• KIPS Transactions on Software and Data Engineering
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• v.3 no.10
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• pp.397-406
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• 2014

In order to answer the questions successfully on behalf of the human in DeepQA environments such as Jeopardy! of the American quiz show, the computer is required to have the capability of fast temporal and spatial reasoning on a large-scale commonsense knowledge base. In this paper, we present a scalable spatial reasoning algorithm for deriving efficiently new directional and topological relations using the MapReduce framework, one of well-known parallel distributed computing environments. The proposed reasoning algorithm assumes as input a large-scale spatial knowledge base including CSD-9 directional relations and RCC-8 topological relations. To infer new directional and topological relations from the given spatial knowledge base, it performs the cross-consistency checks as well as the path-consistency checks on the knowledge base. To maximize the parallelism of reasoning computations according to the principle of the MapReduce framework, we design the algorithm to partition effectively the large knowledge base into smaller ones and distribute them over multiple computing nodes at the map phase. And then, at the reduce phase, the algorithm infers the new knowledge from distributed spatial knowledge bases. Through experiments performed on the sample knowledge base with the MapReduce-based implementation of our algorithm, we proved the high performance of our large-scale spatial reasoner.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.39B no.6
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• pp.333-340
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• 2014

Despite the security weakness of reusing passwords, many Internet users are likely to use a single ID and password on various sites to avoid the inconvenience of remembering multiple credentials. This paper proposes a scheme for securely storing, retrieving, and updating randomly chosen (ID, password) pairs by using smart cards as secure and portable storages. The scheme makes a user free from remembering her (ID, password) pairs for Internet accesses. By splitting and scattering the (ID, password) pairs of a user across the user's smart card memory and a remote server's storage, it can protect the logon credentials even from the theft or loss of the smart card. Also, a user, if deemed necessary, can issue and let the server to delete all information belonging to the user. Hence even an attacker who cracked the smart card memory would not be able to obtain any (ID, password) pair of the victim thereafter. The scheme requires a user to input a site information and pass-phrase to her smart card to obtain the logon credentials, but it should be an acceptable overhead considering the benefits of not remembering the freely chosen (ID, password) pairs at all.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.21 no.3
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• pp.414-419
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• 2020

An artificial intelligence-based cable tension estimation model was developed to expand the utilization of data obtained from cable accelerometers of cable-stayed bridges. The model was based on an algorithm for selecting the natural frequency in the tension estimation process based on the vibration method and an applied artificial neural network (ANN). The training data of the ANN was composed after converting the cable acceleration data into the frequency, and machine learning was carried out using the characteristics with a pattern on the natural frequency. When developing the training data, the frequencies with various amplitudes can be used to represent the frequencies of multiple shapes to improve the selection performance for natural frequencies. The performance of the model was estimated by comparing it with the control criteria of the tension estimated by an expert. As a result of the verification using 139 frequencies obtained from the cable accelerometer as the input, the natural frequency was determined to be similar to the real criteria and the estimated tension of the cable by the natural frequency was 96.4% of the criteria.

• Proceedings of the Korean Information Science Society Conference
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• 2006.10d
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• pp.24-29
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• 2006

본 논문에서는 광대역 통신 방송 융합 서비스 제공을 고려한 WDM 메트로 링 망을 위한 매체 접근 제어(Medium Access Control; MAC) 프로토콜의 성능을 분석한다. 현재 인터넷은 통신 방송 융합 망으로 진화하고 있으며 다양한 트래픽 특성을 갖는 서비스가 액세스 망에서 메트로 망으로 유입되고 있다. 그러나 기존 메트로 망의 MAC 프로토콜은 이러한 망 환경 변화를 고려하지 않고 단순하고 동일한 트래픽만을 고려하여 성능을 분석하였다. 따라서 본 논문에서는 메트로 링에 연결된 액세스 노드의 입력 트래픽을 Self-Similar와 Poisson 트래픽으로 분류하여 기존 MAC 프로토콜의 성능을 분석하고 평가한다. 메트로 링 망에 연결된 액세스 노드는 이 두 종류의 트래픽 중에서 하나를 망에 유입하며 채널을 공유하는 노드 수에 따라서 다양한 트래픽 환경이 고려된다. WDM 메트로 링망의 기본 MAC 프로토콜은 CSMA/CA(Carrier Sense Multiple Access with Collision Avoidance)이며, 패킷을 빈 슬롯에 전송하고 송신지에서 패킷을 제거하는 SS (Source-Stripping) 기반으로 운용된다. 본 논문에서는 SS 방식으로 생성된 빈 슬롯을 바로 패킷 전송에 이용하는 방식과 그렇지 않은 방식을 각각 1-Persistent와 non-Persistent로 분류하고 MAC 프로토콜을 분석하여 기존 방식의 장 단점을 비교한다. 또한 전송 공정성과 처리율을 같이 고려하여 적용할 수 있는 확률 기반 p-Persistent MAC 프로토콜도 분석하였으며 시뮬레이션을 통하여 각 프로토콜을 노드 처리율, 전송 지연, 패킷 손실률, 전송 공정성 관점에서 비교하고 평가한다.y 수행을 여러 서버로 분산처리하게 함으로써 성능에 대한 신뢰성을 향상 시킬 수 있는 Load Balancing System을 제안한다.할 때 가장 효과적인 라우팅 프로토콜이라고 할 수 있다.iRNA 상의 의존관계를 분석할 수 있었다.수안보 등 지역에서 나타난다 이러한 이상대 주변에는 대개 온천이 발달되어 있었거나 새로 개발되어 있는 곳이다. 온천에 이용하고 있는 시추공의 자료는 배제하였으나 온천이응으로 직접적으로 영향을 받지 않은 시추공의 자료는 사용하였다 이러한 온천 주변 지역이라 하더라도 실제는 온천의 pumping 으로 인한 대류현상으로 주변 일대의 온도를 올려놓았기 때문에 비교적 높은 지열류량 값을 보인다. 한편 한반도 남동부 일대는 이번 추가된 자료에 의해 새로운 지열류량 분포 변화가 나타났다 강원 북부 오색온천지역 부근에서 높은 지열류량 분포를 보이며 또한 우리나라 대단층 중의 하나인 양산단층과 같은 방향으로 발달한 밀양단층, 모량단층, 동래단층 등 주변부로 NNE-SSW 방향의 지열류량 이상대가 발달한다. 이것으로 볼 때 지열류량은 지질구조와 무관하지 않음을 파악할 수 있다. 특히 이러한 단층대 주변은 지열수의 순환이 깊은 심도까지 가능하므로 이러한 대류현상으로 지표부근까지 높은 지온 전달이 되어 나타나는 것으로 판단된다.의 안정된 방사성표지효율을 보였다. $^{99m}Tc$-transferrin을 이용한 감염영상을 성공적으로 얻을 수 있었으며, $^{67}Ga$-citrate 영상과 비교하여 더 빠른 시간 안에 우수한 영상을 얻을 수 있었다. 그러므로 $^{99m}Tc$-transierrin이 감염 병소의 영상진단에 사용될 수 있을 것으로 기대된

• Journal of Internet Computing and Services
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• v.18 no.6
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• pp.85-92
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• 2017

Recently, in the field of video surveillance, a Deep Learning based learning method has been applied to a method of detecting a moving person in a video and analyzing the behavior of a detected person. The human activity recognition, which is one of the fields this intelligent image analysis technology, detects the object and goes through the process of detecting the body keypoint to recognize the behavior of the detected object. In this paper, we propose a method for Body Keypoint Localization based on Object Detection using RGB-D information. First, the moving object is segmented and detected from the background using color information and depth information generated by the two cameras. The input image generated by rescaling the detected object region using RGB-D information is applied to Convolutional Pose Machines for one person's pose estimation. CPM are used to generate Belief Maps for 14 body parts per person and to detect body keypoints based on Belief Maps. This method provides an accurate region for objects to detect keypoints an can be extended from single Body Keypoint Localization to multiple Body Keypoint Localization through the integration of individual Body Keypoint Localization. In the future, it is possible to generate a model for human pose estimation using the detected keypoints and contribute to the field of human activity recognition.

• Smart Media Journal
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• v.1 no.2
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• pp.40-46
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• 2012

In this paper, we describe interactive contents which is used the result of the inputted interface recognizing vision-based body gesture. Because the content uses the imp which is the common culture as the subject in Asia, we can enjoy it with culture familiarity. And also since the player can use their own gesture to fight with the imp in the game, they are naturally absorbed in the game. And the users can choose the multiple endings of the contents in the end of the scenario. In the part of the gesture recognition, KINECT is used to obtain the three-dimensional coordinates of each joint of the limb to capture the static pose of the actions. The vision-based 3D human pose recognition technology is used to method for convey human gesture in HCI(Human-Computer Interaction). 2D pose model based recognition method recognizes simple 2D human pose in particular environment On the other hand, 3D pose model which describes 3D human body skeletal structure can recognize more complex 3D pose than 2D pose model in because it can use joint angle and shape information of body part Because gestures can be presented through sequential static poses, we recognize the gestures which are configured poses by using HMM In this paper, we describe the interactive content which is used as input interface by using gesture recognition result. So, we can control the contents using only user's gestures naturally. And we intended to improve the immersion and the interest by using the imp who is used real-time interaction with user.

• Journal of the Korea institute for structural maintenance and inspection
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• v.21 no.6
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• pp.113-125
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• 2017

In spite of bulk literature about the tuning of TMD, the effectiveness of TMD in reducing the seismic response of engineering structures is still in a row. This paper deals with the optimum tuning parameters of a passive TMD and simulated on MATLAB with a ten-story numerical shear building. A weighted multi-objective optimization method based on computer experiment consisting of coupled with central composite design(CCD) central composite design and response surface methodology(RSM) was applied to find out the optimum tuning parameters of TMD. After the optimization, the so-conceived TMD turns out to be optimal with respect to the specific seismic event, hence allowing for an optimum reduction in seismic response. The method was employed on above structure by assuming first the El Centro seismic input as a sort of benchmark excitation, and then additional recent strong-motion earthquakes. It is found that the RSM based weighted multi-objective optimized damper improves frequency responses and root mean square displacements of the structure without TMD by 31.6% and 82.3% under El Centro earthquake, respectively, and has an equal or higher performance than the conventionally designed dampers with respect to frequency responses and root mean square displacements and when applied to earthquakes.

• Journal of the Institute of Convergence Signal Processing
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• v.11 no.2
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• pp.137-142
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• 2010

Although multi-model speech recognizer has been shown to be quite successful in noisy speech recognition, the results were based on general speech front-ends which do not take into account noise adaptation techniques. In this paper, for the accurate evaluation of the multi-model based speech recognizer, we adopted a quite noise-robust speech front-end, AFE, which was proposed by the ETSI for the noisy DSR environment. For the performance comparison, the MTR which is known to give good results in the DSR environment has been used. Also, we modified the structure of the multi-model based speech recognizer to improve the recognition performance. N reference HMMs which are most similar to the input noisy speech are used as the acoustic models for recognition to cope with the errors in the selection of the reference HMMs and the noise signal variability. In addition, multiple SNR levels are used to train each of the reference HMMs to improve the robustness of the acoustic models. From the experimental results on the Aurora 2 databases, we could see better recognition rates using the modified multi-model based speech recognizer compared with the previous method.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.42 no.4
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• pp.819-830
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• 2017

An FM radio based PCL system is a passive radar technique for detecting the multiple moving targets from FM radio signals and tracking the trajectories of the targets by calculating the cross-correlation function of direct-path signal and target echo signals. However, the interference signals are received from a surveillance channel, which is designed to receive the target echo signals. Because of this problem, the target echo signals are masked by the strong interference signals and this makes it difficult to detect the true targets from the cross-correlation function. Adaptive filters are known as effective methods for suppressing the interference signals but there is a problem to present their accurate performances in the PCL system because many literatures used the cross-correlation function and the ratio of input and output power as a measure of the performance analysis. In this paper, a performance analysis method is proposed to evaluate the performance of interference cancellation algorithms. By using the property that each component of the filter weight vector is adjusted to suppress the specific interference signal, a performance measure of the interference signal suppression is defined by a function of adaptive filter weights. Based on the proposed method, we compare the performance of the adaptive filters used in the PCL system. Simulation results show that the proposed method can be very effective for evaluating the performance of interference cancellation algorithms.

• Journal of KIISE:Software and Applications
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• v.32 no.6
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• pp.554-569
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• 2005

In the semistructured distributed documents, it is very difficult to formalize and implement the query processing system due to the lack of structure and rule of the data. In order to precisely retrieve and process the heterogeneous semistructured documents, it is required to handle multiple mappings such as 1:1, 1:W and W:1 on an element simultaneously and to generate the schema from the distributed documents. In this paper, we have proposed an query processing algorithm for querying and answering on the heterogeneous semistructured data or documents over distributed systems and implemented with a metadata interface. The algorithm for generating local queries from the global query consists of mapping between g1oba1 and local nodes, data transformation according to the mapping types, path substitution, and resolving the heterogeneity among nodes on a global input query with metadata information. The mapping, transformation, and path substitution algorithms between the global schema and the local schemas have been implemented the metadata interface called DBXMI (for Distributed Documents XML Metadata Interface). The nodes with the same node name and different mapping or meanings is resolved by automatically extracting node identification information from the local schema automatically. The system uses Quilt as its XML query language. An experiment testing is reported over 3 different OEM model semistructured restaurant documents. The prototype system is developed under Windows system with Java and JavaCC compiler.