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Search Results: 1 - 10 of 7272 matches for " Temporal Prediction "
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Temporal Prediction of Aircraft Loss-of-Control: A Dynamic Optimization Approach  [PDF]
Chaitanya Poolla, Abraham K. Ishihara
Intelligent Control and Automation (ICA) , 2015, DOI: 10.4236/ica.2015.64023
Abstract: Loss of Control (LOC) is the primary factor responsible for the majority of fatal air accidents during past decade. LOC is characterized by the pilot’s inability to control the aircraft and is typically associated with unpredictable behavior, potentially leading to loss of the aircraft and life. In this work, the minimum time dynamic optimization problem to LOC is treated using Pontryagin’s Maximum Principle (PMP). The resulting two point boundary value problem is solved using stochastic shooting point methods via a differential evolution scheme (DE). The minimum time until LOC metric is computed for corresponding spatial control limits. Simulations are performed using a linearized longitudinal aircraft model to illustrate the concept.
Representation of Reward Feedback in Primate Auditory Cortex
Michael Brosch,Henning Scheich
Frontiers in Systems Neuroscience , 2011, DOI: 10.3389/fnsys.2011.00005
Abstract: It is well established that auditory cortex is plastic on different time scales and that this plasticity is driven by the reinforcement that is used to motivate subjects to learn or to perform an auditory task. Motivated by these findings, we study in detail properties of neuronal firing in auditory cortex that is related to reward feedback. We recorded from the auditory cortex of two monkeys while they were performing an auditory categorization task. Monkeys listened to a sequence of tones and had to signal when the frequency of adjacent tones stepped in downward direction, irrespective of the tone frequency and step size. Correct identifications were rewarded with either a large or a small amount of water. The size of reward depended on the monkeys’ performance in the previous trial: it was large after a correct trial and small after an incorrect trial. The rewards served to maintain task performance. During task performance we found three successive periods of neuronal firing in auditory cortex that reflected (1) the reward expectancy for each trial, (2) the reward-size received, and (3) the mismatch between the expected and delivered reward. These results, together with control experiments suggest that auditory cortex receives reward feedback that could be used to adapt auditory cortex to task requirements. Additionally, the results presented here extend previous observations of non-auditory roles of auditory cortex and shows that auditory cortex is even more cognitively influenced than lately recognized.
International Journal of Innovative Research in Computer and Communication Engineering , 2013,
Abstract: Research on evaluating recommender systems shows that algorithms in this area are still deficient in prediction accuracy but recent works prove that modeling with temporal dynamics improves the degree of recommendation accuracy. Recommendations are invariably based on similarities of users and/or items in the user-item matrix of a system, user profiles, and rating information which presumes the presence of users or items in the matrix. The major difference being in the way the algorithms analyze data sources to develop notions of affinity between users for use in identifying well matched pairs. Not many have focused on the temporal absence as an indicator of preference or concept drift: and hence a factor for inclusion in the recommender algorithms and models to improve accuracy. In this paper we to define temporal absence in the context of recommender systems and find out, through examination of the Netflix Prize data, the extent of temporal absence and the significance of such information in future research and improvement of recommendation algorithms.
Temporal Construal Level Theory:A Survey
LI Dan,YIN Hua-zhan, LI Zuo-shan,LI Zuo-shan
Journal of Chongqing Normal University , 2010,
Abstract: Temporal construal level theory explored the mechanism that the subjective evaluation of events changed with the temporal distance from now, which on one hand connected time psychology and decision psychology, and on the other hand provided basis for human rational decision and the most profit. Construal level theory proposes that temporal distance thanges people's responses to future events by changing the way people mentally represent those events. The greater the temporal distance, the more likely are events to be represented in terms of a few abstract features that convey the percerved essence of the events (high-level construals ) rather than in terms of more concrete and incidental details of the events (low-level construals ).The informational and evaluative imlications of high-level construals, compared with those of low-level construals, should therefore have more impact on responses to distant-future events than neaar-future events. In the present article, at first , the basis, intention, and proof were introduced, and the applied research about prediction and evaluation was described, and finally three problems about mechanism, number of segmentation, and post time temporal construal level were pointed out to be breach of the future research. In addition, the suggestion to the research in China was also be pointed out.
Statistical Modeling of the Residents Activity Interval in Smart Homes
M.R. Alam,M.B.I. Reaz,M.A.M. Ali
Journal of Applied Sciences , 2011,
Abstract: The activities of residents in smart homes possess temporal information which can be used to classify and model psychological behavior of the resident. In this study, a learning algorithm is proposed to predict the activity interval of smart home inhabitants. The algorithm is based on the hypothesis that residents activity intervals follow a normal distribution. To predict the starting time of the following activity, it incrementally utilizes mean and standard deviation of previous history which are applied according to the central limit theory of statistical probability. The prediction algorithm exhibits 88.3 to 95.3% prediction accuracies for different ranges of mean and standard deviations when verified by practical smart home data. Further stochastic analyses prove that the time difference between the residents activities follows normal distribution which was merely an assumption previously.
The Golden Age for Pawnshops Current Social Factors that Drive their Success in the Mexican Market
Edly Mortera
School of Doctoral Studies Journal , 2012,
Abstract: Credit plays an important role in the world's finances, but what happens when it is impossible for a great part of the population to have access to it? Besides a mismanagement of personal finances, that have led to a continuous increase in performing loans and distressed assets; there are external social factors that prohibit consumers facing their obligations by basic financial instruments such as short time loans. When unexpected bills come up, these consumers often find themselves in a bind, and they must look to alternative products. In Mexico we have a potential market of 40 million people without access to the banking system and whose needs for flexible financial options are growing constantly. Today the banking industry serves only 20% of demand. Facing this scenario, and complimented by the factors discussed below, a huge opportunity arises for a last resort lender: The Pawn Shops.
Intra prediction algorithm for H.264 based on temporal correlation

HU Shao-hu,YE Shui-sheng,ZHOU Deng-feng,

计算机应用研究 , 2010,
Abstract: In order to reduce the computational complexity, this paper proposed a fast algorithm for the intra-prediction mode selection. By analyzing the spatial correlation and temporal correlation of intra-frame prediction mode, the algorithm used intra-frame prediction modes of macro-blocks in coded frames as the candidate modes of current macro-block, which reduced the cost of computation. Experimental results show that the coding time reduces about 10% without obvious PSNR change.
Yellow River Valley flood and drought disaster:spatial-temporal distribution predictionand early-warning
Gao Lin,Sha Wanying,Liu Huaiquan,Yang Xinhai,
Gao Lin
,Sha Wanying,Liu Huaiquan,Yang Xinhai

环境科学学报(英文版) , 1994,
Abstract: By means of analysing the historical data of flood-drought grade series in the past 2000 years(A.D.0-1900),especially in the last 5000 years (1470-1900) , this paper revealed the spatial-temporaldistribution features of severe flood and drought in Yellow River Valley. Statistical methods of varianceanalysis, probability transition and the principles of scale correspondence were employed tocomprehensively predicate 90's tendency of severe flood and drought in the Yellow River Valley. In addi-tion, this paper pointed out the possible breaching dikes, sectors and the flooding ranges by future's se-vere flood, meanwhile estimating the associated economic losses and impact to environment.
A Study of Ecological Geochemcal Early Prediction and Warning in Qingdao City

DAI Jie-rui,ZHAO Xi-qiang,YU Chao,WANG Zeng-hui,PANG Xu-gui,SUN Bin-bin,

地球学报 , 2011,
Abstract: Based on agro-ecological geochemical survey of eastern Shandong Province, the authors divided Qingdao City into 4 types and 11 eco-geochemical areas for ecological environment status early warning. Mathematical statistics, correlation analysis and comparison were conducted between the data obtained from regional survey of north Qingdao (2200 km2) in 2003 and those in 2007 to study the temporal and spatial variation of elements in soil. The result reveals that such elements in soil as P, OrgC, Ba, La, Ag, B, W, Ga, Ge and Co were accumulated significantly in the four years, and elements like N, Bi, Hg, Cd, Au, OrgC and Pb were accumulated remarkably in some places of the study area, and the acidification of soil (pH decrease) was observable. These data strongly suggest that much attention should be paid to the environment. According to the accumulation rate of elements in soil in the four years, the environment quality changes of soil was predicted, and some suggestions were put forward.
Silhouette Based Human Motion Detection and Recognising their Actions from the Captured Video Streams
Deepak. N. A,Dr.U. N. Sinha
International Journal of Advanced Networking and Applications , 2011,
Abstract: Human detection and recognizing their actions from the captured video streams is more complex and challenging task in the field of image processing. The human action recognition is more complex due to variability in shapes and articulation of human body, motions in the background scene, lighting conditions and occlusion. Human actions are recognized by tracking the selected object over the consecutive frames of gray scale image sequences, initially the background motion of the input video stream is subtracted, and its binary images are constructed, the object which needs to be monitored is selected by enclosing the required pixels within bounding rectangle, by using spatio-temporal interest points (Mo-SIFT). The selected foreground pixels within the bounding rectangle are then tracked using edge tracking algorithm over the consecutive frames of gray scale images. The features like horizontal stride (HS) and vertical distance (VD) are extracted while tracking and the values of these features from the current frame are subtracted with the previous frame values to know the motion. The obtained results after subtraction are then compared with the selected threshold value to predict the type of human action using linear prediction technique. This methodology finds an application where monitoring the human actions is required such as shop surveillance, city surveillance, airports surveillance and other places where security is the prime factor.
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