• Journal of Intelligence and Information Systems
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• v.22 no.1
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• pp.107-118
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• 2016

The advent of 5G mobile communications, which is expected in 2020, will provide many services such as Internet of Things (IoT) and vehicle-to-infra/vehicle/nomadic (V2X) communication. There are many requirements to realizing these services: reduced latency, high data rate and reliability, and real-time service. In particular, a high level of reliability and delay sensitivity with an increased data rate are very important for M2M, IoT, and Factory 4.0. Around the world, 5G standardization organizations have considered these services and grouped them to finally derive the technical requirements and service scenarios. The first scenario is broadcast services that use a high data rate for multiple cases of sporting events or emergencies. The second scenario is as support for e-Health, car reliability, etc.; the third scenario is related to VR games with delay sensitivity and real-time techniques. Recently, these groups have been forming agreements on the requirements for such scenarios and the target level. Various techniques are being studied to satisfy such requirements and are being discussed in the context of software-defined networking (SDN) as the next-generation network architecture. SDN is being used to standardize ONF and basically refers to a structure that separates signals for the control plane from the packets for the data plane. One of the best examples for low latency and high reliability is an intelligent traffic system (ITS) using V2X. Because a car passes a small cell of the 5G network very rapidly, the messages to be delivered in the event of an emergency have to be transported in a very short time. This is a typical example requiring high delay sensitivity. 5G has to support a high reliability and delay sensitivity requirements for V2X in the field of traffic control. For these reasons, V2X is a major application of critical delay. V2X (vehicle-to-infra/vehicle/nomadic) represents all types of communication methods applicable to road and vehicles. It refers to a connected or networked vehicle. V2X can be divided into three kinds of communications. First is the communication between a vehicle and infrastructure (vehicle-to-infrastructure; V2I). Second is the communication between a vehicle and another vehicle (vehicle-to-vehicle; V2V). Third is the communication between a vehicle and mobile equipment (vehicle-to-nomadic devices; V2N). This will be added in the future in various fields. Because the SDN structure is under consideration as the next-generation network architecture, the SDN architecture is significant. However, the centralized architecture of SDN can be considered as an unfavorable structure for delay-sensitive services because a centralized architecture is needed to communicate with many nodes and provide processing power. Therefore, in the case of emergency V2X communications, delay-related control functions require a tree supporting structure. For such a scenario, the architecture of the network processing the vehicle information is a major variable affecting delay. Because it is difficult to meet the desired level of delay sensitivity with a typical fully centralized SDN structure, research on the optimal size of an SDN for processing information is needed. This study examined the SDN architecture considering the V2X emergency delay requirements of a 5G network in the worst-case scenario and performed a system-level simulation on the speed of the car, radius, and cell tier to derive a range of cells for information transfer in SDN network. In the simulation, because 5G provides a sufficiently high data rate, the information for neighboring vehicle support to the car was assumed to be without errors. Furthermore, the 5G small cell was assumed to have a cell radius of 50-100 m, and the maximum speed of the vehicle was considered to be 30-200 km/h in order to examine the network architecture to minimize the delay.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.28 no.5D
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• pp.597-607
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• 2008

ATIS(Advanced Traffic Information System) provide valuable information as the travel time and traffic congestion, detour, traffic accident information to drivers, so it is being in the spotlight. But so far, the study on the consumer satisfaction with providing traffic information is incomplete. So, this study run a Canonical discriminant analysis and a Canonical correlation analysis by a QuantificationIItheory based on a Traffic Information Satisfaction image data through questionnaires, and found out the factors with influence on the consumer satisfaction. And this study definitely found out the correlation between consumer's recognition and traffic information satisfaction through understanding the change on the recognition about traffic information satisfaction by a QuantificationItheory. Finally, this study found out the change on the sensibility recognition of drivers by running the principal component anlysis, developed the traffic information satisfaction evaluation model considering the change on the recognition by using the structural equation model.

• Korean Journal of Construction Engineering and Management
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• v.25 no.1
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• pp.23-31
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• 2024

This study highlights the importance of understanding the fair bidding behavior of bid practitioners in order to eliminate bid-rigging, which has a detrimental impact on the construction industry and the overall economy. The research collected survey data from bid practitioners in the Daegu and Gyeongbuk regions of South Korea and analyzed the causal relationships between attitudes towards bid-rigging, subjective norms, perceived behavioral control, and the intention to engage in fair bidding using PLS-SEM analysis. The analysis results confirm that attitudes towards bid-rigging and perceived behavioral control are significant variables predicting the intention to engage in fair bidding among bid practitioners. This indicates that bid practitioners' perceptions of bid-rigging and personal behavioral control influence their willingness and actions towards fair bidding. The insights gained from this research provide valuable insights into bid practitioners' behavioral changes and can aid in the development of policies and measures to promote fair bidding and prevent bid-rigging.

• Proceedings of the Korea Water Resources Association Conference
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• 2017.05a
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• pp.264-264
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• 2017

국외의 상수도 원격검침 시스템 내 데이터 전송방식은 도시 규모, 계량기의 밀도, 전력공급 여부 및 통신망의 설치 여부 등을 종합적으로 고려하여 결정되었다. 대부분의 스마트워터미터 제조업체들은 계량기의 부호기가 공급하는 판독 내용(데이터)을 전송할 검침단말기와 근거리 통신망(neighborhood area network)을 연계하여 개발 및 판매하였으며, 자체 소유 통신 프로토콜을 사용하여 라디오 주파수(RF) 통신 기술을 사용하고 있다. 광역통신망(wide area network)의 경우, 노드(말단의 계량기 및 센서)들과 이에 연결된 통신망 들을 포함한 네트웍의 배열이나 구성이 스타(star), 메쉬(mesh), 버스(bus), 나무(tree) 등의 형태로 통신망이 구성되어 있으나, 스타와 메쉬형 통신망 구성형태가 가장 널리 활용되는 것으로 조사되었다. 시스템 통합운영관리 업체들인 IBM, Oracle, Itron 등은 용수 인프라 관리 또는 통합네트워크 솔루션 등의 통합 물관리 시스템(integrated water management system)을 개발하여 현장적용을 하고 있으며, 원격검침 시스템을 통해 고객들의 현재 소비량과 과거 누적 소비량, 누수 감지 서비스 및 실시간 요금 고지 등을 실시간으로 웹 포털과 앱을 통해 제공하고 있다. 또한, 일부 제조업체들은 도시 용수공급/소비 관리자가 주민의 용수사용량을 모니터링하여 일평균 용수사용량 및 사용 경향을 파악하고, 누수를 검지하여 복구 및 용수 사용 지속가능성 지수를 제시하고, 실시간으로 주민의 용수사용량 관련 데이터를 모니터링하여 용수공급의 최적화를 위한 의사결정지원 서비스를 용수공급자에게 제공하고 있다. 최근에는 인공지능을 활용해 가정용수의 용도별(세탁용수, 화장실용수, 샤워용수, 식기세척용수 등) 사용량 곡선을 패터닝하여 profiling 기법을 도입해, 스마트워터미터에서 용수사용량이 통합되어 검지될 시 용수사용량의 세부 용도별 re-profiling 기법을 도입하여 가정용수내 과소비되는 지점을 도출 후 절감을 유도하는 기술이 개발 중이다. 또한, 미래 용수 사용량 예측을 위해 다양한 시계열 자료를 분석하는 선형 종속 모형(자기회귀모형, 자기회귀이동평균모형, 자기회귀적분이동평균모형 등)과 비선형 종속 모형(Fuzzy Logic, Neural Network, Genetic Algorithm 등)을 활용한 예측기능이 구축되어 상호 비교하여 최적의 용수사용량 예측 도구를 제공되고 있다.

• Journal of the Korean Society of Radiology
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• v.16 no.6
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• pp.687-695
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• 2022

To find a 3D printer material that can replace lead used as a shield for high-energy electron beam treatment, the shielding composites were simulated by using MCNP6 programs. The Percent Depth Dose (PDD), Flatness, and Symmetry of linear accelerators emitting high-energy electron beams were measured, and the linear accelerator was compared with MCNP6 after simulation, confirming that the source term between the actual measurement and simulation was consistent. By simulating the lead shield, the appropriate thickness of the lead shield capable of shielding 95% or more of the absorbed dose was selected. Based on the absorption dose data for lead shield with a thickness of 3 mm, the shielding performance was analyzed by simulating 1, 5, 10, and 15 mm thicknesses of ABS+W (10%), ABS+Bi (10%), and PLA+Fe (10%). Each prototype was manufactured with a 3D printer, measured and analyzed under the same conditions as in the simulation, and found that when ABS+W (10%) material was formed to have a thickness of at least 10mm, it had a shielding performance that could replace lead with a thickness of 3mm. The surface morphology and atomic composition of the ABS+W (10%) material were evaluated using a scanning electron microscope (SEM) and an energy dispersive X-ray spectrometer (EDS). From these results, it was confirmed that replacing the commercialized lead shield with ABS+W (10%) material not only produces a shielding effect such as lead, but also can be customized to patients using a 3D printer, which can be very useful for high-energy electron beam treatment.

• 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.

• Journal of Intelligence and Information Systems
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• v.18 no.1
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• pp.39-57
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• 2012

Recently, due to the introduction of high-tech equipment in interactive exhibits, many people's attention has been concentrated on Interactive exhibits that can double the exhibition effect through the interaction with the audience. In addition, it is also possible to measure a variety of audience reaction in the interactive exhibition. Among various audience reactions, this research uses the change of the facial features that can be collected in an interactive exhibition space. This research develops an artificial neural network-based prediction model to predict the response of the audience by measuring the change of the facial features when the audience is given stimulation from the non-excited state. To present the emotion state of the audience, this research uses a Valence-Arousal model. So, this research suggests an overall framework composed of the following six steps. The first step is a step of collecting data for modeling. The data was collected from people participated in the 2012 Seoul DMC Culture Open, and the collected data was used for the experiments. The second step extracts 64 facial features from the collected data and compensates the facial feature values. The third step generates independent and dependent variables of an artificial neural network model. The fourth step extracts the independent variable that affects the dependent variable using the statistical technique. The fifth step builds an artificial neural network model and performs a learning process using train set and test set. Finally the last sixth step is to validate the prediction performance of artificial neural network model using the validation data set. The proposed model is compared with statistical predictive model to see whether it had better performance or not. As a result, although the data set in this experiment had much noise, the proposed model showed better results when the model was compared with multiple regression analysis model. If the prediction model of audience reaction was used in the real exhibition, it will be able to provide countermeasures and services appropriate to the audience's reaction viewing the exhibits. Specifically, if the arousal of audience about Exhibits is low, Action to increase arousal of the audience will be taken. For instance, we recommend the audience another preferred contents or using a light or sound to focus on these exhibits. In other words, when planning future exhibitions, planning the exhibition to satisfy various audience preferences would be possible. And it is expected to foster a personalized environment to concentrate on the exhibits. But, the proposed model in this research still shows the low prediction accuracy. The cause is in some parts as follows : First, the data covers diverse visitors of real exhibitions, so it was difficult to control the optimized experimental environment. So, the collected data has much noise, and it would results a lower accuracy. In further research, the data collection will be conducted in a more optimized experimental environment. The further research to increase the accuracy of the predictions of the model will be conducted. Second, using changes of facial expression only is thought to be not enough to extract audience emotions. If facial expression is combined with other responses, such as the sound, audience behavior, it would result a better result.

• The Journal of the Korea Contents Association
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• v.20 no.11
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• pp.656-668
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• 2020

The Sejong City was launched in July 2012 and was initially focused on the relocation of central administrative agencies, but it has been changing from an administrative city to a fourth industrial city since 2019 to a smart city and the implementation of Korea's New Deal in 2020. Identity design needs to be reevaluated accordingly. In particular, the web environment is also calling for an optimized identity design due to rapid changes in information technology such as various wearables and the Internet of Things. As the number of responsive web sites where information and communication technologies can be developed and optimized screens can be viewed increased, identity was intuitively communicated to users and designs were applied to make them more distinct and empathetic to other cities. Prior to the study, we looked at prior studies on the changing times in the web environment and the reactive web, and analyzed the identity design of the reactive web and applied minimalism characteristics step by step. Based on this, we surveyed experts and non-experts on the proposed survey by applying minimalist characteristics (simple, repeatability, and spatiality) of reactive identity and found that it was easily and intuitively recognizable in a small web environment such as mobile. Therefore, we hope that Sejong City's identity will continue to be studied in various ways and efficient management so that identity can be established in accordance with the changes of the times.

• Informatization Policy
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• v.31 no.3
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• pp.3-33
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• 2024

This paper summarizes the legal problems and issues raised in relation to generative AI. In addition, we looked at what regulatory discussions individual countries or international organizations have in order to solve or respond to these issues or to minimize the risks posed by generative AI. Infringement of individual basic rights raised by generative AI, the emergence and control of new crimes, monopolization of specific markets and environmental issues are mainly discussed, and although there are some differences in the necessity and direction of regulation, most countries seem to have similar views. Regarding AI, the issues that are currently being raised have been discussed continuously from the beginning of its appearance. Although certain issues have been discussed relatively much, there are some differences between countries, and situations that require consideration of phenomena different from the past are emerging. It seems that regulations and policies are being refined according to the situation of individual countries. In a situation where various issues are rapidly emerging and changing, measures to minimize the risk of AI and to enjoy the utility and benefits of AI through the use of safe AI should be sought. It will be necessary to continuously identify and analyze international trends and reorganize AI-related regulations and detailed policies suitable for Korea.

• Journal of Korea Society of Industrial Information Systems
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• v.16 no.4
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• pp.87-98
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• 2011

Detecting a moving object from videos and tracking it are basic and necessary preprocessing steps in many video systems like object recognition, context aware, and intelligent visual surveillance. In this paper, we propose a method that is able to detect a moving object quickly and accurately in a condition that background and light change in a real time. Furthermore, our system detects strongly an object in a condition that the target object is covered with other objects. For effective detection, effective Eigen-space and FCM are combined and employed, and a CONDENSATION algorithm is used to trace a detected object strongly. First, training data collected from a background image are linear-transformed using Principal Component Analysis (PCA). Second, an Eigen-background is organized from selected principal components having excellent discrimination ability on an object and a background. Next, an object is detected with FCM that uses a convolution result of the Eigen-vector of previous steps and the input image. Finally, an object is tracked by using coordinates of an detected object as an input value of condensation algorithm. Images including various moving objects in a same time are collected and used as training data to realize our system that is able to be adapted to change of light and background in a fixed camera. The result of test shows that the proposed method detects an object strongly in a condition having a change of light and a background, and partial movement of an object.