Lee, Hyong-Euk;Kim, Yong-Hwi;Lee, Tae-Youb;Park, Kwang-Hyun;Kim, Yong-Soo;Cho, Joon-Myun;Bien, Z. Zenn
Journal of the Korean Institute of Intelligent Systems
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v.17
no.2
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pp.244-251
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2007
Intention reading technique is essential to provide personalized services toward more convenient and human-friendly services in complex ubiquitous environment such as a smart home. If a system has knowledge about an user's intention of his/her behavioral pattern, the system can provide mote qualified and satisfactory services automatically in advance to the user's explicit command. In this sense, learning capability is considered as a key function for the intention reading technique in view of knowledge discovery. In this paper, ore introduce a personalized media control method for a possible application iii a smart home. Note that data pattern such as human behavior contains lots of inconsistent data due to limitation of feature extraction and insufficiently available features, where separable data groups are intermingled with inseparable data groups. To deal with such a data pattern, we introduce an effective engineering approach with the combination of fuzzy logic and probabilistic reasoning. The proposed learning system, which is based on IFCS (Iterative Fuzzy Clustering with Supervision) algorithm, extract probabilistic fuzzy rules effectively from the given numerical training data pattern. Furthermore, an extended architectural design methodology of the learning system incorporating with the IFCS algorithm are introduced. Finally, experimental results of the media contents recommendation system are given to show the effectiveness of the proposed system.
This study has carried out scanning tests in order to figure out the features of scanning search by sex of space users, with the result of which the validity of data has been estimated. In this research, the scanning patterns were set up for verifying the typology of scanning paths and then the reason for determining scanning paths and the validity of estimation method were reviewed. Since the observation features depends on sex, the analysis of visual activities for acquiring any information in a space will reveal the intention and purpose of space users. The findings by analyzing the features of scanning pattern by sex which were found at the determination of scanning patterns can be defined as the followings. First, for estimating the process of space-information search, the movement distance at each point of continuative-observation data from the angle of eye-movement has been extracted, on the ground of which the fixation and movement of eye have been defined for the establishment of scanning-cut characteristics. Second, the scanning times were estimated for the extraction of effective observation data that would be used for comparative analysis, which showed that men had more data (3,398.2/64.4%) than women (2,998.2/55.6%). This enables the acknowledgment that the scanning cut of men was relatively less, which indicates that men will acquire more information on space than women in the process of observing any space. Third, men's scanning times (58.0 times/2.02 seconds) were less than those of women (71.9 times/1.39 seconds) while the scanning time of the former was longer than that of the latter, which shows the feature that it takes longer for men than women in scanning while the scanning times of the former is less than those of the latter. Fourth, the observation features can be determined that the combination of this result with the predominance character by sex for a general viewpoint to be employed indicates that while men employ mixed-scanning for observation activities to acquire space-information spending for longer time, women, by concentrated-scanning, focus on a single point for shorter time or stay at one location for a considerably long time for space-information acquirement.
Journal of the Institute of Electronics Engineers of Korea SD
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v.42
no.12
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pp.45-52
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2005
A systolic array formed by interconnecting a set of identical data-processing cells in a uniform manner is a combination of an algorithm and a circuit that implements it, and is closely related conceptually to arithmetic pipeline. High-performance computation on a large array of cells has been an important feature of systolic array. To achieve even higher degree of concurrency, it is desirable to make cells of systolic array themselves systolic array as well. The structure of systolic array with its cells consisting of another systolic array is to be called super-systolic array. This paper proposes a scalable bit-level super-systolic amy which can be adopted in the VLSI design including regular interconnection and functional primitives that are typical for a systolic architecture. This architecture is focused on highly regular computational structures that avoids the need for a large number of global interconnection required in general VLSI implementation. A bit-level super-systolic FIR filter is selected as an example of bit-level super-systolic array. The derived bit-level super-systolic FIR filter has been modeled and simulated in RT level using VHDL, then synthesized using Synopsys Design Compiler based on Hynix $0.35{\mu}m$ cell library. Compared conventional word-level systolic array, the newly proposed bit-level super-systolic arrays are efficient when it comes to area and throughput.
Proceedings of the Korean Society of Near Infrared Spectroscopy Conference
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2001.06a
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pp.1182-1182
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2001
In this study, the newly constructed optical measurement system, which was mainly composed of a parametric tunable laser and a near infrared photoelectric multiplier, was introduced to clarify the optical characteristics of wood as discontinuous body with anisotropic cellular structure from the viewpoint of the time-of-flight near infrared spectroscopy (TOF-NIRS). The combined effects of the cellular structure of wood sample, the wavelength of the laser beam λ, and the detection position of transmitted light on the time resolved profiles were investigated in detail. The variation of the attenuance of peak maxima At, the time delay of peak maxima Δt and the variation of full width at half maximum Δw were strongly dependent on the feature of cellular structure of a sample and the wavelength of the laser beam. The substantial optical path length became about 30 to 35 times as long as sample thickness except the absorption band of water. Δt ${\times}$ Δw representing the light scattering condition increased exponentially with the sample thickness or the distance between the irradiation point and the end of sample. Around the λ=900-950 nm, there may be considerable light scattering in the lumen of tracheid, which is multiple specular reflection and easy to propagate along the length of wood fiber. Such tendency was remarkable for soft wood with the aggregate of thin layers of cell walls. When we apply TOF-NIRS to the cellular structural materials like wood, it is very important to give attention to the difference in the light scattering within cell wall and the multiple specular-like reflections between cell walls. We tried to express the characteristics of the time resolved profile on the basis of the optical parameters for light propagation determined by the previous studies, which were absorption coefficient K and scattering coefficient S from Kubelka-Munk theory and n from nth power cosine model of radiant intensity. The wavelength dependency of the product of K/S and n, which expressed the light-absorbing and -scattering condition and the degree of anisotropy, respectively, was similar to that of the time delay of peak maxima Δt. The variation of the time resolved profile is governed by the combination of these parameters. So, we can easily find the set of parameters for light propagation synthetically from Δt.
Handwritten character recognition is classified into on-line handwritten character recognition and off-line handwritten character recognition. On-line handwritten character recognition has made a remarkable outcome compared to off-line hacdwritten character recognition. This method can acquire the dynamic written information such as the writing order and the position of a stroke by means of pen-based electronic input device such as a tablet board. On the contrary, Any dynamic information can not be acquired in off-line handwritten character recognition since there are extreme overlapping between consonants and vowels, and heavily noisy images between strokes, which change the recognition performance with the result of the preprocessing. This paper proposes a method that effectively extracts the stroke including dynamic information of characters for off-line Korean handwritten character recognition. First of all, this method makes improvement and binarization of input handwritten character image as preprocessing procedure using watershed algorithm. The next procedure is extraction of skeleton by using the transformed Lu and Wang's thinning: algorithm, and segment pixel array is extracted by abstracting the feature point of the characters. Then, the vectorization is executed with a maximum permission error method. In the case that a few strokes are bound in a segment, a segment pixel array is divided with two or more segment vectors. In order to reconstruct the extracted segment vector with a complete stroke, the directional component of the vector is mortified by using right-hand writing coordinate system. With combination of segment vectors which are adjacent and can be combined, the reconstruction of complete stroke is made out which is suitable for character recognition. As experimentation, it is verified that the proposed method is suitable for handwritten Korean character recognition.
Latent topic models are statistical models which automatically captures salient patterns or correlation among features underlying a data collection in a probabilistic way. They are gaining an increased popularity as an effective tool in the application of automatic semantic feature extraction from text corpus, multimedia data analysis including image data, and bioinformatics. Among the important issues for the effectiveness in the application of latent topic models to the massive data set is the efficient learning of the model. The paper proposes an accelerated learning technique for PLSA model, one of the popular latent topic models, by an incremental EM algorithm instead of conventional EM algorithm. The incremental EM algorithm can be characterized by the employment of a series of partial E-steps that are performed on the corresponding subsets of the entire data collection, unlike in the conventional EM algorithm where one batch E-step is done for the whole data set. By the replacement of a single batch E-M step with a series of partial E-steps and M-steps, the inference result for the previous data subset can be directly reflected to the next inference process, which can enhance the learning speed for the entire data set. The algorithm is advantageous also in that it is guaranteed to converge to a local maximum solution and can be easily implemented just with slight modification of the existing algorithm based on the conventional EM. We present the basic application of the incremental EM algorithm to the learning of PLSA and empirically evaluate the acceleration performance with several possible data partitioning methods for the practical application. The experimental results on a real-world news data set show that the proposed approach can accomplish a meaningful enhancement of the convergence rate in the learning of latent topic model. Additionally, we present an interesting result which supports a possible synergistic effect of the combination of incremental EM algorithm with parallel computing.
Shape features in a content-based image retrieval (CBIR) system are divided into two classes: contour-based and region-based. Contour-based shape features are simple but they are not as efficient as region-based shape features. Most systems using the region-based shape feature have to extract the region firs t. The prior works on region-based systems still have shortcomings. They are complex to implement, particularly with respect to region extraction, and do not sufficiently use the spatial relationship between regions in the distance model In this paper, a region extraction method that is the combination of an edge-based method and a region growing method is proposed to accurately extract regions inside an object. Edges inside an object are accurately detected based on the Canny edge detector and the Hough transform. And the modified Integrated Region Matching (IRM) scheme which includes the adjacency relationship of regions is also proposed. It is used to compute the distance between images for the similarity search using shape features. The experimental results show the effectiveness of our region extraction method as well as the modified IRM. In comparison with other works, it is shown that the new region extraction method outperforms others.
Headache is a symptom with varied etiologies and extraordinarily frequent. Headaches can be a symptom of another diseases, such as meningitis, subarachnoid hemorrhage or brain tumor, may represent the disease entity itself as the case in migraine. The international Headache Society criteria were the first to distinguish between primary and secondary headache disorders. When evaluating a patient who presents with headache, the physician abviously needs to identify or exclude the myriad conditions that can cause secondary headache and initial diagnostic workup should be considered. If patient meets the criteria for a primary headache disorder, treatment commonly initiated without additional neurodiagnostic tests. The headache type, its associated feature, and the duration and the intensity of the pain attack all can influence the choice of acute therapy in migraine. Pharmacologically, such as NSAIDs, combination analgesics, vasoactive antimigraineous drugs, neuroleptics, antidepressants, or corticosteroids. Other approches to managing headache include a headache diary to identify triggers, biofeedback, relaxation technique and behavioral modification. Daily preventive medication should be considered by his attack frequency and intensity, and maintained for 4 to 6 months. Tension-type headaches are distinguished between episodic and chronic tension-type headache, but physician must make sure that patient is not drug-overuse or independent during symptomatic abortive therapy or preventive medication. The most difficult headache patients to treat are those with chronic daily headache. They often have physical dependency, low frustration tolerance, sleep problems, and depression. So discontinuation of overused medication is crucial. New developments in migraine therapy are broadening the scope of abortive and prophylactic treatment choices available to the physician. The enhanced ease of the use of sumatriptan and DHE will likely increase patient compliance and satisfaction.
Lim, Min Su;Kim, Seong-Joong;Kang, Ha Sung;Park, Ho Bum;Nam, Seung Eun;Park, Ho Sik;Lee, Pyung Soo;Park, You In
Membrane Journal
/
v.26
no.1
/
pp.76-85
/
2016
Fabrication of polysulfone (PSf) hollow fiber membranes was investigated for the separation of $N_2/NF_3$ gas mixtures, which are emitted from the display and the semiconductor industries. A combination of the non-solvent induced phase separation (NIPS) and the vapor-induced phase separation (VIPS) technique was applied to develop high flux hollow fiber membranes. Thin polymer layers were further coated onto the surface of the hollow fiber membranes by using polydimethylsiloxiane (PDMS) or Teflon AF1600(R), which contributes to improve the $N_2/NF_3$ selectivity. The $N_2/NF_3$ separation performances of our PSf hollow fiber membranes were determined by the intrinsic properties of coating materials. Especially, the PSf hollow fiber membrane coated with Teflon AF 1600(R) exhibited a higher $N_2/NF_3$ selectivity (> 14) with a slightly lower $N_2$ permeance (4.5 GPU), as compared to the commercial PSf counterparts. This feature provides a good potential as a membrane structure to separate $N_2/NF_3$.
Journal of The Korean Association For Science Education
/
v.32
no.5
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pp.1007-1026
/
2012
The purpose of this study was to develop analytic framework for dialogic argumentation to show the context and flow visualizing interactions of argumentation, to be able to present quality of argumentation specifically. For this, we formulated a method of the argumentation diagram using feature of diagram simple and structurally visualizing interrelation between argument components, and then quantified quality of argumentation to argument level score on this basis. We have developed the learning material for argumentation about a vertical circular motion and used the obtained translations from applying it in developing the framework. We chose argument statements among full transcript and then coded as Toulmin's argument components, and these codes was effectively arranged and linked to show argumentation diagram. Results by argumentation diagram could be useful understanding of interactive argumentation context and the flow and present frequency, the combination of argument elements, rough qualitative level of argumentation. To quantify argumentation quality, we gave different scores to different link lines reflecting indication of argumentation quality like that diversity of argument component, justification, presence or absence of rebuttals. The process of identification of argument level is very simple, qualitative level of argumentation represented as concrete score could present various and concrete argument level. Developed analytic framework might contribute to argumentation research field, because it can present effectively dialogic argumentation result. Also, various analysis cases might guide designing an effective argumentation practice and circular motion learning.
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