• Journal of Information Processing Systems
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• v.19 no.5
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• pp.614-630
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• 2023

Dead trees significantly impact forest production and the ecological environment and pose constraints to the sustainable development of forests. A lightweight YOLOv4 dead tree detection algorithm based on unmanned aerial vehicle images is proposed to address current limitations in dead tree detection that rely mainly on inefficient, unsafe and easy-to-miss manual inspections. An improved logarithmic transformation method was developed in data pre-processing to display tree features in the shadows. For the model structure, the original CSPDarkNet-53 backbone feature extraction network was replaced by MobileNetV3. Some of the standard convolutional blocks in the original extraction network were replaced by depthwise separable convolution blocks. The new ReLU6 activation function replaced the original LeakyReLU activation function to make the network more robust for low-precision computations. The K-means++ clustering method was also integrated to generate anchor boxes that are more suitable for the dataset. The experimental results show that the improved algorithm achieved an accuracy of 97.33%, higher than other methods. The detection speed of the proposed approach is higher than that of YOLOv4, improving the efficiency and accuracy of the detection process.

• Natural Product Sciences
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• v.29 no.2
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• pp.83-90
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• 2023

To our knowledge, this is the first study aiming to optimize the extraction conditions of total phenolic compounds (TPC) and total flavonoids contents (TFC) from Argania spinosa leaves using Response Surface Methodology (RSM) with a Box-Behnken design (BBD). The optimal conditions obtained were 5% (w/v) solvent-to-solid ratio, 72.33% ethanol concentration, and 10h ours as an extraction time, which resulted in an extract with maximum TPC (131.63 mg GAE/g dw) and TFC (10.66 mg QE/g dw). Under the optimal extraction conditions, the antioxidant activity of the extracts of leaves of argan tree showed a moderate antiradical capacity of DPPH (IC₅₀ = 0,130 mg/mL) and ABTS (IC₅₀ = 0.198 mg/mL). However, the leaves of argan tree showed a very interesting reducing power of Iron (IC₅₀ = 0.448 mg/ml) which is similar to that of the ascorbic acid (IC₅₀ = 0.371 mg/mL).

• Journal of the Korean Society for Library and Information Science
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• v.45 no.2
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• pp.251-275
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• 2011

In this paper, we propose a novel kernel called a semantic parse tree kernel that extends the parse tree kernel previously studied to extract protein-protein interactions(PPIs) and shown prominent results. Among the drawbacks of the existing parse tree kernel is that it could degenerate the overall performance of PPI extraction because the kernel function may produce lower kernel values of two sentences than the actual analogy between them due to the simple comparison mechanisms handling only the superficial aspects of the constituting words. The new kernel can compute the lexical semantic similarity as well as the syntactic analogy between two parse trees of target sentences. In order to calculate the lexical semantic similarity, it incorporates context-based word sense disambiguation producing synsets in WordNet as its outputs, which, in turn, can be transformed into more general ones. In experiments, we introduced two new parameters: tree kernel decay factors, and degrees of abstracting lexical concepts which can accelerate the optimization of PPI extraction performance in addition to the conventional SVM's regularization factor. Through these multi-strategic experiments, we confirmed the pivotal role of the newly applied parameters. Additionally, the experimental results showed that semantic parse tree kernel is superior to the conventional kernels especially in the PPI classification tasks.

• 한국HCI학회:학술대회논문집
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• 2007.02a
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• pp.667-674
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• 2007

Facial expressions provide significant clues about one's emotional state; however, it always has been a great challenge for machine to recognize facial expressions effectively and reliably. In this paper, we report a method of feature-based adaptive motion energy analysis for recognizing facial expression. Our method optimizes the information gain heuristics of ID3 tree and introduces new approaches on (1) facial feature representation, (2) facial feature extraction, and (3) facial feature classification. We use minimal reasonable facial features, suggested by the information gain heuristics of ID3 tree, to represent the geometric face model. For the feature extraction, our method proceeds as follows. Features are first detected and then carefully "selected." Feature "selection" is finding the features with high variability for differentiating features with high variability from the ones with low variability, to effectively estimate the feature's motion pattern. For each facial feature, motion analysis is performed adaptively. That is, each facial feature's motion pattern (from the neutral face to the expressed face) is estimated based on its variability. After the feature extraction is done, the facial expression is classified using the ID3 tree (which is built from the 1728 possible facial expressions) and the test images from the JAFFE database. The proposed method excels and overcomes the problems aroused by previous methods. First of all, it is simple but effective. Our method effectively and reliably estimates the expressive facial features by differentiating features with high variability from the ones with low variability. Second, it is fast by avoiding complicated or time-consuming computations. Rather, it exploits few selected expressive features' motion energy values (acquired from intensity-based threshold). Lastly, our method gives reliable recognition rates with overall recognition rate of 77%. The effectiveness of the proposed method will be demonstrated from the experimental results.

• Proceedings of the Korean Society for Language and Information Conference
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• 2007.11a
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• pp.76-85
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• 2007

This paper addresses a task of opinion extraction from given documents and its positive/negative classification. We propose a sentence classification method using a notion of syntactic piece. Syntactic piece is a minimum unit of structure, and is used as an alternative processing unit of n-gram and whole tree structure. We compute its semantic orientation, and classify opinion sentences into positive or negative. We have conducted an experiment on more than 5000 opinion sentences of multiple domains, and have proven that our approach attains high performance at 91% precision.

• Korean Journal of Food Science and Technology
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• v.50 no.4
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• pp.357-361
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• 2018

This study aimed to explore efficient DNA extraction methods using tree nuts. Four different DNA extraction procedures, including silica membrane method, modified silica method, cetyltrimethylammonium bromide (CTAB) method, and modified CTAB method were examined for their relative efficiency in extracting DNA from pistachio, pine nut, almond, hazelnut, cashew nut, walnut, and peanut. The quality and quantity of the extracted DNA were subsequently assessed by spectrometric measurements, gel electrophoresis, and PCR amplifications. CTAB method was the most appropriate one for extracting DNA from pine nut, cashew nut, pistachio, and peanut. However, it could be replaced by the silica membrane method for walnut and modified CTAB method for almond and hazelnut.

• Annual Conference on Human and Language Technology
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• 2014.10a
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• pp.149-152
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• 2014

자연어처리 분야에서 관계 추출은 중요한 연구 분야이다. 많은 관계 추출 연구는 지도 학습 방법을 사용하지만 정답을 구축하는 비용이 큰 문제가 있다. 본 논문에서는 distant supervision을 이용하여 데이터를 구축하고, suffix tree를 이용한 규칙기반 관계 추출 모델을 제안한다. Suffix tree를 이용한 관계추출의 Macro F1-measure는 84.05%로 관계 추출에서 사용이 가능함을 보였다.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.33 no.6
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• pp.605-614
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• 2015

Drone imaging, which is more cost-effective and controllable compared to airborne LiDAR, requires a low-cost camera and is used for capturing color images. From the overlapped color images, we produced two high-resolution digital surface models over different test areas. After segmentation, we performed tree identification according to the method proposed by , and computed the tree height and the canopy crown size. Compared with the field measurements, the computed results for the tree height in test area 1 (coniferous trees) were found to be accurate, while the results in test area 2 (deciduous coniferous trees) were found to be underestimated. The RMSE of the tree height was 0.84 m, and the width of the canopy crown was 1.51 m in test area 1. Further, the RMSE of the tree height was 2.45 m, and the width of the canopy crown was 1.53 m in test area 2. The experiment results validated the use of drone images for the extraction of a tree structure.

• Journal of Electrical Engineering and Technology
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• v.10 no.2
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• pp.670-675
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• 2015

Medical imaging is one of the most powerful tools for gaining information about internal organs and tissues. It is a challenging task to develop sophisticated image analysis methods in order to improve the accuracy of diagnosis. The objective of this paper is to develop a Computer Aided Diagnostics (CAD) scheme for Brain Tumour detection from Magnetic Resonance Image (MRI) using active contour models and to investigate with several approaches for improving CAD performances. The problem in clinical medicine is the automatic detection of brain Tumours with maximum accuracy and in less time. This work involves the following steps: i) Segmentation performed by Fuzzy Clustering with Level Set Method (FCMLSM) and performance is compared with snake models based on Balloon force and Gradient Vector Force (GVF), Distance Regularized Level Set Method (DRLSE). ii) Feature extraction done by Shape and Texture based features. iii) Brain Tumour detection performed by various tree classifiers. Based on investigation FCMLSM is well suited segmentation method and Random Forest is the most optimum classifier for this problem. This method gives accuracy of 97% and with minimum classification error. The time taken to detect Tumour is approximately 2 mins for an examination (30 slices).

• Proceedings of the KIEE Conference
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• 1997.11a
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• pp.302-304
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• 1997

Chemical structure and electrical properties such as water treeing and space charge accumulation of various raw materials(XLPE) used for power cable insulation were investigated. It was found that chemical structure was changed after crosslinking reaction and every materials have different amounts of DCP and antioxidant. Electrical properties were also changed after extraction using $CHCl_3$ and xylene. Water tree length was smaller with additives such as DCP and antioxidant and bigger with low molecular weight components of polyethylene than that of extracted samples. Heterocharge was changed into homocharge after extraction. This shows that additives and low molecular weight components of polyethylene cause the heterocharge.