• Journal of the Korea Institute of Information and Communication Engineering
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• v.19 no.12
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• pp.2885-2891
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• 2015

Twitter, one of online social network services, is one of the most popular micro-blogs, which generates a large number of automated programs, known as tweet bots because of the open structure of Twitter. While these tweet bots are categorized to legitimate bots and malicious bots, it is important to detect tweet bots since malicious bots spread spam and malicious contents to human users. In the conventional work, temporal information was utilized for the classficiation of human and bot. In this paper, by utilizing geo-tagged tweets that provide high-precision location information of users, we first identify both Twitter users' exact location and the corresponding timestamp, and then propose an improved two-stage tweet bot detection algorithm by computing an entropy based on spatio-temporal information. As a main result, the proposed algorithm shows superior bot detection and false alarm probabilities over the conventional result which only uses temporal information.

• Proceedings of the Korean Information Science Society Conference
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• 2000.10a
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• pp.57-59
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• 2000

실세계의 객체들은 공간 정보뿐만 아니라 시간적 정보와도 연관을 갖는데 기존의 공간데이터베이스만으로는 시간 흐름에 따른 공간 객체의 정보를 효율적으로 관리해 주지 못하는 단점이 있다. 이러한 문제점을 해결하기 위하여 시공간 데이터베이스에 대한 데이터 모델과 시공간 연산자가 제시되었다. 그러나, 시공간 연산자에 대한 정의와 시그너처정도 만이 기술되었고 시공간 연산자에 대한 설계와 구현에 대한 사항은 제시되지 않았다. 이 논문에서는 시공간 데이터모델과 시공간 연산자 그리고 공간 연산자 구현 기법인 Planc-Sweep 기법을 이용한 시공간 연산자인 Trajectory와 MPIntersection에 대한 설계와 구현 알고리즘을 제시하였다.

• Proceedings of the Korean Information Science Society Conference
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• 2001.10c
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• pp.745-747
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• 2001

대역폭이 보장되지 않는 인터넷 상에서 대용량의 멀티미디어 데이터를 실시간으로 서비스하는 것은 여러가지 문제점을 안고 있다. 이에 미디어 데이터의 전송량을 줄이기 위한 연구로서 layered coding을 통한 스케일러블 전송에 대한 연구가 시도되었다. 본 논문에서는 MPEG 비디오 스트림의 스케일러블 전송을 가능케 하기 위하여 Temporal-Fidelity Scaling 기법을 제안하며, MPEG-4 Visual Component에서의 적용 방법에 대해 제안하고자 한다.

• The Transactions of the Korean Institute of Electrical Engineers D
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• v.53 no.8
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• pp.606-610
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• 2004

A noble caption text detection and recognition algorithm using the temporal nature of video is proposed in this paper. A text registration technique is used to locate the temporal and spatial positions of captions in video from the accumulated frame difference information. Experimental results show that the proposed method is effective and robust. Also, a high processing speed is achieved since no time consuming operation is included.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.12 no.7
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• pp.3239-3267
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• 2018

Image and video dehazing is a popular topic in the field of computer vision and digital image processing. A fast, optimized dehazing algorithm was recently proposed that enhances contrast and reduces flickering artifacts in a dehazed video sequence by minimizing a cost function that makes transmission values spatially and temporally coherent. However, its fixed-size block partitioning leads to block effects. The temporal cost function also suffers from the temporal non-coherence of newly appearing objects in a scene. Further, the weak edges in a hazy image are not addressed. Hence, a video dehazing algorithm based on well designed spectral clustering is proposed. To avoid block artifacts, the spectral clustering is customized to segment static scenes to ensure the same target has the same transmission value. Assuming that edge images dehazed with optimized transmission values have richer detail than before restoration, an edge intensity function is added to the spatial consistency cost model. Atmospheric light is estimated using a modified quadtree search. Different temporal transmission models are established for newly appearing objects, static backgrounds, and moving objects. The experimental results demonstrate that the new method provides higher dehazing quality and lower time complexity than the previous technique.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.9 no.6
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• pp.2217-2229
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• 2015

Since the variations of illumination, the irregular changes of human shapes, and the partial occlusions, multiple person tracking is a challenging work in computer vision. In this paper, we propose a graph clustering method based on spatio-temporal information of moving objects for multiple person tracking. First, the part-based model is utilized to localize individual foreground regions in each frame. Then, we heuristically leverage the spatio-temporal constraints to generate a set of reliable tracklets. Finally, the graph shift method is applied to handle tracklet association problem and consequently generate the completed trajectory for individual object. The extensive comparison experiments demonstrate the superiority of the proposed method.

• Proceedings of the Korea Inteligent Information System Society Conference
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• 2001.06a
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• pp.377-381
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• 2001

An ATMS(Assumption-based Truth Maintenance System) has been widely used for maintaining the truth of information by detecting and solving contradictions in nile-based systems. But the ATMS can not correctly maintain the truth of the information in case that the generated information is satisfied within a time interval or includes data about temporal relations of events in time varying situations, because it has no mechanism manipulating temporal data. In this paper, The extended ATMS method is proposed, which can maintain the truth of the information in the inference system using information changing over time or temporal relations of events. In order to maintain contexts generated by relations of events, the label representation method is modified, the disjunction, conjunction simplification method in the label-propagation procedure and nogood handling method of the conventional ATMS are modified, too.

• Journal of Information Processing Systems
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• v.17 no.2
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• pp.242-252
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• 2021

Following the intuition that the local information in time instances is hardly incorporated into the posterior sequence in long short-term memory (LSTM), this paper proposes an attention augmented mechanism for fault diagnosis of the complex chemical process data. Unlike conventional fault diagnosis and classification methods, an attention mechanism layer architecture is introduced to detect and focus on local temporal information. The augmented deep network results preserve each local instance's importance and contribution and allow the interpretable feature representation and classification simultaneously. The comprehensive comparative analyses demonstrate that the developed model has a high-quality fault classification rate of 95.49%, on average. The results are comparable to those obtained using various other techniques for the Tennessee Eastman benchmark process.

• Journal of Korean Institute of Industrial Engineers
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• v.16 no.2
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• pp.63-70
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• 1990

This paper presents a new temporal reasoning scheme based on explicit expression of time intervals. The proposed scheme deals with the general problem of temporal knowledge representation and temporal reasoning and may be used in rule-based systems and qualitative models. Time intervals, not time points, are defined in terms of orders and/or numbers in a quantity space. As a result, the system behavior is represented in the form of partially ordered networks. Such explicit and qualitative description of temporal quantities enables both reduction of ambiguity and parsimonious used of temporal information. Based on the proposed temporal reasoning scheme, a new rule-based qualitative simulation system is being built and evaluated.

• Journal of KIISE:Software and Applications
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• v.26 no.1
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• pp.80-80
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• 1999

As Temporal DataBase Systems(TDBSs) manages both the historical versions and the current version of each data item, a temporal transaction may access more data records than atransaction in traditional database systems. Hence, the concurrency control subsystem of temporaldatabase management system should be able to correctly and efficiently detect actual conflicts amongconcurrent temporal transactions while the cost of detecting conflicts is maintained in low levelwithout detecting false conflicts which cause severe degradation of system throughput.In this paper, Two-Level Conflict Detection(TLCD) scheme is proposed for efficient conflictdetection between concurrent temporal transactions in TDBs. In the proposed TLCD scheme, sincechecking conflict between concurrent temporal transactions is performed at two levels, i, e., logicallevel and physical level, conflicts between concurrent temporal transactions are efficiently and correctlydetected,Furthermore, we also evaluate the performance of the proposed TLCD scheme with those oftraditional conflict detection schemes, logical-level conflict detection scheme and physical-level conflictdetection scheme by simulation approach, The result of the simulation study shows that the proposedTLCD scheme outperforms the previous conflict detection schemes with respect to the averageresponse time.