• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2014.06a
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• pp.254-257
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• 2014

Recently, various applications using real-time face detection have been developed as face recognition technology and hardware grows. While network service is developing and video instruments costs lower, it is needed that smart surveillance camera and service using network camera based on IP and face detection technology. However, videos should be compressed for reducing network bandwidth and storage capacity in surveillance system. As it requires high-level improvement of system performance when all the compressed frames are processed in a face detection program, fast face detection method is needed. In this paper, not only a fast way of algorithm using Haar like features and adaboost learning and motion information but also an application on broadcast system is suggested.

• The Korean Journal of Cytopathology
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• v.9 no.2
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• pp.213-219
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• 1998

Glycogen-rich clear ceil carcinoma of the breast is an unusual variant of carcinoma with a recorded incidence of $1.4{\sim}3%$ of breast carcinomas. The cytologic characteristics have not been well described. We report two cases of glycogen-rich clear cell carcinoma with corresponding fine needle aspiration(FNA) cytologic findings and compare them to infiltrating ductal carcinoma and other clear ceil malignancies with a review of literature. One was a 62-year-old woman exhibiting a palpable mass of the right breast. The smears showed atypical tight cell clusters and individually scattered single cells containing leanly or clear abundant cytoplasm with well defined cytoplasmic margins. Mild to moderate nuclear pleomorphism and a prominent nucleolus were present. The other was a 42-year-old woman who was admitted with a right breast mass. The smears showed moderately cellular, tightly cohesive tumor cells. The cytoplasmic outline was generally well demarcated. The tumor cells Contained foamy to clear abundant cytoplasm with large and small vacuoles. The nuclear pleomorphism was marked. Both tumors resected by modified radical mastectomy, were diagnosed as glycogen-rich clear cell carcinoma. Histologically, the clear cell nature of tumor cells were not characteristic enough to predict this type of the tumor. Some cytologic features can be distinguished other clear cell breast cancer from glycogen-rich carcinoma. Recognition of these unusual patterns in a breast FNAC should raise the suspicion of a clear cell carcinoma including glycogen-rich subtype. Cytological localization of glycogen using PAS and D-PAS staining may permit the correct Identification and differential diagnosis of this tumor.

• Knowledge Management Research
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• v.21 no.1
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• pp.197-210
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• 2020

The smart speaker includes an AI assistant function in the existing portable speaker, which enables a person to give various commands using a voice and provides various offline services associated with control of a connected device. The speed of domestic distribution is also increasing, and the functions and linked services available through smart speakers are expanding to shopping and food orders. Through text mining-based customer review analysis, there have been many proposals for identifying the impact on customer attitudes, sentiment analysis, and product evaluation of product functions and attributes. Emotional investigation has been performed by extracting words corresponding to characteristics or features from product reviews and analyzing the impact on assessment. After obtaining the topic from the review, the effect on the evaluation was analyzed. And the market competition of similar products was visualized. Also, a study was conducted to analyze the reviews of smart speaker users through text mining and to identify the main attributes, emotional sensitivity analysis, and the effects of artificial intelligence attributes on product satisfaction. The purpose of this study is to collect blog posts about the user's experiences of smart speakers released in Korea and to analyze the attitudes of customers according to their attributes. Through this, customers' attitudes can be identified and visualized by each smart speaker product, and the positioning map of the product was derived based on customer recognition of smart speaker products by collecting the information identified by each property.

• Journal of Biosystems Engineering
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• v.26 no.2
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• pp.147-154
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• 2001

In Korea and Japan, dried oak mushrooms are classified into 12 to 16 different categories based on its external visual quality. And grading used to be done manually by the human expert and is limited to the randomly sampled oak mushrooms. Visual features of dried oak mushrooms dominate its quality and are distributed over both sides of the gill and the cap. The 2nd prototype computer vision based automatic grading and sorting system for dried oak mushrooms was developed based on the 1st prototype. Sorting function was improved and overall system for grading was simplified to one stage grading instead of two stage grading by inspecting both front and back sides of mushrooms. Neuro-net based side(gill or cap) recognition algorithm of the fed mushroom was adopted. Grading was performed with both images of gill and cap using neural network. A real time simultaneous discharge algorithm, which is good for objects randomly fed individually and for multi-objects located along a series of discharge buckets, was developed and implemented to the controller and the performance was verified. Two hundreds samples chosen from 10 samples per 20 grade categories were used to verify the performance of each unit such as feeding, reversing, grading, and discharging unites. Test results showed that success rates of one-line feeding, reversing, grading, and discharging functions were 93%, 95%, 94%, and 99% respectively. The developed prototype revealed successful performance such as the approximate sorting capability of 3,600 mushrooms/hr per each line i.e. average 1sec/mushroom. Considering processing time of approximate 0.2 sec for grading, it was desired to reduce time to reverse a mushroom to acquire the reversed surface image.

• Parasites, Hosts and Diseases
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• v.51 no.4
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• pp.401-412
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• 2013

Because of an increased number of Acanthamoeba keratitis (AK) along with associated disease burdens, medical professionals have become more aware of this pathogen in recent years. In this study, by analyzing both the nuclear 18S small subunit ribosomal RNA (18S rRNA) and mitochondrial 16S rRNA gene loci, 27 clinical Acanthamoeba strains that caused AK in Japan were classified into 3 genotypes, T3 (3 strains), T4 (23 strains), and T5 (one strain). Most haplotypes were identical to the reference haplotypes reported from all over the world, and thus no specificity of the haplotype distribution in Japan was found. The T4 sub-genotype analysis using the 16S rRNA gene locus also revealed a clear subconformation within the T4 cluster, and lead to the recognition of a new sub-genotype T4i, in addition to the previously reported sub-genotypes T4a-T4h. Furthermore, 9 out of 23 strains in the T4 genotype were identified to a specific haplotype (AF479533), which seems to be a causal haplotype of AK. While heterozygous nuclear haplotypes were observed from 2 strains, the mitochondrial haplotypes were homozygous as T4 genotype in the both strains, and suggested a possibility of nuclear hybridization (mating reproduction) between different strains in Acanthamoeba. The nuclear 18S rRNA gene and mitochondrial 16S rRNA gene loci of Acanthamoeba spp. possess different unique characteristics usable for the genotyping analyses, and those specific features could contribute to the establishment of molecular taxonomy for the species complex of Acanthamoeba.

• 한국정보교육학회:학술대회논문집
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• 2010.08a
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• pp.199-207
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• 2010

Making use of mobile in the education field with international providing of iPod, iPhone and the rapid growth of information oriented society suggest lots of ideas in the aspect of method of education. Using the various technology of iPod and iPhone leads to change of teaching method because iPod and iPhone supports lots of skills of teaching which is student-centered is gradually supplying to students. Furthermore, Not only the development of various mobile contents can be materialized in iPod circumstance is processing in information-communication field of Korea, but also a recognition of people about iPod and iPhone is changing positively. Along this change, it expects to using of iPod and iPhone for teaching methods in school will affect to the education effectively and promote the quality of education. So, this study was focused on the development application for using iPod and iPhone in each subjects of Society and Science according to this features of changes with expecting the educational effect accompanied by using iPod and iPhone and searched the previous examples of using mobile application.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.11 no.9
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• pp.3510-3516
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• 2010

In this paper to make young children to learn habits of the animals, crying, features, and English and Korean language, The system was developed to target the zoo various animals exist. If young child places a doll on the front of interesting animal, then young child can learn to look through the display connected to the model. The zoo is reducing the current appearance of the zoo, sensors that can recognize animals are attached to each cage. Attached to each sensor has a unique ID, If this approach recognizes a doll baby and will transmit a unique ID to the handler. Transmitted ID search the matched value sent from the database to retrieve the content and then the content is to be output through the output device. Also if the doll near the animal's room, young children find out animal sound and basic learning by multimedia effects. At the same time Korean, English, Mathematics are learned.

• The Journal of the Acoustical Society of Korea
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• v.6 no.3
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• pp.60-67
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• 1987

In this paper, a phoneme classification method for Korean speech recognition has been proposed and its performance has been studied. The phoneme classification has been done based on the phonemic features extracted by the prewindowed recursive least-square (PRLS) algorithm that is a kind of adaptive filter algorithms. Applying the PRLS algorithm to input speech signal, precise detection of phoneme boundaries has been made, Reference patterns of Korean phonemes have been generated by the ordinery vector quantization (VQ) of feature vectors obtained manualy from prototype regions of each phoneme. In order to obtain the performance of the proposed phoneme classification method, the method has been tested using spoken names of seven Korean cities which have eleven different consonants and eight different vowels. In the speaker-dependent phoneme classification, the accuracy is about $85\%$ considering simple phonemic rules of Korean language, while the accuracy of the speaker-independent case is far less than that of the speaker-dependent case.

• KIPS Transactions on Software and Data Engineering
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• v.7 no.3
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• pp.91-98
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• 2018

Automatic detection of pig wasting diseases is an important issue in the management of group-housed pigs. In particular, porcine respiratory diseases are one of the main causes of mortality among pigs and loss of productivity in intensive pig farming. In this paper, we propose a noise-robust system for the early detection and recognition of pig wasting diseases using sound data. In this method, first we convert one-dimensional sound signals to two-dimensional gray-level images by normalization, and extract texture images by means of dominant neighborhood structure technique. Lastly, the texture features are then used as inputs of convolutional neural networks as an early anomaly detector and a respiratory disease classifier. Our experimental results show that this new method can be used to detect pig wasting diseases both economically (low-cost sound sensor) and accurately (over 96% accuracy) even under noise-environmental conditions, either as a standalone solution or to complement known methods to obtain a more accurate solution.

• Journal of Intelligence and Information Systems
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• v.10 no.2
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• pp.65-77
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• 2004

This paper presents a priori and the local font classification method. The font classification uses ascenders, descenders, and serifs extracted from a word image. The gradient features of those sub-images are extracted, and used as an input to a neural network classifier to produce font classification results. The font classification determines 2 font styles (upright or slant), 3 font groups (serif sans-serif or typewriter), and 7-font names (Postscript fonts such as Avant Garde, Helvetica, Bookman, New Century Schoolbook, Palatine, Times, and Courier). The proposed a priori and local font classification method allows an OCR system consisting of various font-specific character segmentation tools and various mono-font character recognizers. Experiments have shown font classification accuracies reach high performance levels of about 95.4 percent even with severely touching characters. The technique developed for tile selected 7 fonts in this paper can be applied to any other fonts.