• Speech Sciences
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• v.10 no.1
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• pp.27-39
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• 2003

This study attempts to verify the reliability of automatically generated segment labels as compared to those obtained by conventional labelling by hand. First of all, an autolabeller is constructed using the standard HMM speech recognition technique. For evaluation, we compare the automatically generated labels with manually annotated labels for the same speech data. The comparison is performed by calculating the temporal difference between an autolabel boundary and its corresponding hand label boundary. When the mismatched duration between two labels falls within 10 msec, we consider the autolabel as correct. The results suggest that overall 78% of autolabels are correctly obtained. It is found that the boundary of obstruents is better aligned than that of sonorants and vowels. In case of stop sound classes, strong stops in manner-of-articulation wise and velar stops in place-of-articulation wise show better performance in boundary alignment. The result suggests that more phone-specific consideration is necessary to improve autosegmentation performance.

• Journal of Korean Neurosurgical Society
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• v.29 no.4
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• pp.485-490
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• 2000

Objective : To study the expression of apoptosis and bcl-2 in the astrocytic tumors. Patients and Methods : A total of thirty-eight astrocytomas(9 cases in low grade astrocytoma, 12 cases in anaplastic astrocytoma and 17 cases in glioblastoma) are included in this study. Immunohistochemical stain for bcl-2 using monoclonal antibody, in situ end labelling technique for apoptosis were used. Results : The malignant group(anaplastic astrocytoma and glioblastoma) showed significantly higher apoptosis positive index(PI) compared to the benign group(low grade astrocytoma)(1.35 vs 0.14). However apoptosis PI and bcl-2 PI were not significantly different among three groups. Correlation between apoptosis PI and bcl-2 PI was not statistically significant(p=0.58). Conclusion : This result suggest that apoptosis PI and bcl-2 PI are not related the degree of malignancy in astrocytic neoplasm, but apoptosis PI in malignant group was higher possibly due to greater DNA damage.

• Biomolecules & Therapeutics
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• v.1 no.1
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• pp.58-64
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• 1993

DNA addicts induced by putative chemical related to carcinogenesis were detected and determined by $^{32}$P-Postlabelling assay after exposure of 4 compounds comprising two auto dyes (amaranth, new coccine) and two flavonoid compounds (rutin, quercetin) to ICR mouse. DNA was isolated from mouse liver and digested enzymatically to deoxyribonucleoside 3'-monophosphate. The postincubation of DNA digests with nuclease Pl before $^{32}$P-labelling enhanced the technique's sensitivity. Nuclease Pl cleaves deoxyribonucleoside 3'-mono-phosphates of normal nucleotides to deoxyrihonucleosides which do not serve as substrates for polynucleotide kinase, while most of addicts were found to be totally or partially resistant to the 3'-dephosphorylating action of nuclease Pl. The adducted deoxyribonucleoside 3'-monophosphate was converted to 5'-$^{32}$P-labelled deoxynucleoside 3',5'-bisphosphate by T4 polynucleotide kinase. The nucleotides were separated by anion-exchange thin layer chromatography(TLC) on polyethyleneimine cellulose by 4-dimensional or 2-dimensional TLC then detected by autoradiography. The results show that DNA addicts were detected in liver DNA of ICR mouse after administration of amaranth and quercetin by 2-dimensional and/or 4-dimensional TLC.

• The Korean Journal of Nuclear Medicine
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• v.11 no.1
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• pp.9-15
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• 1977

Radioiodine labelled human follicle stimulating hormone has been prepared using chloramine-T, with the approximate labelling yield of 65%. The labelled product is purified by means of a starch gel electrophoresis, and a Sephadex gel filtration, and the separation efficiencies are assessed for the effective use in radioimmunoassay. The results indicate that the gel filtration is efficient in view of the separation time, simplicity and bindability of the labelled hormone to the antibody. In determining the ratio of the free to the antibody hound labelled hormone, a double antibody technique is applied in comparison with a chromatoelectrophoresis. The ratio could be obtained only in the case of applying the double antibody technique.

• International Journal of Computer Science & Network Security
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• v.22 no.3
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• pp.29-36
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• 2022

In deep learning classification tasks, most models frequently assume that all labels are available for the training datasets. As such strategies to learn new concepts from unlabeled datasets are scarce. In fingerprint classification tasks, most of the fingerprint datasets are labelled using the subject/individual and fingerprint datasets labelled with finger type classes are scarce. In this paper, authors have developed approaches of classifying fingerprint images using the majorly known fingerprint classes. Our study provides a flexible method to learn new classes of fingerprints. Our classifier model combines both the clustering technique and use of deep learning to cluster and hence label the fingerprint images into appropriate classes. The K means clustering strategy explores the label uncertainty and high-density regions from unlabeled data to be clustered. Using similarity index, five clusters are created. Deep learning is then used to train a model using a publicly known fingerprint dataset with known finger class types. A prediction technique is then employed to predict the classes of the clusters from the trained model. Our proposed model is better and has less computational costs in learning new classes and hence significantly saving on labelling costs of fingerprint images.

• Journal of the Korea Society of Computer and Information
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• v.18 no.4
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• pp.13-18
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• 2013

Panorama picturing is an elongated photographing technique that connects images with rotating and moving multiple images horizontally that are partly overlapped. However, for hand-operated photographs, it is difficult to adjust overlapped parts because of tilted angles. There has been a study comparing adjacent pictures using labeling technique but it was time-consuming and had angle dissonant cases in nature. In this paper, we propose a less time-consuming paranoiac scene reconstruction method. Our method is also based on labeling-and-comparing technique but uses only 1/3 of it. Then, if there exists angle dissonance, it tries to find characteristic points by SURF algorithm and adjusts them with homography. The efficacy of this method is experimentally verified by experiments using various images

• Korean journal of applied entomology
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• v.20 no.4 s.49
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• pp.207-211
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• 1981

It has been documented that the resistance to planthoppers is attributed to the feeding preference of the insects. This might be related to difference in the amount of feeding plant sap between resistant and susceptible hosts. In this aspect, this study was conducted to verify it and to develop an effective screening method for resistance to planthoppers by tracer technique. An effective P-32 labelling of rice seedlings at $2\~3$ leaf stage was dipping the roots in concentration of $0.1{\mu}Ci/ml$ solution for 48 hours. Radioactivity was significantly higher in planthopers fed on susceptible variety for 48 hours as compared to those fed on resistant variety. Radioactivity of adults was higher than that of nymphs and also higher in female than male. The results were highly correlated to that indicated by the feeding preference of the insects and therefore, considered to be valid for a screening technique.

• Journal of Fashion Business
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• v.16 no.4
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• pp.29-45
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• 2012

The purpose of this study is for providing not only the latest design technique trend for zero waste fashion, but information about creative fashion design education through eco-fashion industry trend in globally and domestic which is focusing on eco-fashion labelling. The research were processed with literature related eco, sustainable, green fashion books, former articles, newspapers, and web sites. The results as follows; The certification about eco-fashion product is moving to 'Life Cycle Assessment' from focused on primary process like material, finishing, dyeing. Especially simplicity of process means reducing the wastes. And fabric wastage for adult outwear was estimated 15% percent of total fabric used in general design studios. Three cases for Zero waste fashion were as follows; First, Jigsaw puzzle by Timo Rissane and Mark Liu were different zero waste methods, but the result was same. Rissene's method was based on traditional cutting like 'cut and sew' but traditional cutting can lead to design that have an abundance of fabric and drape. Jigsaw of Rissene was approached with description a pattern-cutting technique in which all piece interlock with each other generating no waste from design production. Another Jigsaw by Liu was related with innovative textile design. DTP makes the possibilities for zero waste garment production almost endless. The dress intricately cut from 10 pieces, wastes none of the fabric required to make it. Second, Subtraction Cutting by Julian Roberts provides unexpected fluid, organic forms and zero waste fabric. Utilizing Roberts plug(tunnel) technique enables any part of the garment that is removed for fit or aesthetics to be reincorporated into the design of garment. Third was 'Bio Couture' by Suzanne Lee. She has created garments from cellulose bacteria which grow in a bathtub using only green methods addressing in such as way ecological issues and exploring the future of fashion design in conjunction with technology.

• International Journal of Computer Science & Network Security
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• v.23 no.12
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• pp.151-160
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• 2023

Breast cancer is the most dangerous and deadly form of cancer. Initial detection of breast cancer can significantly improve treatment effectiveness. The second most common cancer among Indian women in rural areas. Early detection of symptoms and signs is the most important technique to effectively treat breast cancer, as it enhances the odds of receiving an earlier, more specialist care. As a result, it has the possible to significantly improve survival odds by delaying or entirely eliminating cancer. Mammography is a high-resolution radiography technique that is an important factor in avoiding and diagnosing cancer at an early stage. Automatic segmentation of the breast part using Mammography pictures can help reduce the area available for cancer search while also saving time and effort compared to manual segmentation. Autoencoder-like convolutional and deconvolutional neural networks (CN-DCNN) were utilised in previous studies to automatically segment the breast area in Mammography pictures. We present Automatic SegmenAN, a unique end-to-end adversarial neural network for the job of medical image segmentation, in this paper. Because image segmentation necessitates extensive, pixel-level labelling, a standard GAN's discriminator's single scalar real/fake output may be inefficient in providing steady and appropriate gradient feedback to the networks. Instead of utilising a fully convolutional neural network as the segmentor, we suggested a new adversarial critic network with a multi-scale L1 loss function to force the critic and segmentor to learn both global and local attributes that collect long- and short-range spatial relations among pixels. We demonstrate that an Automatic SegmenAN perspective is more up to date and reliable for segmentation tasks than the state-of-the-art U-net segmentation technique.

• Proceedings of the Korean Society for Agricultural Machinery Conference
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• 2017.04a
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• pp.42-42
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• 2017

Prediction of rice yield during a growing season would be very helpful to magnify rice yield as it also allows better farm practices to maximize yield with greater profit and lesser costs. UAV imagery based automatic detection of rice can be a relevant solution for early prediction of yield. So, we propose an image processing technique to predict rice yield using low altitude UAV images. We proposed $L^*a^*b^*$ color space based image segmentation algorithm. All images were captured using UAV mounted RGB camera. The proposed algorithm was developed to find out rice grain area from the image background. We took RGB image and applied filter to remove noise and converted RGB image to $L^*a^*b^*$ color space. All color information contain in both $a^*$ and $b^*$ layers and by using k-mean clustering classification of these colors were executed. Variation between two colors can be measured and labelling of pixels was completed by cluster index. Image was finally segmented using color. The proposed method showed that rice grain could be segmented and we can recognize rice grains from the UAV images. We can analyze grain areas and by estimating area and volume we could predict rice yield.