• Journal of KIBIM
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• v.11 no.2
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• pp.54-59
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• 2021

In the process of designing a building, the process of expressing the designer's ideas through images is essential. However, it is expensive and time consuming for a designer to analyze every individual case image to generate a hypothetical design. This study aims to visualize the basic design draft sketch made by the designer as a real image using the Generative Adversarial Network (GAN) based on the continuously accumulated architectural case images. Through this, we proposed a method to build an automated visualization environment using artificial intelligence and to visualize the architectural idea conceived by the designer in the architectural planning stage faster and cheaper than in the past. This study was conducted using approximately 20,000 images. In our study, the GAN algorithm allowed us to represent primary materials and shades within 2 seconds, but lacked accuracy in material and shading representation. We plan to add image data in the future to address this in a follow-up study.

• Journal of Multimedia Information System
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• v.9 no.1
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• pp.11-20
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• 2022

In this paper, we have recently created self-driving cars and self-parking systems in human-friendly cars that can provide high safety and high convenience functions by recognizing the internal and external situations of automobiles in real time by incorporating next-generation electronics, information communication, and function control technologies. And with the development of connected cars, the ITS (Intelligent Transportation Systems) market is expected to grow rapidly. Intelligent Transportation System (ITS) is an intelligent transportation system that incorporates technologies such as electronics, information, communication, and control into the transportation system, and aims to implement a next-generation transportation system suitable for the information society. By combining the technologies of connected cars and Internet of Things with software features and operating systems, future cars will serve as a service platform to connect the surrounding infrastructure on their own. This study creates a research methodology based on the Enhanced Security Model in Self-Driving Cars model. As for the types of attacks, Availability Attack, Man in the Middle Attack, Imperial Password Use, and Use Inclusive Access Control attack defense methodology are used. Along with the commercialization of 5G, various service models using advanced technologies such as autonomous vehicles, traffic information sharing systems using IoT, and AI-based mobility services are also appearing, and the growth of smart transportation is accelerating. Therefore, research was conducted to defend against hacking based on vulnerabilities of smart cars based on artificial intelligence blockchain.

• Journal of Information Technology Services
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• v.20 no.6
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• pp.125-139
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• 2021

To explore college students' course satisfaction over the course of the semester during which a full-scale digital transformation was in progress due to COVID-19 pandemic, this study analyzed student survey data from a university located in the metropolitan area. To minimize the respondents' burden to answer long list of detailed questions in repetition, the study utilized a pulse survey method and students were asked to answer a brief and regular set of online questions 5 times throughout the semester. The number of survey respondents ranged from 1,640 to 4,116, with an average of more than 3,700. The main results and implications of this study are summarized as follows. First, the survey data indicated that the overall student satisfaction with online courses was above average (3.46/5). Vast majority of students have chosen pre-recorded, contents-based course over real-time, video-based course as their preferred course delivery method and this tendency remained the same throughout the semester. Second, the results of keyword network analysis of open-ended questions indicated that technical issues, increased workload (e.g., course assignments and course attendance) were main causes of online course dissatisfaction. And students suggested an unified online course platform and more interactive course design to further improve online courses in the future.

• Journal of Drive and Control
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• v.19 no.4
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• pp.29-35
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• 2022

In this paper, we developed a workload index for monitoring the durability test using operation information of an excavator. First, the acceleration and cylinder pressure were selected as load factors by analyzing operation data. Through load correlation analysis according to each load factor, Root Mean Square (RMS) and Work Load Range (WLR) were respectively derived as a load feature representing mechanical load. In addition, the workload index was used to quantify load features. For applying the workload index to monitoring, a real-time monitoring system consisting of sensors and embedded controller was installed on the excavator and the system was integrated with a remote monitoring environment using a wireless network. Results of load monitoring and analysis verified that the developed workload index was effective from the viewpoint of the relative comparison of the workload.

• Journal of Korea Multimedia Society
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• v.25 no.1
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• pp.39-51
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• 2022

Image-based gender classification and age estimation of human are classic problems in computer vision. Most of researches in this field focus just only one task of either gender classification or age estimation and most of the reported methods for each task focus on accuracy performance and are not computationally light. Thus, running both tasks together simultaneously on low cost mobile or embedded systems with limited cpu processing speed and memory capacity are practically prohibited. In this paper, we propose a novel light-weight gender classification and age estimation method based on ensemble multitasking deep learning with light-weight processing neural network architecture, which processes both gender classification and age estimation simultaneously and in real-time even for embedded systems. Through experiments over various well-known datasets, it is shown that the proposed method performs comparably to the state-of-the-art gender classification and/or age estimation methods with respect to accuracy and runs fast enough (average 14fps) on a Jestson Nano embedded board.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.32 no.2
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• pp.193-200
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• 2022

Unknown cryptographic communication protocols may have advantage of guaranteeing personal and data privacy, but when used for malicious purposes, it is almost impossible to identify and respond to using existing network security equipment. In particular, there is a limit to manually analyzing a huge amount of traffic in real time. Therefore, in this paper, we attempt to identify packets of unknown cryptographic communication protocols and separate fields comprising a packet by using machine learning techniques. Using sequential patterns analysis, hierarchical clustering, and Pearson's correlation coefficient, we found that the structure of packets can be automatically analyzed even for an unknown cryptographic communication protocol.

• Journal of Fashion Business
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• v.26 no.5
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• pp.76-90
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• 2022

The rapid growth and influence of digital technologies have had a profound effect on modern society. Companies and businesses can connect through SNS(social network service accounts). The importance of mass media empowers the creation of virtual images that are more realistic than time and space. Unlike traditional reproduction or imitation, the virtual images created in this way are reproduced in a form that lacks the original inspiration's essence. Jean Baudrillard described this phenomenon as the theory of simulation. Baudrillard argued that imitated simulated images replace reality. He stated that reality is lost under excessive images in modern society. In response, based on an understanding of the theory of hyper-reality that emerged through the late stages of the order of simulacre, this study aimed to analyze modern fashion's method of reproducing hyper-real images and investigate the method's characteristics. This study examined the characteristics of hyper-reality described by Baudrillard and analyzed the method of artistic expression of hyper-reality. Based on this method of expression, reproducibility, following the stages of image simulation, was derived. A specific case applied to fashion was analyzed, and based on the image reproduction method, specific characteristics of hyper-reality characteristics in fashion were obtained. Sixty-four collections were selected, out of which 155 images and 43 brands demonstrated the principles of image transformation.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.15 no.11
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• pp.3875-3891
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• 2021

In this study, a Velostat pressure sensor was manufactured to develop a plantar pressure measurement system and a C#-based application was developed to monitor and collect plantar pressure data in real time. In order to evaluate the characteristics of the proposed plantar pressure measurement system, the accuracy of plantar pressure index and personal classification was verified by comparing with MatScan, a commercial plantar pressure measurement system. As a result, the output characteristics according to the weight of the Velostat pressure sensor were evaluated and a trend line with the reliability of r² = 0.98 was detected. The Root Mean Square Error(RMSE) of the weighted area was 11.315 cm², the RMSE of the x coordinate of Center of Pressure(CoP_x) was 1.036 cm and the RMSE of the y coordinate of Center of Pressure(CoP_y) was 0.936 cm. Finally, inaccuracy of personal classification, the proposed system was 99.47% and MatScan was 96.86%. Based on the advantage of being simple to implement and capable of manufacturing at low cost, it is considered that it can be applied to various fields of measuring vital signs such as sitting posture and breathing in addition to the plantar pressure measurement system.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.16 no.11
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• pp.3761-3779
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• 2022

The performance of existing recognition algorithms for binary phase shift keying (BPSK) and quadrature phase shift keying (QPSK) signals degrade under conditions of low signal-to-noise ratios (SNR). Hence, a novel recognition algorithm based on features in the graph domain is proposed in this study. First, the power spectrum of the squared candidate signal is truncated by a rectangular window. Thereafter, the graph representation of the truncated spectrum is obtained via normalization, quantization, and edge construction. Based on the analysis of the connectivity difference of the graphs under different hypotheses, the sum of degree (SD) of the graphs is utilized as a discriminate feature to classify BPSK and QPSK signals. Moreover, we prove that the SD is a Schur-concave function with respect to the probability vector of the vertices (PVV). Extensive simulations confirm the effectiveness of the proposed algorithm, and its superiority to the listed model-driven-based (MDB) algorithms in terms of recognition performance under low SNRs and computational complexity. As it is confirmed that the proposed method reduces the computational complexity of existing graph-based algorithms, it can be applied in modulation recognition of radar or communication signals in real-time processing, and does not require any prior knowledge about the training sets, channel coefficients, or noise power.

• Current Optics and Photonics
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• v.6 no.2
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• pp.137-142
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• 2022

Leak detection is one of the most important challenges in condition monitoring of water pipelines. Fiber Bragg grating (FBG) sensors offer an attractive technique to detect leak signals. In this paper, leak measurements were conducted on a water distribution pilot plant with a length of 270 m and a diameter of 100 mm. FBG sensors were installed on the pipeline surface and used to detect leak vibration signals. The leak was demonstrated with 1-, 2-, 3-, and 4-mm diameter leak holes in four different pipe types. The frequency response of leak signals was analyzed by fast Fourier transform analysis in real time. In the experiment, the frequency range of leak signals was approximately 340-440 Hz. The frequency shifts of leak signals according to the pipe type and the size of the leak hole were demonstrated at a pressure of 1.8 bar and a flow rate of 25.51 m³/h. Results show that frequency shifts detected by FBG sensors can be used to detect leaks in pipelines.