• The Journal of the Convergence on Culture Technology
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• v.8 no.6
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• pp.807-812
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• 2022

Recently, as the number of voice recording files submitted as court evidence increases, the number of cases claiming forgery is also increasing. If the audio recording file structure and metadata, which are objective grounds, are completely forged, it is actually impossible to detect forgery of the sophisticated audio recording file. It is extremely rare for the court to reject the file structure and metadata analysis performed with the forged audio recording file. The purpose of this study is to prove that forgery of voice recording file structure and metadata is easily possible. To this end, in this study, it was introduced that forgery detection is impossible when the 'mixed paste' function, which enables sophisticated editing based on the typification of the editing method of voice recording files, is applied. Moreover, it has been proven through experiments that forgery of file structure and metadata is possible. Therefore, a stricter standard for judging the admissibility of evidence is required when the audio recording file is adopted as digital evidence. This study will not only contribute to the standard of integrity in the adoption of digital evidence by judges, but will also contribute to the method of constructing a dataset for artificial intelligence in detecting forgery of recorded files that is expected to be developed in the future.

• Journal of the Korean Society of Radiology
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• v.16 no.1
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• pp.25-34
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• 2022

Brain computed tomography (CT) is useful for brain lesion diagnosis, such as brain hemorrhage, due to non-invasive methodology, 3-dimensional image provision, low radiation dose. However, there has been numerous misdiagnosis owing to a lack of radiologist and heavy workload. Recently, object detection technologies based on artificial intelligence have been developed in order to overcome the limitations of traditional diagnosis. In this study, the applicability of a deep learning-based YOLOv5s model was evaluated for brain hemorrhage detection using brain CT images. Also, the effect of hyperparameters in the trained YOLOv5s model was analyzed. The YOLOv5s model consisted of backbone, neck and output modules. The trained model was able to detect a region of brain hemorrhage and provide the information of the region. The YOLOv5s model was trained with various activation functions, optimizer functions, loss functions and epochs, and the performance of the trained model was evaluated in terms of brain hemorrhage detection accuracy and training time. The results showed that the trained YOLOv5s model is able to provide a bounding box for a region of brain hemorrhage and the accuracy of the corresponding box. The performance of the YOLOv5s model was improved by using the mish activation function, the stochastic gradient descent (SGD) optimizer function and the completed intersection over union (CIoU) loss function. Also, the accuracy and training time of the YOLOv5s model increased with the number of epochs. Therefore, the YOLOv5s model is suitable for brain hemorrhage detection using brain CT images, and the performance of the model can be maximized by using appropriate hyperparameters.

• The Journal of the Convergence on Culture Technology
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• v.8 no.5
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• pp.279-284
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• 2022

As a study of the blended learning method on design education through the blended learning method, I would like to propose that more advanced learner-led customized design education is possible. Understanding in face-to-face classes and advantages in non-face-to-face classes can be supplemented in an appropriate way in remote classes. Advanced artificial intelligence and big data technology can provide personalized and subdivided learning materials and effective learning methods tailored to learners' levels and interests based on quantified data in design classes. In this paper, it was proposed to maximize the efficiency of the class by applying a method that exceeds the limitations of time and space through the proposal of the A La Carte model (A La Carte). It is a remote class that can be heard anytime, anywhere, and it is also possible to bridge the educational quality and educational gap provided to students living in underprivileged areas. As the goal of fostering creative convergence-type future talents, it is changing with a rapid technological development speed. It is necessary to adapt to the change in learning methods in line with this. An analysis of the infographic virtual space design and construction process through the A La Carte model (A La Carte) proposal was presented. Rather than simply acquiring knowledge, it is expected that knowledge can be sorted, distinguished, learned, and easily reborn with its own knowledge.

• Knowledge Management Research
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• v.23 no.2
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• pp.193-210
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• 2022

The rapid development of mobile technology and the improvement of network speed are providing convenience to various services, and mobile shopping malls are no exception. Although efforts are being made to promote sales by combining various technologies such as customized recommendations using big data and specialized personalization services based on artificial intelligence, most mobile shopping malls have the same detailed page information structure including detailed product information. In this context, in this study, it was determined that the content layout of the product detail page and the mobile product detail page layout tailored to the consumer's preference should be presented according to the consumer's preference. Based on Higgins' Regulatory Focus Theory, a study of consumer propensity revealed that the content layout arrangement on a product detail page, when presented in an F-shape, informs the consumer that it is organized. If presented in a Z-shape, vivid information was recognized, and it was examined whether the product attitude and purchase intention were affected. As a result, when the content layout composition was presented as a layout arrangement in the form of a sense of unity and organization, prevention-focused consumers were positively affected by product attitudes and purchase intentions, and promotion-oriented consumers felt freedom. When presented in an arrangement, it was confirmed that the product attitude and purchase intention were affected.

• The Journal of the Korea institute of electronic communication sciences
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• v.17 no.4
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• pp.555-562
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• 2022

This study measured and analyzed the propagation characteristics at frequencies 6, 10, and 17 GHz to discover the new propagation demands in a semi-basement indoor corridor environment for meeting the 4th industrial revolution requirements. The measured indoor environment is a straight corridor consisting of three lecture rooms and glass windows on the outside. The measurement scenario development and measurement system were constructed to match this environment. The transmitting antenna was fixed, and the frequency domain and time domain propagation characteristics were measured and analyzed in the line-of-sight environment based on the distance of the receiving antenna location. In the frequency domain, reliability was determined by the parameters of the floating intercept (FI) path loss model and an R-squared value of 0.5 or more. In the time domain, the root mean square (RMS) delay spread and the cumulative probability of K-factor were used to determine that 6 GHz had high propagation power and 17 GHz had low propagation power. These research results will be effective in providing ultra-connection and ultra-delay artificial intelligence services for WIFI 6, 5G, and future systems in a semi-basement indoor corridor environment.

• Journal of Christian Education in Korea
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• v.70
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• pp.141-173
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• 2022

The purpose of this study is to illuminate depersonalization in the flow of technological revolution and to present a Christian SARAMDAUM education that aims for a new human image. It represents the Christian SARAMDAUM education that adapts to, mediates, and offers alternatives to the technological and human evolutionary flow of the machine age. The purpose of education for this purpose is to aim for 'Homo Creators', creative human beings presented as a new human image in the age of technological revolution. The educational goal is to nurture creative human beings through creative interpretation, creative integration between disciplines, and personal dialogue in the post-mechanical/ post-conventional paradigm. The content of the education is a conversation with the SARAMDAUM that consiliences the characteristics of post-machine and post-convention. The educational method utilizes Edu-Tech and AIED(Artificial Intelligence in Education) to realize systemic thinking and SARAMDAUM dialogue of technology. In addition, the composition of teachers and learners, educational environment and educational evaluation is presented. The significance of this study is that from the point of view of Christian education, the identity of human beings in the era of the technological revolution has been identified, and research on the creative image of the human being is newly attempted, and the direction of Christian SARAMDAUM education aimed at this is presented. This can be said to be a Christian education that emphasizes the essential characteristics of human beings while accommodating the era of technological revolution.

• The Journal of the Convergence on Culture Technology
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• v.8 no.5
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• pp.393-398
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• 2022

Megacities of the Repulic of Korea(ROK) will have increased by urbanization and the fourth industrial revolution. Mgacities are absolutely the opportunity factor to make human life enriched. Simultaneously, those are the challenge foctor considering the crucial conventional threat such as massive artillery and multiple rocket launcher from the North Korea. Israel that has faced the geopolitical situation of ROK developed the Multi-layer air defense system to offset the low altitude threat from the neighboring nations. As a result, Israel substantially removed plenty of Hamas' rockes and suicidal drones in 2021. Applying Israel's concept, North Korea's low altitude threat toward the ROK's megacities can effectively be eliminated. Furthermore, this Multi-layer air defense system can be a game-changer that gets rid of the low and high altitude threat from North Korea and neighboring nations with both hyperconnected sensor-C2-shooter and artificial intelligence. Through this approach, the ROK will be able to achieve the prosperity and prowth of nation at the center of Megacities concentrated on PMESII(Politics, Military, Economy, Society, Information, and Infrastructure) factors.

• Journal of the Korean Society of Marine Environment & Safety
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• v.28 no.5
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• pp.780-790
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• 2022

Quantitative risk levels must be presented by analyzing the causes and consequences of accidents and predicting the occurrence patterns of the accidents. For the analysis of marine accidents related to vessel traffic, research on the traffic such as collision risk analysis and navigational path finding has been mainly conducted. The analysis of the occurrence pattern of marine accidents has been presented according to the traditional statistical analysis. This study intends to present a marine accident prediction model using the statistics on marine accidents related to vessel traffic. Statistical data from 1998 to 2021, which can be accumulated by month and hourly data among the Korean domestic marine accidents, were converted into structured time series data. The predictive model was built using a long short-term memory network, which is a representative artificial intelligence model. As a result of verifying the performance of the proposed model through the validation data, the RMSEs were noted to be 52.5471 and 126.5893 in the initial neural network model, and as a result of the updated model with observed datasets, the RMSEs were improved to 31.3680 and 36.3967, respectively. Based on the proposed model, the occurrence pattern of marine accidents could be predicted by learning the features of various marine accidents. In further research, a quantitative presentation of the risk of marine accidents and the development of region-based hazard maps are required.

• Journal of Service Research and Studies
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• v.12 no.2
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• pp.80-93
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• 2022

This study is a study on a methodology that can extract various factors that affect purchase and use of products/services from the consumer's point of view through previous studies, and analyze the types and tendencies of consumers according to age and gender. To this end, we quantify factors in terms of general personal propensity, consumption influence, consumption decision, etc. to check the consistency of data, and based on these studies, we conduct research to suggest and prove data analysis methodologies of consumer types that are meaningful from the perspectives of startups and SMEs. did As a result, it was confirmed through cross-validation that there is a correlation between the three main factors assumed for data analysis from the consumer's point of view, the general tendency, the general consumption tendency, and the factors influencing the consumption decision. verified. This study presented a data analysis methodology and a framework for consumer data analysis from the consumer's point of view. In the current data analysis trend, where digital infrastructure develops exponentially and seeks ways to project individual preferences, this data analysis perspective can be a valid insight.

• Journal of the Korean Society of Marine Environment & Safety
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• v.28 no.7
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• pp.1120-1128
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• 2022

In the event of a marine accident, the longer the exposure time to the sea increases, the faster the chance of survival decreases. However, because the search area of the sea is extremely wide compared to that of land, marine object detection technology based on the sensor mounted on a satellite or an aircraft must be applied rather than ship for an efficient search. The purpose of this study was to rapidly detect an object in the ocean using a hyperspectral image sensor mounted on an aircraft. The image captured by this sensor has a spatial resolution of 8,241 × 1,024, and is a large-capacity data comprising 127 spectra and a resolution of 0.7 m per pixel. In this study, a marine object detection model was developed that combines a seawater identification algorithm using DBSCAN and a density-based land removal algorithm to rapidly analyze large data. When the developed detection model was applied to the hyperspectral image, the performance of analyzing a sea area of about 5 km² within 100 s was confirmed. In addition, to evaluate the detection accuracy of the developed model, hyperspectral images of the Mokpo, Gunsan, and Yeosu regions were taken using an aircraft. As a result, ships in the experimental image could be detected with an accuracy of 90 %. The technology developed in this study is expected to be utilized as important information to support the search and rescue activities of small ships and human life.