• Journal of KIISE
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• v.42 no.2
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• pp.190-202
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• 2015

Much research has been conducted on location-based intelligent personal assistants that can understand a user's intention by learning the user's route model and then inferring the user's destinations and routes using data of GPS and other sensors in a smartphone. The intelligence of the location-based personal assistant is contingent on the accuracy and efficiency of the real-time predictions of the user's intended destinations and routes by processing movement information based on uncertain sensor data. We propose a robust particle filter based on Dynamic Bayesian Network model to infer the user's routes. The proposed robust particle filter includes a particle generator to supplement the incorrect and incomplete sensor information, an efficient switching function and an weight function to reduce the computation complexity as well as a resampler to enhance the accuracy of the particles. The proposed method improves the accuracy and efficiency of determining a user's routes and destinations.

• Journal of Microbiology and Biotechnology
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• v.28 no.8
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• pp.1318-1331
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• 2018

Lettuce (Lactuca sativa L.) is a major ingredient used in many food recipes in South Korea. Lettuce samples were collected during their maximum production period between April and July in order to investigate the microbiota of lettuce during different seasons. 16S rRNA gene-based sequencing was conducted using Illumina MiSeq, and real-time PCR was performed for quantification. The number of total bacterial was greater in lettuce collected in July than in that collected in April, albeit with reduced diversity. The bacterial compositions varied according to the site and season of sample collection. Potential pathogenic species such as Bacillus spp., Enterococcus casseliflavus, Klebsiella pneumoniae, and Pseudomonas aeruginosa showed season-specific differences. Results of the network co-occurrence analysis with core genera correlations showed characteristics of bacterial species in lettuce, and provided clues regarding the role of different microbes, including potential pathogens, in this microbiota. Although further studies are needed to determine the specific effects of regional and seasonal characteristics on the lettuce microbiota, our results imply that the 16S rRNA gene-based sequencing approach can be used to detect pathogenic bacteria in lettuce.

• The Journal of the Korea Contents Association
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• v.15 no.2
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• pp.11-20
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• 2015

In this paper, we develop an intelligent mobile surveillance system based on binary CDMA for the unmanned automatic tracking and surveillance. That is, we implement a intelligent surveillance system using the binary CDMA wireless communication technology which is applied the merit of CDMA and TDMA on it complexly. This system is able to monitor the site of the accident on network in real time and process the various situations by implementing the security surveillance system. This system pursues an object by the 360-degree using camera, expands image using a PTZ(Pan/Tilt/Zoom) camera zooming function, identifies the mobile objects image within a screen and transfers the identified image to the remote site. Finally, we show the efficiency of the implemented system through the simulation of the controlled situations, such as tracking coverage on objects, object expansion, object detection number, monitoring the remote transferred image, number of frame per second by the image output signal etc..

• IMMUNE NETWORK
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• v.11 no.4
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• pp.203-209
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• 2011

Background: T cell immunoglobulin mucin containing molecule (TIM)-3 is expressed in differentiated Th1 cells and is involved in the suppression of the cytokine production by these cells. However, the regulation of the expression of other T cell genes by TIM-3 is unclear. Herein, we attempted to identify differentially expressed genes in cells abundantly expressing TIM-3 compared to cells with low expression of TIM-3. Methods: TIM-3 overexpressing cell clones were established by transfection of Jurkat T cells with TIM-3 expression vector. For screening of differentially expressed genes, gene fishing technology based on reverse transcription-polymerase chain reaction (RT-PCR) using an annealing control primer system was used. The selected candidate genes were validated by semi quantitative and real-time RT-PCR. Results: The transcription of TIMP-1, IFITM1, PAR3 and CCL1 was different between TIM-3 overexpressing cells and control cells. However, only CCL1 transcription was significantly different in cells transiently transfected with TIM3 expression vector compared with control cells. CCL1 transcription was increased in primary human $CD4^+$ T cells abundantly expressing TIM-3 but not in cells with low expression of TIM-3. Conclusion: CCL1 was identified as a differentially transcribed gene in TIM-3-expressing $CD4^+$ T cells.

• Journal of the Institute of Electronics and Information Engineers
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• v.52 no.6
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• pp.21-31
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• 2015

The Internet users want to get real-time services for various multi-media applications. Network traffic rate has been rapidly increased, and data amounts that the Internet has to carry have been exponentially increased. A packet is the basic unit in transferring data at the Internet, and packet classification is one of the most challenging functionalities that routers should perform at wire-speed. Among various known packet classification algorithms, area-based quad-trie (AQT) algorithm is one of the efficient algorithms which can lookup five header fields simultaneously. As a representative space decomposition algorithm, the AQT requires a small amount of memory in storing classification rules, but it does not provide high-speed classification performance. In this paper, we propose a new packet classification algorithm by applying a binary search for the codewords of the AQT to overcome the issue of the AQT. Throughout simulation, it is shown that the proposed algorithm provides a better performance than the AQT in the number of rule comparisons with each input packet.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.49 no.2
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• pp.1-6
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• 2012

In recent years global climate change of hurricanes and torrential rains are going to significantly, that increase damages to property and human life. The disasters have been several claimed in every field. In future, climate changes blowing are keen to strike released to the world like in several movies. Reducing the damage of long-term weather phenomena are emerging with predicting changes in weather. In this study, it is shown how to predict the red tide phenomenon with multiple linear regression analysis and artificial neural network techniques. The red tide phenomenon causing risk could be reduced by filtering sensor data which are transmitted and forecasted in real time. It could be ubiquitous driven custom marine information service system, and forecasting techniques to use throughout the meteorological disasters to minimize damage.

• Speech Sciences
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• v.10 no.4
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• pp.117-124
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• 2003

Speaker recognition is the technology that confirms the identification of speaker by using the characteristic of speech. Such technique is classified into speaker identification and speaker verification: The first method discriminates the speaker from the preregistered group and recognize the word, the second verifies the speaker who claims the identification. This method that extracts the information of speaker from the speech and confirms the individual identification becomes one of the most efficient technology as the service via telephone network is popularized. Some problems, however, must be solved for the real application as follows; The first thing is concerning that the safe method is necessary to reject the imposter because the recognition is not performed for the only preregistered customer. The second thing is about the fact that the characteristic of speech is changed as time goes by, So this fact causes the severe degradation of recognition rate and the inconvenience of users as the number of times to utter the text increases. The last thing is relating to the fact that the common characteristic among speakers causes the wrong recognition result. The silence parts being included the center of speech cause that identification rate is decreased. In this paper, to make improvement, We proposed identification rate can be improved by removing silence part before processing identification algorithm. The methods detecting speech area are zero crossing rate, energy of signal detect end point and starting point of the speech and process DTW algorithm by using two methods in this paper. As a result, the proposed method is obtained about 3% of improved recognition rate compare with the conventional methods.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2016.05a
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• pp.493-495
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• 2016

In this paper, we propose an alternative method of collecting image data and changing nodes in wireless sensor networks based sensing disaster systems configured with zigbee using quad copter. It is difficult to observe a wide area caused by existing fixed video cameras in the wireless sensor network system using a conventional image-based. Also the nodes don't have provide to alternate methodology in situations when missing due to a disaster or destruction. In this paper, to use wearing the IP camera and the communication node to the quad copter, it provides a method to take advantage of as improving an alternative node of the reliability of the sensor node. The results show to improve the reliability of the sensor nodes and real-time status information through a video quad Copt than conventional systems.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2017.05a
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• pp.77-80
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• 2017

One of the fundamental limits of Bluetooth Low Energy(BLE) is that the data transmission is available via singlehop connection. In this research, we suggested the stable multihop transmission method to overcome this limitation. In multihop connection situation, multiple singlehop connection should be made and disconnected dynamically. Therefore, we stored the data within the GATT layer and tried to send it dynamically. We divided whole process as 4 states, and let each nodes transfers around each states to make data connection safely. Also, we set the transfer policy between each states during the transmission to make a robust system. From the experiment in real-time environment, we proved that our method showed high rate of packet delivery in a multihop network, which consists of more than 3 nodes.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.29 no.4C
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• pp.494-504
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• 2004

The researches about gaze detection have been much developed with many applications. Most previous researches only rely on image processing algorithm, so they take much processing time and have many constraints. In our work, we implement it with a computer vision system setting a IR-LED based single camera. To detect the gaze position, we locate facial features, which is effectively performed with IR-LED based camera and SVM(Support Vector Machine). When a user gazes at a position of monitor, we can compute the 3D positions of those features based on 3D rotation and translation estimation and affine transform. Finally, the gaze position by the facial movements is computed from the normal vector of the plane determined by those computed 3D positions of features. In addition, we use a trained neural network to detect the gaze position by eye's movement. As experimental results, we can obtain the facial and eye gaze position on a monitor and the gaze position accuracy between the computed positions and the real ones is about 4.2 cm of RMS error.