementation approaches to the shadowing distance by the random Romberg algorithm are presented, and the convergence of this method is also proved to be mean-square. This ensures the feasibility of the numerical method. The practical use of these theorems and the associated algorithms is demonstrated in the numerical computations of the (omega,L delta)-periodic Lipschitz shadowing orbits of the stochastic logistic equation.

关键词： STOCHASTIC differential equations LIPSCHITZ spaces LOGISTIC functions (Mathematics) PERIODIC functions computer algorithms

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Fast parallel grid warping-based image sharpening method

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PROGRAMMING AND computer SOFTWARE 2017年第4期43卷 230-233页

作者： Gusev, A. D. Nasonov, A. V. Krylov, A. S. Moscow MV Lomonosov State Univ Dept Computat Math & Cybernet Lab Math Methods Image Proc Moscow 119991 Russia

The development of image sharpening algorithms is currently one of the most important problems in image processing. This paper presents a parallel implementation of a pixel grid warping algorithm for image sharpening. To sharpen image edges, the proposed algorithm moves pixels in the edge neighborhood towards edge centers rather than changing pixel values directly. This approach does not increase noise and does not cause ringing artifacts.

关键词： IMAGE processing computer algorithms PIXELS PROBLEM solving PARALLEL computers

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Narrow Artificial Intelligence with Machine Learning for Real-Time Estimation of a Mobile Agent's Location Using Hidden Markov Models

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INTERNATIONAL JOURNAL OF computer GAMES TECHNOLOGY 2017年第2-14期2017卷 1-10页

作者： Beaulac, Cedric Larribe, Fabrice Univ Quebec Dept Math 201 Ave President Kennedy Montreal PQ Canada

We propose to use a supervised machine learning technique to track the location of a mobile agent in real time. Hidden Markov Models are used to build artificial intelligence that estimates the unknown position of a mobile target moving in a defined environment. This narrow artificial intelligence performs two distinct tasks. First, it provides real-time estimation of the mobile agent's position using the forward algorithm. Second, it uses the Baum-Welch algorithm as a statistical learning tool to gain knowledge of the mobile target. Finally, an experimental environment is proposed, namely, a video game that we use to test our artificial intelligence. We present statistical and graphical results to illustrate the efficiency of our method.

关键词： Artificial intelligence Machine learning Real-time computing Hidden Markov models computer algorithms

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An Out Space Accelerating Algorithm for Generalized Affine Multiplicative Programs Problem

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JOURNAL OF CONTROL SCIENCE AND ENGINEERING 2017年第6-14期2017卷 1-7页

作者： Cai, Lei Tang, Shuai Yin, Jingben Hou, Zhisong Jiao, Hongwei Henan Inst Sci & Technol Sch Informat Engn Xinxiang 453003 Peoples R China Jiyuan Vocat & Tech Coll Jiyuan 459000 Peoples R China Henan Inst Sci & Technol Sch Math Sci Xinxiang 453003 Peoples R China

This paper presents an out space branch-and-bound algorithm for solving generalized affine multiplicative programs problem. Firstly, by introducing new variables and constraints, we transform the original problem into an equivalent nonconvex programs problem. Secondly, by utilizing new linear relaxation technique, we establish the linear relaxation programs problem of the equivalent problem. Thirdly, based on the out space partition and the linear relaxation programs problem, we construct an out space branch-and-bound algorithm. Fourthly, to improve the computational efficiency of the algorithm, an out space reduction operation is employed as an accelerating device for deleting a large part of the investigated out space region. Finally, the global convergence of the algorithm is proved, and numerical results demonstrate the feasibility and effectiveness of the proposed algorithm.

关键词： NONCONVEX programming ACCELERATION (Mechanics) computer algorithms PROBLEM solving COMPUTATIONAL complexity STOCHASTIC convergence

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A unified method of detecting core-periphery structure and community structure in networks

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CHAOS 2018年第1期28卷 013122-013122页

作者： Xiang, Bing-Bing Bao, Zhong-Kui Ma, Chuang Zhang, Xingyi Chen, Han-Shuang Zhang, Hai-Feng Anhui Univ Sch Math Sci Hefei 230601 Anhui Peoples R China Anhui Univ Inst Bioinspired Intelligence & Min Knowledge Sch Comp Sci & Technol Hefei 230601 Anhui Peoples R China Anhui Univ Sch Phys & Mat Sci Hefei 230601 Anhui Peoples R China Anhui Univ Ctr Informat Support & Assurance Technol Hefei 230601 Anhui Peoples R China North Univ China Dept Commun Engn Taiyuan 030051 Shanxi Peoples R China

The core-periphery structure and the community structure are two typical meso-scale structures in complex networks. Although community detection has been extensively investigated from different perspectives, the definition and the detection of the core-periphery structure have not received much attention. Furthermore, the detection problems of the core-periphery and community structure were separately investigated. In this paper, we develop a unified framework to simultaneously detect the core-periphery structure and community structure in complex networks. Moreover, there are several extra advantages of our algorithm: our method can detect not only single but also multiple pairs of core-periphery structures;the overlapping nodes belonging to different communities can be identified;different scales of core-periphery structures can be detected by adjusting the size of the core. The good performance of the method has been validated on synthetic and real complex networks. So, we provide a basic framework to detect the two typical meso-scale structures: the core-periphery structure and the community structure. Published by AIP Publishing.

关键词： COMMUNITY organization TELECOMMUNICATION computer algorithms TASK performance INFORMATION science

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Application of Fuzzy Control in a Photovoltaic Grid-Connected Inverter

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JOURNAL OF ELECTRICAL AND computer ENGINEERING 2018年第Pt.1期2018卷 3806372.1-3806372.10页

作者： Zheng, Zhaohong Zhang, Tianxia Xue, Jiaxiang South China Univ Technol Sch Mech & Automot Engn Guangzhou 510641 Guangdong Peoples R China

To realize the maximum power output of a grid-connected inverter, the MPPT (maximum power point tracking) control method is needed. The perturbation and observation (P&O) method can cause the inverter operating point to oscillate near the maximum power. In this paper, the fuzzy control P&O method is proposed, and the fuzzy control algorithm is applied to the disturbance observation method. The simulation results of the P&O method with fuzzy control and the traditional P&O method prove that not only can the new method reduce the power loss caused by inverter oscillation during maximum power point tracking, but also it has the advantage of speed. Inductive loads in the post-grid-connected stage cause grid-connected current distortion. A fuzzy control algorithm is added to the traditional deadbeat grid-connected control method to improve the quality of the system's grid-connected operation. The fuzzy deadbeat control method is verified by experiments, and the harmonic current of the grid-connected current is less than 3%.

关键词： Fuzzy control Maximum power dead-beat Control Methods computer algorithms Workstations maximum power point trackers maximum power output power loss current harmonics Inventors perturbation PO

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Critical appraisal of data used to infer record UVI in the tropical andes

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PHOTOCHEMICAL & PHOTOBIOLOGICAL SCIENCES 2017年第5期16卷 785-794页

作者： McKenzie, R. L. Liley, J. B. Madronich, S. NIWA Lauder PB 50061 Omakau 9352 Central Otago New Zealand NCAR Boulder CO 80303 USA

When the data sets that suggested record high UVI values at Mt Licancabur, and Laguna Blanca, Bolivia are reviewed in full, we find that the reported peak values are incorrect, probably due to instrumental problems. These affect the UVB, UVA and PAR channels at different times and different solar zenith angles, with distinct diurnal patterns in each case. The outliers are consistent with errors that would result from build-up of ice or snow on the surface of the entrance dome, combined with incomplete baffling of light within the integrating spheres that form the entrance optic of these instruments, but we cannot unequivocally attribute them to this cause. The analysis shows that for all three channels, cloud enhancements over clear-sky values by a factor of similar to 4 or more would be required to explain their highest values. Such repeated enhancements are not physically plausible and are more than twice those previously observed in the UV region. Further, at the time of peak reported UVB, the UVA cloud enhancement factor was less than 1.2 (i.e., UVA radiation was increased by less than 20% over clear-sky values), which implies that to explain the high UVB values, an atmospheric ozone amount (similar to 25 DU) far below the minimum ever observed would be required. The analysis also shows that the algorithm to convert from UVB to UVI is incorrect, and that if the correct algorithm had been used, the peak UVI values would have been even larger than reported. Disregarding the obviously incorrect measurements, the highest realistic values near solar noon from this dataset are in the range UVI = 25 +/- 5, which is in agreement with previous estimates in the region.

关键词： ULTRAVIOLET radiation computer algorithms ZENITH distance ATMOSPHERIC ozone

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Learning to Detect Traffic Incidents from Data Based on Tree Augmented Naive Bayesian Classifiers

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DISCRETE DYNAMICS IN NATURE AND SOCIETY 2017年第Pt.3期2017卷 1-9页

作者： Li, Dawei Hu, Xiaojian Jin, Cheng-jie Zhou, Jun Southeast Univ Sch Transportat Jiangsu Key Lab Urban ITS Jiangsu Prov Collaborat Innovat Ctr Modern Urban Sipailou 2 Nanjing 210096 Jiangsu Peoples R China Huaiyin Inst Technol Key Lab Traff & Transportat Secur Jiangsu Prov Meicheng Rd Huaian 223003 Peoples R China

This study develops a tree augmented naive Bayesian (TAN) classifier based incident detection algorithm. Compared with the Bayesian networks based detection algorithms developed in the previous studies, this algorithm has less dependency on experts' knowledge. The structure of TAN classifier for incident detection is learned from data. The discretization of continuous attributes is processed using an entropy-based method automatically. A simulation dataset on the section of the Ayer Rajah Expressway (AYE) in Singapore is used to demonstrate the development of proposed algorithm, including wavelet denoising, normalization, entropy-based discretization, and structure learning. The performance of TAN based algorithm is evaluated compared with the previous developed Bayesian network (BN) based and multilayer feed forward (MLF) neural networks based algorithms with the same AYE data. The experiment results show that the TAN based algorithms perform better than the BN classifiers and have a similar performance to the MLF based algorithm. However, TAN based algorithm would have wider vista of applications because the theory of TAN classifiers is much less complicated than MLF. It should be found from the experiment that the TAN classifier based algorithm has a significant superiority over the speed of model training and calibration compared with MLF.

关键词： NAIVE Bayes classification CLASSIFICATION algorithms TRAFFIC accidents computer algorithms BAYESIAN analysis

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