• Journal of Korean Philosophical Society
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• no.118
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• pp.25-51
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• 2017

The purpose of this article is to elucidate Plotinus' concept of freedom. Particular attention is paid to two terms, 'what is self-determined' (to autexousion) and 'what is up to us' (to $eph^{\prime}h{\hat{e}}min$), which Plotinus employs in order to articulate the meaning of freedom. It is shown that freedom in Plotinus consists in the power of doing whatever one wills while willing the good. We first situate Plotinus' concept of freedom in the Socratic tradition. Next we investigate how Plotinus and Alexander of Aphrodisias conceptualize freedom in terms of self-determination in the context of criticizing determinism. It is shown that Alexander tries to secure the psychological grounds for human moral responsibility by introducing a causally undetermined power of choice between alternatives. In contrast, Plotinus is interested in psychological conditions that allow humans to do the right thing. For this purpose, he establishes the concept of will ($boul{\hat{e}}sis$) as the power of wanting and choosing the best. We then try to clarify his claim that free will cannot choose otherwise by appealing to his concept of divine freedom, which idealizes the power of doing one's best and being oneself at one's best. Finally, we discuss Plotinus' view of the limitations and possibilities of human freedom and indicate its practical implications. In conclusion we claim that Plotinus pleads for an active way of living which spreads inner freedom out into the world, rather than living in seclusion so as to protect an inner freedom which is pure.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.12 no.5
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• pp.467-474
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• 2019

In this paper, we propose a novel method to improve FPS while maintaining the accuracy of YOLO v2 model in NVIDIA Jetson TX1. In general, in order to reduce the amount of computation, a conversion to an integer operation or reducing the depth of a network have been used. However, the accuracy of recognition can be deteriorated. So, we use methods to reduce computation and memory consumption through adjustment of the filter size and integrated computation of the network The first method is to replace the $3{\times}3$ filter with a $1{\times}1$ filter, which reduces the number of parameters to one-ninth. The second method is to reduce the amount of computation through CBR (Convolution-Add Bias-Relu) among the inference acceleration functions of TensorRT, and the last method is to reduce memory consumption by integrating repeated layers using TensorRT. For the simulation results, although the accuracy is decreased by 1% compared to the existing YOLO v2 model, the FPS has been improved from the existing 3.9 FPS to 11 FPS.

• Journal of the Korean Academy of Esthetic Dentistry
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• v.27 no.2
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• pp.82-96
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• 2018

3D printing is a process of producing 3d object from a digital file in STL format by joining, bonding, sintering or polymerizing small volume elements by layer. The various type of 3d printing is classified according to the additive manufacturing strategies. Among the types of 3D printer, SLA(StereoLithography Apparatus) and DLP(Digital Light Processing) 3D printer which use polymerization by light source are widely used in dental office. In the previous study, a full-arch scale 3d printed model is less precise than a conventional stone model. However, in scale of quadrant arch, a 3d printed model is significantly precise than a five-axis milled model. Using $3^{rd}$ Party dental CAD program, full denture, provisional crowns and diagnostic wax-up model are fabricated by 3d printer in dental office. In Orthodontics, based on virtual setup model, indirect bracket bonding tray can be generated by 3d printer. And thermoforming clear aligner can be fabricated on the 3d printed model. 3D printed individual drilling guide enable the clinician to place the dental implant on the proper position. The development of layer additive technology enhance the quality of 3d printing object and shorten the operating time of 3D printing. In the near future, traditional dental laboratory process such as casting, denture curing will be replaced by digital 3D printing.

• KIPS Transactions on Software and Data Engineering
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• v.9 no.12
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• pp.403-410
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• 2020

In addition to the research on noise removal and super-resolution using the data restoration (Output result) function of Autoencoder, research on the performance improvement of clustering using the dimension reduction function of autoencoder are actively being conducted. The clustering function and data restoration function using Autoencoder have common points that both improve performance through the same learning. Based on these characteristics, this study conducted an experiment to see if the autoencoder model designed to have excellent data recovery performance is superior in clustering performance. Skip connection technique was used to design autoencoder with excellent data recovery performance. The output result performance and clustering performance of both autoencoder model with Skip connection and model without Skip connection were shown as graph and visual extract. The output result performance was increased, but the clustering performance was decreased. This result indicates that the neural network models such as autoencoders are not sure that each layer has learned the characteristics of the data well if the output result is good. Lastly, the performance degradation of clustering was compensated by using both latent code and skip connection. This study is a prior study to solve the Hanja Unicode problem by clustering.

• Journal of the Korea Convergence Society
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• v.13 no.3
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• pp.281-289
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• 2022

Plasma ozone is utilized in a variety of applications in the field of sterilization due to its high sterilization performance. Dielectric materials used in DBD(dielectric barrier discharges) are mainly polymer, quartz and ceramics. These dielectric layers have the advantage of limiting the amount of supplied electron charge and allowing plasma to occur evenly on the surface of dielectric. Actually, the target or environment for sterilization is often a complex structure, so research and academic study are needed by utilizing the concept of space sterilization. In this study, the device is applied to generate DBD plasma at atmospheric pressure for disinfection due to the effectiveness in producing radicals and ozone. The generator of plasma ozone is a basic structure of dielectric barrier discharge by placing ceramic tube dielectrics and stainless steel electrical conductors at regular intervals. Various applications can be developed based on the proposed design method. Plasma ozone generation for space sterilization device is recognized as an excellent sterilization device. Through the design and verification of the device, we intend to establish an optimal design of the spatial sterilization device and provide the basis data for sterilization applications.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.42 no.1
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• pp.35-44
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• 2022

The V_S30 map is used as a key variable for site amplification in the ShakeMap, which predicts ground motion at any site. However, no V_S30 map considering Korean geology and geomorphology has been developed yet. To develop a proxy-based V_S30 map, we used 1,101 V_S profiles obtained from a geophysical survey and collected proxy layers of geological and topographical information for the Korean Peninsula. Then, V_S30 prediction models were developed using linear regression analysis for each geological age considering the distribution of V_S30. As a result, models depending on geomorphology were suggested per each geologic group, including Quaternary, Fill, Ocean, Mesozoic group and Precambrian. Resolution of map is doubled from that of V_S30 map by U.S. Geological Survey (USGS). Standard deviation of residual in natural log of proxy-based V_S30 map is 0.233, whereas standard deviation of slope-based USGS V_S30 map is 0.387. Therefore, the proxy-based V_S30 map developed in this study is expected to have less uncertainty and to contribute to predicting more accurately the ground motion amplitude.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.39 no.6
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• pp.515-523
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• 2021

An integrated underground spatial map consists of underground facilities, underground structures, and ground information, and is periodically updated. In this paper, we design and implement a system for detecting and extracting only changed ground objects to shorten the map update speed. To find the changed objects, all the objects are compared, which are included in the newly input map and the reference map in the integrated map. Since the entire process of comparing objects and generating results is classified by function, the implemented system is composed of several modules such as object comparer, changed object detector, history data manager, changed object extractor, changed type classifier, and changed object saver. We use two metrics: detection rate and extraction rate, to evaluate the performance of the system. As a result of applying the system to boreholes, ground wells, soil layers, and rock floors in Pyeongtaek, 100% of inserted, deleted, and updated objects in each layer are detected. In addition, it provides the advantage of ensuring the up-to-dateness of the reference map by downloading it whenever maps are compared. In the future, additional research is needed to confirm the stability and effectiveness of the developed system using various data to apply it to the field.

• Journal of the Korean Association of Geographic Information Studies
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• v.25 no.4
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• pp.163-180
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• 2022

Real estate data can be big data. Because the amount of real estate data is growing rapidly and real estate data interacts with various fields such as the economy, law, and crowd psychology, yet is structured with complex data layers. The existing Relational Database tends to show difficulty in handling various relationships for managing real estate big data, because it has a fixed schema and is only vertically extendable. In order to improve such limitations, this study constructs the real estate data in a Graph Database and verifies its usefulness. For the research method, we modeled various real estate data on MySQL, one of the most widely used Relational Databases, and Neo4j, one of the most widely used Graph Databases. Then, we collected real estate questions used in real life and selected 9 different questions to compare the query times on each Database. As a result, Neo4j showed constant performance even in queries with multiple JOIN statements with inferences to various relationships, whereas MySQL showed a rapid increase in its performance. According to this result, we have found out that a Graph Database such as Neo4j is more efficient for real estate big data with various relationships. We expect to use the real estate Graph Database in predicting real estate price factors and inquiring AI speakers for real estate.

• Journal of Broadcast Engineering
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• v.28 no.3
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• pp.293-301
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• 2023

Unstandardized medical data collection and management are still being conducted manually, and studies are being conducted to classify CT data using deep learning to solve this problem. However, most studies are developing models based only on the axial plane, which is a basic CT slice. Because CT images depict only human structures unlike general images, reconstructing CT scans alone can provide richer physical features. This study seeks to find ways to achieve higher performance through various methods of converting CT scan to 2D as well as axial planes. The training used 1042 CT scans from five body parts and collected 179 test sets and 448 with external datasets for model evaluation. To develop a deep learning model, we used InceptionResNetV2 pre-trained with ImageNet as a backbone and re-trained the entire layer of the model. As a result of the experiment, the reconstruction data model achieved 99.33% in body part classification, 1.12% higher than the axial model, and the axial model was higher only in brain and neck in contrast classification. In conclusion, it was possible to achieve more accurate performance when learning with data that shows better anatomical features than when trained with axial slice alone.

• The Journal of the Acoustical Society of Korea
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• v.42 no.2
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• pp.102-111
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• 2023

Automatic Music Transcription (AMT) is a task that detects and recognizes musical note events from a given audio recording. In this paper, we focus on reducing the latency of real-time AMT systems on piano music. Although neural AMT models have been adapted for real-time piano transcription, they suffer from high latency, which hinders their usefulness in interactive scenarios. To tackle this issue, we explore several techniques for reducing the intrinsic latency of a neural network for piano transcription, including reducing window and hop sizes of Fast Fourier Transformation (FFT), modifying convolutional layer's kernel size, and shifting the label in the time-axis to train the model to predict onset earlier. Our experiments demonstrate that combining these approaches can lower latency while maintaining high transcription accuracy. Specifically, our modified model achieved note F1 scores of 92.67 % and 90.51 % with latencies of 96 ms and 64 ms, respectively, compared to the baseline model's note F1 score of 93.43 % with a latency of 160 ms. This methodology has potential for training AMT models for various interactive scenarios, including providing real-time feedback for piano education.