I try to formalize the system of modal logic and interpret it in view of constructivism through this study. As to the meaning of a sentence, as we saw, Frege endorsed extensions in view of the fact that they are enough to provide for a compositional account for truth, in particular that (1) the assignment of extensions to expressions is compositional ; (2) the assignment of extensions to sentences coincides with the assignment of truth values. But nobody would be willing to admit that a truth value is what a sentence means and that consequently all true sentences are synonymous. So, if what we are after is meaning in the intuitive sense, then extensions would not do. This consideration has later become the point of departure of modal and intensional semantics. So, it is clear that the language of modal logic do not allow for an extensional interpretation. ${\square}$ is syntactically on a par with ${\vdash}$, hence within the extensional framework it would have to denote a unary truth function. This means that if modal logic is to be interpreted, we need a semantics which is not extensional. The first attempt to build a feasible intensional semantics was presented by Saul Kripke. He came to the conclusion that we must let sentences denote not truth values, but rather subsets of a given set. He called elements of the underlying set possible world. Hence each sentence is taken to denote the set of those possible world in which it is true. This lets us explicate necessity as 'truth in every possible world' and possibility as 'truth in at least one possible world'. But it is clear that the system of modal logic is not only an enlargement of propositional logic, as long as the former contains the new symbols, but that it is of an other nature. In fact, the modal logic is intensional, in that the operators do not determine the functions of truth any more. But this new element is not given a priori, but a posteriori from construction by logicist.
An, Joon-Sang;Kang, Kyung-Nam;Kim, San-Ha;Song, Ki-Il
Journal of the Korean Geotechnical Society
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v.35
no.4
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pp.27-35
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2019
This study confirmed the applicability to the field of geotechnical engineering for relatively complicated space and many target design variables in back analysis. The Sharan's equation and the Blum's method were used for the tunnel field and the retaining wall as a model for the multi-variate problem of geotechnical engineering. Optimization methods are generally divided into a deterministic method and a stochastic method. In this study, Simulated Annealing Method (SA) was selected as a deterministic method and Differential Evolution Algorithm (DEA) and Particle Swarm Optimization Method (PSO) were selected as stochastic methods. The three selected optimization methods were compared by applying a multi-variate model. The problem of deterministic method has been confirmed in the multi-variate back analysis of geotechnical engineering, and the superiority of DEA can be confirmed. DEA showed an average error rate of 3.12% for Sharan's solution and 2.23% for Blum's problem. The iteration number of DEA was confirmed to be smaller than the other two optimization methods. SA was confirmed to be 117.39~167.13 times higher than DEA and PSO was confirmed to be 2.43~6.91 times higher than DEA. Applying a DEA to the multi-variate back analysis of geotechnical problems can be expected to improve computational speed and accuracy.
Lee, Dong-Goo;Shin, Wu-Hyeon;Kim, Tae-Jung;Lee, Jeong-Ho;Lee, Young-Seok;Hwang, Heon;Choi, Sun
The Journal of Korea Institute of Information, Electronics, and Communication Technology
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v.12
no.2
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pp.170-177
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2019
In this paper, three theories for improving the stability of quadruped robot are presented. First, the Minimum-Jerk Trajectory is used to optimize the leg trajectory. Second, we compare the newly proposed sine wave and the conventional LSM in this paper based on the Jerk value. Third, we calculate the optimum stride of the sway through repetitive robot simulation using ADAMS-MATLAB cosimulation. Through the above process, the improvement of the robot walking is compared with the existing theory. First, the average gradient of the point where the leg trajectory changes rapidly was reduced from at least 1.2 to 2.9 by using the Minimum-Jerk targetory for the movement of the body and the end of the leg during the first walk, thereby increasing the walking stability. Second, the average Jerk was reduced by 0.019 on the Z-axis, 0.457 on the X-axis, and 0.02, 3D on the Y-axis by 0.479 using the Sin wave type sways presented in this paper, rather than the LSM(Longitude Stability Margin) method. Third, the length of the optimal stride for walking at least the Jerk value was derived from the above analysis, and the 20cm width length was the most stable.
This research was conducted to compare the rhythm reproduction abilities between older adults with and without mild cognitive impairment (MCI) and analyze the abilities depending on the rhythm idiom. Participants between 60-85 years of age were recruited from senior community centers, dementia prevention centers, and senior welfare centers. A total of 57 participants were included in this study: 27 diagnosed with MCI and 30 healthy older adults (HOA). The experiment was conducted individually in a private room in which a participant was given random binary time rhythm idioms and instructed to reproduce the rhythmic idioms with finger tapping. Each participant's beat production was recorded with the Beat Processing Device (BPD) for iPad. BPD calculated rhythm reproduction as measured through rhythm ratio and error among beats. Results showed marginal differences between the two groups in terms of mean scores of rhythm reproduction abilities. In terms of the rhythm ratio among beats, both groups' highest rhythm reproduction rate was for <♩ ♩>, and their lowest reproduction rate was for <♩. ♪>. In conclusion, there was no significant difference in rhythm reproduction ability between the HOA and MCI groups. However, the study found an interesting result related to performance level of rhythmic idioms. This result provides therapeutic insight for formulating rhythm tasks for older adults.
The caldera lake "Chun-ji" is located at the summit of Baekdu volcano, which is in the border of China and North Korea. Chun-ji Lake has altitude 2,189 m above sea level. The Chun-ji is freezing in the winter when the water temperature goes down to zero for a year, and it melts in the season when the water temperature goes up again. However,since it is located at a high altitude, there are many cloudy days, and it is difficult to observe with optical images. For this reason, radar images, which are less influenced by weather than optical images, are more effective for observing the ice of heaven and earth. In this study, 75 TerraSAR-X images from chun-ji area were used for analysis from 2015 to 2017, and the calculated ice area and temperature changes were analyzed. As a result, the ice of the caldera lake formed was formed in early December and slowly melted until mid-April. During this period, temperatures in the Samjiyeon area were about $-10^{\circ}C$ when ice was produced, and the temperature was about $0^{\circ}C$ in mid-April when it was thawing. Correlation coefficients between ice surface area and temperature in winter 2015 and 2016, where global ice is produced,show a high correlation of -0.82 and -0.75. In addition to the results of this study, it can be used as an indicator to monitor the volcanic activity by comparing the result of the recent volcanic activity with the result of the increase in water temperature using various imagery.
The Journal of Korean Institute of Next Generation Computing
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v.15
no.5
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pp.64-74
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2019
Although a non-rigid registration has high demands in clinical practice, it has a high computational complexity and it is very difficult for ensuring the accuracy and robustness of registration. This study proposes a method of applying a non-rigid registration to 3D magnetic resonance images of brain in an unsupervised learning environment by using a deep-learning network. A feature vector between two images is produced through the network by receiving both images from two different patients as inputs and it transforms the target image to match the source image by creating a displacement vector field. The network is designed based on a U-Net shape so that feature vectors that consider all global and local differences between two images can be constructed when performing the registration. As a regularization term is added to a loss function, a transformation result similar to that of a real brain movement can be obtained after the application of trilinear interpolation. This method enables a non-rigid registration with a single-pass deformation by only receiving two arbitrary images as inputs through an unsupervised learning. Therefore, it can perform faster than other non-learning-based registration methods that require iterative optimization processes. Our experiment was performed with 3D magnetic resonance images of 50 human brains, and the measurement result of the dice similarity coefficient confirmed an approximately 16% similarity improvement by using our method after the registration. It also showed a similar performance compared with the non-learning-based method, with about 10,000 times speed increase. The proposed method can be used for non-rigid registration of various kinds of medical image data.
This study examined the implications of a place-based earth science program integrated with Mathematics. 11 pre-service earth science teachers and 22 middle school students participated in the service education activities of earth science for 30 hours focusing on the measurement of the earth's size through earth science experiments as part of the middle school curriculum. In order to minimize errors that may occur during the earth's size measurement experiments using Eratosthenes's shadows length method of the ancient Greek era, the actual data were collected after triangulation ratios were conducted in the locations of two middle schools: one in remote metropolitan and the other in rural area. The two schools' students shared the final estimate result. Through this process, they learned the mathematical method to express the actual data effectively. Participants, experienced the importance and difficulty of the repetitive and accurate data acquisition process, and also discussed the causes of errors included in the final results. It implies that a Place-Based Earth Science Program activity can contribute to students' increased-understanding of the characteristics of earth science inquiry and to developing their problem solving skills, thinking ability, and communication skills as well, which are commonly emphasized in science and mathematics in the 2015 reunion curriculum. It is expected that a place-based science program can provide a foundation for developing an integrated curriculum of mathematics and science.
Journal of Korea Entertainment Industry Association
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v.15
no.1
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pp.53-62
/
2021
After the first to present projected moving pictures to audiences, the film industry has been reshaping along with technological advancements. Through the full-scale introduction of visual effects-oriented post-production and digital technologies in the film-making process, the film industry has not only undergone significant changes in the production, but is also embracing the cutting edge technologies broadly and expanding the scope of industry. Not long after the change to digital cinema, the concept of artificial intelligence, first known at the Dartmouth summer research project in 1956, before the digitalization of film, is expected to bring about a big transformation in the film industry once again. Large volume of clear digital data from digital film-making makes easy to apply recent artificial intelligence technologies represented by machine learning and deep learning. The use of artificial intelligence techniques is prominent around major visual effects studios due to automate many laborious, time-consuming tasks currently performed by artists. This study aims to predict how artificial intelligence technology will change the film industry in the future through analysis of visual effects production cases using artificial intelligence technology as a production tool and to discuss the industrial potential of artificial intelligence as visual effects technology.
Journal of Korean Tunnelling and Underground Space Association
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v.24
no.2
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pp.153-170
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2022
Waterjet has been comprehensively used in urban areas owing to a suitable technique for cutting concrete and rock, and low noise and vibration. Recently, the abrasive waterjet technique has been adopted and applied by the Korea Atomic Energy Research Institute to demolish concrete plugging without disturbing and damaging In-situ Demonstration of Engineered Barrier System in the disposal research tunnel. In this study, the use of abrasive waterjet in the tunnel was evaluated for practical applicability and the existing cutting model was compared with the experimental results. As a variable for waterjet cutting, multi-cutting, water flow rate, abrasive flow rate, and standoff distance were selected for the diversity of analysis. As regarding the practical application, the waterjet facilitated path selection for cutting the concrete plugging and prevented additional disturbances in the periphery. The pump's noise at idling was 64.9 dB which is satisfied with the noise regulatory standard, but it exceeded the standard at ejection to air and target concrete because the experiment was performed in the tunnel space. The experimental result showed that the error between the predicted and measured cutting volume was 12~13% for the first cut and 16% for second cut. The standoff distance had a significant influence on the cutting depth and width, and the error tended to decrease with decrement of standoff distance.
The Sea:JOURNAL OF THE KOREAN SOCIETY OF OCEANOGRAPHY
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v.27
no.2
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pp.49-70
/
2022
Sea Surface Temperature (SST), one of the ocean features, has a significant impact on climate, marine ecosystem and human activities. Therefore, SST prediction has been always an important issue. Recently, deep learning has drawn much attentions, since it can predict SST by training past SST patterns. Compared to the numerical simulations, deep learning model is highly efficient, since it can estimate nonlinear relationships between input data. With the recent development of Graphics Processing Unit (GPU) in computer, large amounts of data can be calculated repeatedly and rapidly. In this study, Short-term SST will be predicted through Convolutional Neural Network (CNN)-based U-Net that can handle spatiotemporal data concurrently and overcome the drawbacks of previously existing deep learning-based models. The SST prediction performance depends on the seasonal and interannual SST variabilities around the southern coast of Korea. The predicted SST has a wide range of variance during spring and summer, while it has small range of variance during fall and winter. A wide range of variance also has a significant correlation with the change of the Pacific Decadal Oscillation (PDO) index. These results are found to be affected by the intensity of the seasonal and PDO-related interannual SST fronts and their intensity variations along the southern Korean seas. This study implies that the SST prediction performance using the developed deep learning model can be significantly varied by seasonal and interannual variabilities in SST.
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