• Journal of Information Processing Systems
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• v.16 no.2
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• pp.329-342
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• 2020

In recent years, emotional text classification is one of the essential research contents in the field of natural language processing. It has been widely used in the sentiment analysis of commodities like hotels, and other commentary corpus. This paper proposes an improved W-LDA (weighted latent Dirichlet allocation) topic model to improve the shortcomings of traditional LDA topic models. In the process of the topic of word sampling and its word distribution expectation calculation of the Gibbs of the W-LDA topic model. An average weighted value is adopted to avoid topic-related words from being submerged by high-frequency words, to improve the distinction of the topic. It further integrates the highest classification of the algorithm of support vector machine based on the extracted high-quality document-topic distribution and topic-word vectors. Finally, an efficient integration method is constructed for the analysis and extraction of emotional words, topic distribution calculations, and sentiment classification. Through tests on real teaching evaluation data and test set of public comment set, the results show that the method proposed in the paper has distinct advantages compared with other two typical algorithms in terms of subject differentiation, classification precision, and F1-measure.

• Mycobiology
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• v.31 no.3
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• pp.133-138
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• 2003

Analysis of phylogenetic relationship was performed among Phellinus species based on 18S ribosomal subunit sequence data. Twenty-five strains of 19 Phellinus species including P. linteus were examined in this study. Regions of 18S ribosomal subunit were very conserved, but some variable regions between Phellinus species were observed. The species-specific detection primers, modified by 2 or 3 nucleotides in sense primer were designed based on 18S ribosomal DNA(rDNA) sequence data. The 210 by PCR bands were detected with annealing temperature $48^{\circ}C$. The 18S 2F-18S 4R detection primer set distinguished P. linteus from various Phellinus species but some species like P. baumii, P. weirianius, P. rhabarberinus and P. pomaceus also had weak reactivity on this primer set. The 18S 3F-18S 4R primer set distinguished only P. linteus from various Phellinus species, although sensitivity with this primer set was lower than that of 18S 2F-18 4R primer set. These primer sets would be useful for the detection of only P. linteus among unknown Phellinus species rapidly.

• Geomechanics and Engineering
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• v.27 no.6
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• pp.551-560
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• 2021

Due to the low strength and high compressibility characteristics, the loess deposits tunnels are prone to large deformations and collapse. An accurate stability evaluation for loess deposits is of considerable significance in deformation control and safety work during tunnel construction. 37 groups of representative data based on real loess deposits cases were adopted to establish the stability evaluation model for the tunnel project in Yan'an, China. Physical and mechanical indices, including water content, cohesion, internal friction angle, elastic modulus, and poisson ratio are selected as index system on the stability level of loess. The data set is randomly divided into 80% as the training set and 20% as the test set. Firstly, principal component analysis (PCA) is used to convert the five index system to three linearly independent principal components X1, X2 and X3. Then, the principal components were used as input vectors for probabilistic neural network (PNN) to map the nonlinear relationship between the index system and stability level of loess. Furthermore, Leave-One-Out cross validation was applied for the training set to find the suitable smoothing factor. At last, the established model with the target smoothing factor 0.04 was applied for the test set, and a 100% prediction accuracy rate was obtained. This intelligent classification method for loess deposits can be easily conducted, which has wide potential applications in evaluating loess deposits.

• Proceedings of the KIEE Conference
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• 2005.11b
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• pp.183-185
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• 2005

This paper discusses an economic study analysis of captive power plant as a commercial plant in the cost based pool market. In this paper I assumed the conversion of a captive power plant owned by factories to a commercial plant and investigated the changes in profitability associated with this. I set the total electricity expense of a captive purpose plant as state A and the costs associated with converting to a commercial purpose plant as state B. Each state subdivided by case which is classified its plant variable cost, type of generation (combined cycle, single cycle) and type of power contract received. After set model for each case, different economic benefits by each case can be calculated.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.48 no.4
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• pp.30-37
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• 2011

This paper proposes a language set of hand motions for enhancing the performance of vision-based hand signal recognizer. Based on the statistical analysis of the angular tendency of hand movements in sign language and the hand motions in practical use, we construct four motion primitives as building blocks for basic hand motions. By combining these motion primitives, we design a discernable 'fundamental hand motion set' toward increasing the hand signal recognition. To demonstrate the validity of proposed designing method, we develop a 'fundamental hand motion set' recognizer based on hidden Markov model (HMM). The recognition system showed 99.01% recognition rate on the proposed language set. This result validates that the proposed language set enhances discernaility among the hand motions such that the performance of hand signal recognizer is improved.

• Toxicological Research
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• v.32 no.4
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• pp.289-300
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• 2016

Non-genotoxic carcinogens are substances that induce tumorigenesis by non-mutagenic mechanisms and long term rodent bioassays are required to identify them. Recent studies have shown that transcription profiling can be applied to develop early identifiers for long term phenotypes. In this study, we used rat liver expression profiles from the NTP (National Toxicology Program, Research Triangle Park, USA) DrugMatrix Database to construct a gene classifier that can distinguish between non-genotoxic carcinogens and other chemicals. The model was based on short term exposure assays (3 days) and the training was limited to oxidative stressors, peroxisome proliferators and hormone modulators. Validation of the predictor was performed on independent toxicogenomic data (TG-GATEs, Toxicogenomics Project-Genomics Assisted Toxicity Evaluation System, Osaka, Japan). To build our model we performed Random Forests together with a recursive elimination algorithm (VarSelRF). Gene set enrichment analysis was employed for functional interpretation. A total of 770 microarrays comprising 96 different compounds were analyzed and a predictor of 54 genes was built. Prediction accuracy was 0.85 in the training set, 0.87 in the test set and increased with increasing concentration in the validation set: 0.6 at low dose, 0.7 at medium doses and 0.81 at high doses. Pathway analysis revealed gene prominence of cellular respiration, energy production and lipoprotein metabolism. The biggest target of toxicogenomics is accurately predict the toxicity of unknown drugs. In this analysis, we presented a classifier that can predict non-genotoxic carcinogenicity by using short term exposure assays. In this approach, dose level is critical when evaluating chemicals at early time points.

• Wind and Structures
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• v.26 no.2
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• pp.75-87
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• 2018

A large number of low-rise buildings experienced serious roof covering failures under strong wind while few suffered structural damage. Clay and concrete tiles are two main kinds of roof covering. For the tile roof system, few researches were carried out based on Finite Element (FE) analysis due to the difficulty in the simulation of the interface between the tiles and the roof sheathing (the bonding materials, foam or mortar). In this paper, the FE analysis of a single clay or concrete tile with foam-set or mortar-set were built with the interface simulated by the equivalent nonlinear springs based on the mechanical uplift and displacement tests, and they were expanded into the whole roof. A detailed wind tunnel test was carried out at Tongji University to acquire the wind loads on these two kinds of roof tiles, and then the test data were fed into the FE analysis. For the purpose of validation and calibration, the results of FE analysis were compared with the full-scale performance ofthe tile roofs under simulated strong wind impact through one-of-a-kind Wall of Wind (WoW) apparatus at Florida International University. The results are consistent with the WoW test that the roof of concrete tiles with mortar-set provided the highest resistance, and the material defects or improper construction practices are the key factors to induce the roof tiles' failure. Meanwhile, the staggered setting of concrete tiles would help develop an interlocking mechanism between the tiles and increase their resistance.

• Environmental Analysis Health and Toxicology
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• v.19 no.1
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• pp.81-91
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• 2004

Although it is suggested that risk -based management plan is needed to manage air pollution effectively, we have no resources enough to evaluate all aspects of substances and set priorities. So we need to develop a logical and easy risk-based priority setting method. However, it if impossible that only one generic system that is consistent with all the use is developed. In this study, we proposed a human health risk based priority-setting method for hazardous air pollutants, and ranked priorities for this method. First of all, after investigating previous chemical ranking and scoring systems, we chose appropriate indicators and logics to goal of this study and made a chemical priority ranking method using these. As results, final scores in priority ranking method were derived for 25 substances, and ethylene oxide, acrylonitrile and vinyl chloride were included in high ranks. In addition, same substances were highly ranked when using default values like when using no default, but the scores of hydrofluoric acid and ryan and compounds were sensitive to default values. This study could be important that priorities were set including toxicity type and quality and local inherent exposure conditions and we can set area-specific management guidelines and survey plans as a screening tool.

• Journal of the Korea Society of Computer and Information
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• v.23 no.4
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• pp.147-153
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• 2018

In this paper, we propose an efficient WBC 14-Diff classification which performs using the WBC-ResNet-152, a type of CNN model. The main point of view is to use Super-pixel for the segmentation of the image of WBC, and to use ResNet for the classification of WBC. A total of 136,164 blood image samples (224x224) were grouped for image segmentation, training, training verification, and final test performance analysis. Image segmentation using super-pixels have different number of images for each classes, so weighted average was applied and therefore image segmentation error was low at 7.23%. Using the training data-set for training 50 times, and using soft-max classifier, TPR average of 80.3% for the training set of 8,827 images was achieved. Based on this, using verification data-set of 21,437 images, 14-Diff classification TPR average of normal WBCs were at 93.4% and TPR average of abnormal WBCs were at 83.3%. The result and methodology of this research demonstrates the usefulness of artificial intelligence technology in the blood cell image classification field. WBC-ResNet-152 based morphology approach is shown to be meaningful and worthwhile method. And based on stored medical data, in-depth diagnosis and early detection of curable diseases is expected to improve the quality of treatment.

• ETRI Journal
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• v.38 no.5
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• pp.885-895
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• 2016

The lowest power mode (passive-standby mode) was proposed for reducing the power consumption of set-top boxes in a standby state when not receiving content. However, low-power set-top boxes equipped with the lowest power mode have been rarely commercialized because of their low-quality user experience. In the lowest power mode, they deactivates almost all of operational modules and processes, and thus require dozens of seconds for activation latency (that is, the latency for activating all modules of the set-top boxes in a standby state). They are not even updated in a standby state because they deactivate their network interfaces in a standby state. This paper proposes an adaptive standby mode scheduling method for improving the user experience of such boxes. Set-top boxes using the proposed method can analyze the activation pattern and find the frequently used time period (that is, when the set-top boxes are frequently activated). They prepare for their activation during this frequently used time period, thereby reducing the activation latency and enabling their update in a standby state.