• Journal of the Korea Society of Computer and Information
• /
• v.24 no.1
• /
• pp.217-224
• /
• 2019

The intelligent robot industry is a complex which encompasses all fields of science and technology, and its marketability and industrial impact are remarkable. Major countries in the world have been strengthening their policies to foster the intelligent robot industry, but discussions on liability issues and legal actions that are accompanied by the related big or small accidents are still insufficient. In this study, therefore, the patent law by artificial intelligence robots and the legislation for relevant legal actions at the criminal law level are presented. Patent law legislation by artificial intelligence robots should comply with the followings. First, the electronic human being other than humans ought to be given legal personality, which is the subject of patent infringement. Even if artificial intelligence has legal personality, legal responsibility will be varied depending on the judgment of whether the accident has occurred due to the malfunction of the artificial intelligence itself or due to the human intervention with malicious intention. Second, artificial intelligence as a subject of actors and responsibility should be distinguished strictly; in other words, the injunction is the responsibility of the intelligent robot itself, but the financial repayment is the responsibility of the owner. In the criminal law legislation, regulations for legal punishment of intelligent robot manufacturing companies and manufacturers should be prepared promptly in case of legal violation, by amending the scope of application of Article 47 (Penal Provisions) of the Intelligent Robots Development and Distribution Promotion Act. In this way, joint penal provisions, which can clearly distinguish the responsibilities of the related parties, should be established to contribute to the development of the fourth industrial revolution.

• Proceedings of the Korean Society of Precision Engineering Conference
• /
• 2006.05a
• /
• pp.37-38
• /
• 2006

In this paper, power distribution module for car relay control with Control area network is developed. This module is called Intelligent power distribution module because it has microprossor which can communicate with other electric module such as ECU and Body control module and also has self-diagonasis function. The developed IPDM module is tested on vehicle and the good performance has been achieved.

• Proceedings of the Korea Society for Simulation Conference
• /
• 1998.03a
• /
• pp.101-105
• /
• 1998

A large system predictor, which can perform prediction of sales trend in a huge number of distribution centers, is presented using neural predictive model. There are 20,000 number of distribution centers, and each distribution center need to forecast future demand in order to establish a reasonable inventory policy. Therefore, the number of forecasting models corresponds to the number of distribution centers, which is not possible to estimate that kind of huge number of accurate models in ERP (Enterprise Resource Planning)module. Multilayer neural net as universal approximation is employed for fitting the prediction model. In order to improve prediction accuracy, a sequential simulation procedure is performed to get appropriate network structure and also to improve forecasting accuracy. The proposed simulation procedure includes neural structure identification and virtual predictive model generation. The predictive model generation consists of generating virtual signals and estimating predictive model. The virtual predictive model plays a key role in tuning the real model by absorbing the real model errors. The complement approach, based on real and virtual model, could forecast the future demands of various distribution centers.

• The Transactions of The Korean Institute of Electrical Engineers
• /
• v.60 no.4
• /
• pp.687-693
• /
• 2011

In this paper, problems and solutions are proposed for applying IEC 61850 to Distribution Automation System(DAS). Communication protocol integration in power automation system have issued by IEC standards, IEC 61850 of them has researched for applying IEC 61850 to many areas of power system in spite of that it was made for substation automation system. Especially, DAS is just about to apply IEC 61850 by communication network change from serial to ethernet although DNP 3.0 is used. But it's impossible to apply directly IEC 61850 to DAS by difference of environment which unfixed wide area and separated nodes in power distribution system unlike concept of IEC 61850 is made by Substation Automation System(SAS) environment of limited space. Thus, this paper proposed applications of three types which conceptual, practical, and future to consider problems and solutions when apply IEC 61850 to Ethernet based DAS.

• Journal of the Korean Society of Safety
• /
• v.36 no.2
• /
• pp.32-38
• /
• 2021

This paper suggests an approach to evaluate the reliability of an intelligent power module with information deficiency of prior distribution and the characteristics of censored data through Bayesian statistics. This approach used a prior distribution of Bayesian statistics using the lifetime information provided by the manufacturer and compared and evaluated diffuse prior (vague prior) distributions. To overcome the computational complexity of Bayesian posterior distribution, it was computed with Gibbs sampling in the Monte Carlo simulation method. As a result, the standard deviation of the prior distribution developed using simple information was smaller than that of the posterior distribution calculated with the diffuse prior. In addition, it showed excellent error characteristics on RMSE compared with the Kaplan-Meier method.

• Proceedings of the IEEK Conference
• /
• 1998.06a
• /
• pp.46-49
• /
• 1998

In this paper, we introduce the notion of intelligent communication by introducing a novel intelligent receiver model. This receiver is continually evolving and learns and improves in performance as it compiles its experience over time. In digital communication context, in a typical training mode, it jearns the concept of "1" as is deteriorated by arbitrary (not necessarily additive as is typically assumed) disturbance and /or modulation. After learning "1", in test mode, it classifies the received signal "1" and "0" almost completely. The intelligent receiver as implemented is grounded on the recently introduced Stochastic Morphological Sampling Theorem(SMST), a distribution-free result which gives theoretical bounds on the sample complexity(training size) needed for the required performance parameters such as accuracy($\varepsilon$) and confidence($\delta$). Based on this theorem, we demonstrate --almost irrespective of channel and modulation model-- the number of samples needed to learn the concept of "1" is not too "large" and the resulting universal receiver structure, that corresponding to classical Nearest Neighbor rule in Pattern Recognition Theory, is trivial. We check the surprising efficiency and validity of this model through some simple simulations. and validity of this model through some simple simulations.

• The Transactions of the Korean Institute of Electrical Engineers A
• /
• v.55 no.9
• /
• pp.351-358
• /
• 2006

In this paper, DSPOCS(Digital Switchgear-Panel Operation and Control Solution) is designed, which is the intelligent inference based operation and control solution to obtain the safety and reliability of electric power supply in substation based on IED. DSPOCS is designed as a scheduled monitoring and control task and a real-time alarm inference task, and is interlinked with BRES(Bus Reconfiguration Expert System) in the required case. The intelligent alarm inference task consists of the alarm knowledge generation part and the real-time pattern matching part. The alarm knowledge generation part generates automatically alarm knowledge from DB saves it in alarm knowledge base. On the other hand, the pattern matching part inferences the real-time event by comparing the real-time event information furnished from IEDs of substation with the patterns of the saved alarm knowledge base.; Especially, alarm knowledge base includes the knowledge patterns related with fault alarm, the overload alarm and the diagnosis alarm. In order to design the database independently in substation structure, busbar is represented as a connectivity node which makes the more generalized graph theory possible. Finally, DSPOCS is implemented in MS Visual $C^{++}$, MFC, the effectiveness and accuracy of the design is verified by simulation study to the typical distribution substation.

• ETRI Journal
• /
• v.44 no.2
• /
• pp.183-193
• /
• 2022

Smart cities are expected to provide residents with convenience via various agents such as CCTV, delivery robots, security robots, and unmanned shuttles. Environmental data collected by various agents can be used for various purposes, including advertising and security monitoring. This study suggests a surveillance map data framework for efficient and integrated multimodal data representation from multi-agents. The suggested surveillance map is a multilayered global information grid, which is integrated from the multimodal data of each agent. To confirm this, we collected surveillance map data for 4 months, and the behavior patterns of humans and vehicles, distribution changes of elevation, and temperature were analyzed. Moreover, we represent an anomaly detection algorithm based on a surveillance map for security service. A two-stage anomaly detection algorithm for unusual situations was developed. With this, abnormal situations such as unusual crowds and pedestrians, vehicle movement, unusual objects, and temperature change were detected. Because the surveillance map enables efficient and integrated processing of large multimodal data from a multi-agent, the suggested data framework can be used for various applications in the smart city.

• Journal of Korea Society of Digital Industry and Information Management
• /
• v.15 no.4
• /
• pp.19-29
• /
• 2019

Recently, with the rise of environmental issues and the change of government policy (Renewable Energy 3020 Implementation Plan), a large amount of renewable energy such as solar and wind power is connected to the power system, and most of the renewable energy is concentrated in the power distribution network. This causes many problems with the voltage management and the protection coordination of the grid due to the its intermittent power generation. In order to effectively operate the distribution network, it is necessary to deploy more intelligent terminal devices in the field to measure the status of the distribution network and develop various operation functions such as visualization and big data analysis to support the power distribution system operators. In addition, the failover technology must be supported for the non-stop operation of the power distribution system. This paper proposes the system architecture of new power distribution management system to cope with high penetration of renewable energy. To verify the proposed system architecture, the functional unit test and performance measurement were performed.

• Journal of the Korean Institute of Intelligent Systems
• /
• v.19 no.4
• /
• pp.457-463
• /
• 2009

In this paper, a novel foot force distribution algorithm for hexapod walking robots is presented. The considered hexapod robot has fault-tolerant tripod gaits with a failed leg in locked-joint failure. The principle of the proposed algorithm is to minimize the slippage of the leg that determines the stability margin of the fault-tolerant gaits. The fault-tolerant tripod gait has a drawback that it has less stability margin than normal gaits. Considering this drawback, we use the feature that there are always three supporting legs, and by incorporating the theory of Zero-Interaction Force, we calculate the foot forces analytically without resort to any optimization technique. In a case study, the proposed algorithm is compared with a conventional foot force distribution method and its applicability is demonstrated.