• Journal of Korea Multimedia Society
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• v.9 no.12
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• pp.1529-1541
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• 2006

Moving objects have been widely employed in traffic and logistic applications. Spatio-temporal aggregations mainly describe the moving object's behavior in the spatial data warehouse. The previous works usually express the object moving in some certain region, but ignore the object often moving along as the trajectory. Other researches focus on aggregation and comparison of trajectories. They divide the spatial region into units which records how many times the trajectories passed in the unit time. It not only makes the storage space quite ineffective, but also can not maintain spatial data property. In this paper, a spatio-temporal aggregation index structure for moving object trajectory in constrained network is proposed. An extended B-tree node contains the information of timestamp and the aggregation values of trajectories with two directions. The network is divided into segments and then the spatial index structure is constructed. There are the leaf node and the non leaf node. The leaf node contains the aggregation values of moving object's trajectory and the pointer to the extended B-tree. And the non leaf node contains the MBR(Minimum Bounding Rectangle), MSAV(Max Segment Aggregation Value) and its segment ID. The proposed technique overcomes previous problems efficiently and makes it practicable finding moving object trajectory in the time interval. It improves the shortcoming of R-tree, and makes some improvement to the spatio-temporal data in query processing and storage.

• Journal of KIISE:Databases
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• v.32 no.6
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• pp.567-584
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• 2005

Temporal data mining, the incorporation of temporal semantics to existing data mining techniques, refers to a set of techniques for discovering implicit and useful temporal knowledge from temporal data. Association rules and classification are applied to various applications which are the typical data mining problems. However, these approaches do not consider temporal attribute and have been pursued for discovering knowledge from static data although a large proportion of data contains temporal dimension. Also, data mining researches from temporal data treat problems for discovering knowledge from data stamped with time point and adding time constraint. Therefore, these do not consider temporal semantics and temporal relationships containing data. This paper suggests that temporal associative classification technique based on temporal class association rules. This temporal classification applies rules discovered by temporal class association rules which extends existing associative classification by containing temporal dimension for generating temporal classification rules. Therefore, this technique can discover more useful knowledge in compared with typical classification techniques.

• Journal of Korea Spatial Information System Society
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• v.5 no.2 s.10
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• pp.5-21
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• 2003

Sptaio-temporal databases are important to store the real-time location information of large spatio-temporal objects efficiently and retrieve them rapidly. Accordingly necessity for spatio-temporal database system that can manage spatial information, aspatial information and temporal information of spatio-temporal objects is increasing. Sptaio-temporal databases are important to store the real-time location information of large spatio-temporal objects efficiently and retrieve them rapidly. Accordingly necessity for spatio-temporal database system that can manage spatial information, aspatial information and temporal information of spatio-temporal objects is increasing. Therefore, in this paper, we propose a spatio-temporal data model that is able to efficiently manage historical spatio-temporal objects that change dynamically their states as time. Also, various spatio-temporal operations and constraint conditions are defined to keep integrity of spatio-temporal data and spatio-temporal operations.

• Proceedings of the KSPS conference
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• 2007.05a
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• pp.213-216
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• 2007

The purpose of this study is to observe how Korean learners with low (KL) and high (KH) English proficiency manifest English rhythm with respect to the relative temporal stability or temporal constraint of syllable. In this study, speech cycling task, repeating a short phrase with the series of beeps of same interval, was used to examine temporal distribution of stressed beats.

• Journal of KIISE:Databases
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• v.32 no.1
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• pp.43-55
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• 2005

Spatiotemporal databases support methods of recording and querying for spatiotemporal data to user by offering both spatial management and historical information on various types of objects in the real world. We can answer to the following query in real world: 'What is the average of volume of pesticide sprayed for cach farm land from April to August on 2001, within some query window' Such aggregation queries have both temporal and spatial constraint. However, previous works for aggregation are attached only to temporal aggregation or spatial aggregation. So they have problems that are difficult to apply for spatiotemporal data directly which have both spatial and temporal constraint. Therefore, in this paper, we propose spatiotemporal aggregate functions for analysis of spatiotemporal data which have spatiotemporal characteristic, such as stCOUNT, stSUM, stAVG, stMAX, stMIN. We also show that our proposal resulted in the convenience and improvement of query in application systems, and facility of analysis on spatiotemporal data which the previous temporal or spatial aggregate functions are not able to analyze, by applying to the estate management system. Then, we show the validity of our algorithm performance through the evaluation of spatiotemporal aggregate functions.

• Geophysics and Geophysical Exploration
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• v.21 no.3
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• pp.139-149
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• 2018

The resistivity monitoring is a practical method to resolve changes in resistivity of underground structures over time. With the advance of sophisticated automatic data acquisition system and rapid data communication technology, resistivity monitoring has been widely applied to understand spatio-temporal changes of subsurface. In this study, a new 4D inversion algorithm is developed, which can effectively emphasize significant changes of underground resistivity with time. To overcome the overly smoothing problem in 4D inversion, the Lagrangian multipliers in the space-domain and time-domain are determined automatically so that the proportion of the model constraints to the misfit roughness remains constant throughout entire inversion process. Furthermore, a focusing model constraint is added to emphasize significant spatio-temporal changes. The performance of the developed algorithm is demonstrated by the numerical experiments using the synthetic data set for a time-lapse model.

• Journal of Intelligence and Information Systems
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• v.13 no.4
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• pp.121-135
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• 2007

Constraint directed scheduling techniques, representing problem constraints explicitly and constructing schedules by constrained heuristic search, have been successfully applied to real world scheduling problems that require satisfying a wide variety of constraints. However, there has been little basic research on the representation and optimization of the objective value of a schedule in the constraint directed scheduling literature. In particular, the cost objective is very crucial for enterprise decision making to analyze the effects of alternative business plans not only from operational shop floor scheduling but also through strategic resource planning. This paper aims to explicitly represent and optimize the total cost of a schedule including the tardiness and inventory costs while satisfying non-relaxable constraints such as resource capacity and temporal constraints. Within the cost based scheduling framework, a cost propagation algorithm is presented to update cost information throughout temporal constraints within the same job.

• KNOM Review
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• v.22 no.3
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• pp.25-30
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• 2019

For meteorological applications, meaningful results must be derived and provided within time and resource limits. Forecasts through numerous historical data are time-consuming and still have resource limitations in the case of disaster safety-related analyses/predictions such as local typhoon forecasts. Suitable forecasts should be provided without any problems caused by limited physical environmental conditions and when results are to be drawn under time constraints, such as typhoon forecasts and forecast services for flooded areas by road. In this paper, we analyze the application of weather and climate forecasting to provide a suitable forecasting service in both temporal and resource conditions. Through the analysis of execution time according to mesh sizes, it was confirmed that a mesh adjustment can cope with the case of the temporal constraint. In addition, by analyzing the execution time through memory resource control, we confirmed the minimum resource condition that does not affect the performance and the resource usage pattern of the application through the swap and mlock analysis.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.18 no.4
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• pp.490-498
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• 1993

A variety of methods for measuring the velocity from an image sequence use the relationship between the spatial and temporal gradients of image brightness function. In most situations, an additional constraint is required because the velocity is not determined uniquely by a above relationship. Horn and Schunch proposed a constraint that the velocity field should vary smoothly over the image. This requirement, however, forces the velocity field to vary smoothly even across motion boundaries. To complement this probe, Nagel introduced and 'oriented smoothness' constraint which restricts variations of velocity field only in directions with small or no variation of image brightness function. On the other hand, Paquin and Dubois proposed a different type of constraint that the velocity is constant in a small area of image. But, this constraint also creates difficulties at motion boundaries which large variations in velocity field often occur. We propose the method to overcome these difficulties by utilizing the information of discontinuities in image brightness function, and present the experimental results.

• Journal of information and communication convergence engineering
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• v.1 no.4
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• pp.177-182
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• 2003

Conventional multilayer feedforward artificial neural networks are very effective in dealing with spatial problems. To deal with problems with time dependency, some kinds of memory have to be built in the processing algorithm. In this paper we show how the newly proposed Serial Input Neuron (SIN) convolutional decoders can be derived. As an example, we derive the SIN decoder for rate code with constraint length 3. The SIN is tested in Gaussian channel and the results are compared to the results of the optimal Viterbi decoder. A SIN approach to decode convolutional codes is presented. No supervision is required. The decoder lends itself to pleasing implementations in hardware and processing codes with high speed in a time. However, the speed of the current circuits may set limits to the codes used. With increasing speeds of the circuits in the future, the proposed technique may become a tempting choice for decoding convolutional coding with long constraint lengths.