• Korean journal of communication and information
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• v.43
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• pp.314-358
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• 2008

This study examined how the meaning of news stories covering the split of national opinion was constructed in the media to represent social conflicts. To clarify the function of the term 'split of national opinion' as an ultimate term, this study examined the meaning of the term in the context of both text and society. Ten newspapers were included in the content analysis. The frequency of words used for the purpose of metaphor and equivalent in describing the split of national opinion was calculated to determine their meaning in the textual context. The frequency of incidents and subjects involved in allegedly causing the split of national opinion was calculated to determine their meaning in the social context. The results of this study are summarized as follows: First, the term 'split of national opinion' was coined by the newspapers as a metaphor of disease, disaster, and cost. The attitudes or the ways in which the split of national opinion was dealt with were generally negative and passive. Second, the term 'split of national opinion' was dealt with an equivalent status of such terms as national policy, national loss, societal problems, and ideology. Third, each newspaper reported that the split of national opinion had been caused by certain subjects, which indicates that each newspaper had its own position of viewing who was the key player in splitting the national opinion. The implication was also discussed that the use of the ultimate term would incur the unbalance of power between participants and the existing players, which would make individuals or groups who were involved in the social actions excluded and make the newspapers exercise the rhetorical power as news media.

• Journal of the Institute of Electronics and Information Engineers
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• v.49 no.12
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• pp.209-218
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• 2012

Recently, the Field Programmable Stateful Logic Array (FPSLA) was proposed as one of the most promising system integration technologies which will extend the life of the Moore's law. This work is the first proposal of the FPSLA design automation flow, and the approaches to logic synthesis, synchronization, physical mapping, and automatic placement of the FPSLA designs. The synchronization at each gate for pipelining determines the x-coordinates of cells, and reduces the placement to 1-dimensional problems. The objective function and its gradients for the non-linear optimization of the net length and placement density have been remodeled for the reduced global placement problem. Also, a recursive algorithm has been proposed to legalize the placement by relaxing the density overflow of bipartite bin groups in a top-down hierarchical fashion. The proposed model and algorithm are implemented, and validated by applying them to the ACM/SIGDA benchmark designs. The output state of a gate in an FPSLA needs to be duplicated so that each fanout gate can be connected to a dedicated copy. This property has been taken into account by merging the duplicated nets into a hyperedge, and then, splitting the hyperedge into edges as the optimization progresses. This yields additional 18.4% of the cell count reduction in the most dense logic stage. The practicality of the FPSLA can be further enhanced primarily by incorporating into the logic synthesis the constraint to avoid the concentrated fains of gates on some logic stages. In addition, an efficient algorithm needs to be devised for the routing problem which is based on a complicated graph. The graph models the nanowire crossbar which is trimmed to be embedded into the FPSLA fabric, and therefore, asymmetric. These CAD tools can be used to evaluate the fabric efficiency during the architecture enhancement as well as automate the design.

• Sim-seong Yeon-gu
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• v.38 no.2
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• pp.269-304
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• 2023

The purpose of this paper is to present the psychological meaning of the creation myths by utilizing related myths, analysand's dreams, active imagination, and artwork to reveal the creative function of the unconscious. The creation myth is the phenomenon of projection when a new order is demanded in the chaotic phase of personal and human history. Depending on the attitude of the ego, it can be a sign of a reconstruction/alteration of consciousness or an invasion. Related literature such as Jung, von Franz, Neumann, Harding, and Edinger, domestic papers, and case reports are introduced to identify the background for this research. The psychological meaning of 'darkness' in creation myths is regarded as unconscious that is too dark to see. The Eskimo creation myth and an analysand's dreams of being blind and wandering in darkness are discussed in relation to nigredo in Alchemy. The psychological meaning of 'massa confusa' regards Uroboros, pleroma, early childhood experience, and a psychological womb in which everything is contained in one. With related myths and unconscious materials, a discussion is followed on how this realm can be a precursor of creation but also be trapped in an abyss. The psychological meaning of 'separation of world parent' is related to splitting one into two when unconscious contexts were touched before it became consciousness. Related myths, 'the world created between heaven and earth,' 'celestial being descending to the earth,' and 'the legend of relocation of a mountain,' as well as clinical material, are examined. Then this paper discusses the clinical implications of the separation of heaven and earth occurring on its own, that the creator's emotional aspects, such as loneliness and anxiety, are involved, and that delayed separation leads to the death of creatura and sudden separation leads to the death of the chaos. Then, the meaning of 'separation of world parent' is discussed in relation with separatio, the alchemical process of acquiring light/consciousness from darkness/unconsciousness. The psychological meaning of the creation of 'land/island' refers to the emergence of consciousness, the contents of the unconscious material into the realm of the ego. Related myths, such as the 'body of the monster/dragon becoming land' and analysand's dreams, are introduced, referring to the embodiment of Mercurius. This is followed by discussing related myths in creating the land to coagulatio in alchemy and utilizing creative work such as active imagination, art, music, and dance that can coagulate or concretize unconscious material in clinical approaches. Finally, myths of resurfaced land after the Flood or the complete destruction of the world in relation to the reconstruction of ego are discussed with related clinical material to show the importance of the analyst/therapist/supervisor's mental stability and capacity.

• Journal of Intelligence and Information Systems
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• v.27 no.3
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• pp.139-156
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• 2021

The biggest reason for using a deep learning model in image classification is that it is possible to consider the relationship between each region by extracting each region's features from the overall information of the image. However, the CNN model may not be suitable for emotional image data without the image's regional features. To solve the difficulty of classifying emotion images, many researchers each year propose a CNN-based architecture suitable for emotion images. Studies on the relationship between color and human emotion were also conducted, and results were derived that different emotions are induced according to color. In studies using deep learning, there have been studies that apply color information to image subtraction classification. The case where the image's color information is additionally used than the case where the classification model is trained with only the image improves the accuracy of classifying image emotions. This study proposes two ways to increase the accuracy by incorporating the result value after the model classifies an image's emotion. Both methods improve accuracy by modifying the result value based on statistics using the color of the picture. When performing the test by finding the two-color combinations most distributed for all training data, the two-color combinations most distributed for each test data image were found. The result values were corrected according to the color combination distribution. This method weights the result value obtained after the model classifies an image's emotion by creating an expression based on the log function and the exponential function. Emotion6, classified into six emotions, and Artphoto classified into eight categories were used for the image data. Densenet169, Mnasnet, Resnet101, Resnet152, and Vgg19 architectures were used for the CNN model, and the performance evaluation was compared before and after applying the two-stage learning to the CNN model. Inspired by color psychology, which deals with the relationship between colors and emotions, when creating a model that classifies an image's sentiment, we studied how to improve accuracy by modifying the result values based on color. Sixteen colors were used: red, orange, yellow, green, blue, indigo, purple, turquoise, pink, magenta, brown, gray, silver, gold, white, and black. It has meaning. Using Scikit-learn's Clustering, the seven colors that are primarily distributed in the image are checked. Then, the RGB coordinate values of the colors from the image are compared with the RGB coordinate values of the 16 colors presented in the above data. That is, it was converted to the closest color. Suppose three or more color combinations are selected. In that case, too many color combinations occur, resulting in a problem in which the distribution is scattered, so a situation fewer influences the result value. Therefore, to solve this problem, two-color combinations were found and weighted to the model. Before training, the most distributed color combinations were found for all training data images. The distribution of color combinations for each class was stored in a Python dictionary format to be used during testing. During the test, the two-color combinations that are most distributed for each test data image are found. After that, we checked how the color combinations were distributed in the training data and corrected the result. We devised several equations to weight the result value from the model based on the extracted color as described above. The data set was randomly divided by 80:20, and the model was verified using 20% of the data as a test set. After splitting the remaining 80% of the data into five divisions to perform 5-fold cross-validation, the model was trained five times using different verification datasets. Finally, the performance was checked using the test dataset that was previously separated. Adam was used as the activation function, and the learning rate was set to 0.01. The training was performed as much as 20 epochs, and if the validation loss value did not decrease during five epochs of learning, the experiment was stopped. Early tapping was set to load the model with the best validation loss value. The classification accuracy was better when the extracted information using color properties was used together than the case using only the CNN architecture.

• Korean Journal of Mineralogy and Petrology
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• v.33 no.3
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• pp.273-291
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• 2020

The strength characteristics of the three orthogonal splitting planes, known as rift, grain and hardway planes in granite quarries, were examined. R, G and H specimens were obtained from the block samples of Jurassic granites in Geochang and Hapcheon areas. The directions of the long axes of these three specimens are perpendicular to each of the three planes. First, The chart, showing the scaling characteristics of three graphs related to the uniaxial compressive strengths of R, G and H specimens, were made. The graphs for the three specimens, along with the increase of strength, are arranged in the order of H < G < R. The angles of inclination of the graphs for the three specimens, suggesting the degree of uniformity of the texture within the specimen, were compared. The above angles for H specimens(θ^H, 24.0°~37.3°) are the lowest among the three specimens. Second, the scaling characteristics related to the three graphs of RG, GH and RH specimens, representing a combination of the mean compressive strengths of the two specimens, were derived. These three graphs, taking the various N-shaped forms, are arranged in the order of GH < RH < RG. Third, the correlation chart between the strength difference(Δσ_t) and the angle of inclination(θ) was made. The above two parameters show the correlation of the exponential function with an exponent(λ) of -0.003. In both granites, the angle of inclination(θ^RH) of the RH-graph is the lowest. Fourth, the six types of charts, showing the correlations among the three kinds of compressive strengths for the three specimens and the five parameters for the two sets of microcracks aligned parallel to the compressive load applied to each specimen, were made. From these charts for Geochang and Hapcheon granites, the mean value(0.877) of the correlation coefficients(R²) for total density(Lt), along with the frequency(N, 0.872) and density(ρ, 0.874), is the highest. In addition, the mean values(0.829) of correlation coefficients associated with the mean compressive strengths are more higher than the minimum(0.768) and maximum(0.804) compression strengths of three specimens. Fifth, the distributional characteristics of the Brazilian tensile strengths measured in directions parallel to the above two sets of microcracks in the three specimens from Geochang granite were derived. From the related chart, the three graphs for these tensile strengths corresponding to the R, G and H specimens show an order of H(R1+G1) < G(R2+H1) < R(R1+G1). The order of arrangement of the three graphs for the tensile strengths and that for the compressive strengths are mutually consistent. Therefore, the compressive strengths of the three specimens are proportional to the three types of tensile strengths. Sixth, the values of correlation coefficients, among the three tensile strengths corresponding to each cumulative number(N=1~10) from the above three graphs and the five parameters corresponding to each graph, were derived. The mean values of correlation coefficients for each parameter from the 10 correlation charts increase in the order of density(0.763) < total length(0.817) < frequency(0.839) < mean length(Lm, 0.901) ≤ median length(Lmed, 0.903). Seventh, the correlation charts among the compressive strengths and tensile strengths for the three specimens were made. The above correlation charts were divided into nine types based on the three kinds of compressive strengths and the five groups(A~E) of tensile strengths. From the related charts, as the tensile strength increases with the mean and maximum compressive strengths excluding the minimum compressive strength, the value of correlation coefficient increases rapidly.

• Journal of the Korean Wood Science and Technology
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• v.2 no.2
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• pp.8-12
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• 1974

1. If one unity is given to the prongs whose ends touch each other for estimating the internal stresses occuring in it, the internal stresses which are developed in the open prongs can be evaluated by the ratio to the unity. In accordance with the above statement, an equation was derived as follows. For employing this equation, the prongs should be made as shown in Fig. I, and be measured A and B' as indicated in Fig. l. A more precise value will result as the angle (J becomes smaller. $CH=\frac{(A-B') (4W+A) (4W-A)}{2A[(2W+(A-B')][2W-(A-B')]}{\times}100%$ where A is thickness of the prong, B' is the distance between the two prongs shown in Fig. 1 and CH is the value of internal stress expressed by percentage. It precision is not required, the equation can be simplified as follows. $CH=\frac{A-B'}{A}{\times}200%$ 2. Under scheduled drying condition III the kiln, when the weight of a sample board is constant, the moisture content of the shell of a sample board in the case of a normal casehardening is lower than that of the equilibrium moisture content which is indicated by the Forest Products Laboratory, U. S. Department of Agriculture. This result is usually true, especially in a thin sample board. A thick unseasoned or reverse casehardened sample does not follow in the above statement. 3. The results in the comparison of drying rate with five different kinds of wood given in Table 1 show that the these drying rates, i.e., the quantity of water evaporated from the surface area of I centimeter square per hour, are graded by the order of their magnitude as follows. (1) Ginkgo biloba Linne (2) Diospyros Kaki Thumberg. (3) Pinus densiflora Sieb. et Zucc. (4) Larix kaempheri Sargent (5) Castanea crenata Sieb. et Zucc. It is shown, for example, that at the moisture content of 20 percent the highest value revealed by the Ginkgo biloba is in the order of 3.8 times as great as that for Castanea crenata Sieb. & Zucc. which has the lowest value. Especially below the moisture content of 26 percent, the drying rate, i.e., the function of moisture content in percentage, is represented by the linear equation. All of these linear equations are highly significant in testing the confficient of X i. e., moisture content in percentage. In the Table 2, the symbols are expressed as follows; Y is the quantity of water evaporated from the surface area of 1 centimeter square per hour, and X is the moisture content of the percentage. The drying rate is plotted against the moisture content of the percentage as in Fig. 2. 4. One hundred times the ratio(P%) of the number of samples occuring in the CH 4 class (from 76 to 100% of CH ratio) within the total number of saplmes tested to those of the total which underlie the given SR ratio is measured in Table 3. (The 9% indicated above is assumed as the danger probability in percentage). In summarizing above results, the conclusion is in Table 4. NOTE: In Table 4, the column numbers such as 1. 2 and 3 imply as follows, respectively. 1) The minimum SR ratio which does not reveal the CH 4, class is indicated as in the column 1. 2) The extent of SR ratio which is confined in the safety allowance of 30 percent is shown in the column 2. 3) The lowest limitation of SR ratio which gives the most danger probability of 100 percent is shown in column 3. In analyzing above results, it is clear that chestnut and larch easly form internal stress in comparison with persimmon and pine. However, in considering the fact that the revers, casehardening occured in fir and ginkgo, under the same drying condition with the others, it is deduced that fir and ginkgo form normal casehardening with difficulty in comparison with the other species tested. 5. All kinds of drying defects except casehardening are developed when the internal stresses are in excess of the ultimate strength of material in the case of long-lime loading. Under the drying condition at temperature of $170^{\circ}F$ and the lower humidity. the drying defects are not so severe. However, under the same conditions at $200^{\circ}F$, the lower humidity and not end coated, all sample boards develop severe drying defects. Especially the chestnut was very prone to form the drying defects such as casehardening and splitting.