• Journal of Digital Convergence
• /
• v.15 no.6
• /
• pp.51-59
• /
• 2017

The role of government is to defend its lands and people from enemies. The range of that defense has now extended into the cyber domain, regarded as the fourth domain of the conventional defense domains (i.e., land, sea, sky, and universe). Traditionally, a government's intelligence power overrides that of its civilians, and government is exclusively responsible for defense. However, it is difficult for government to take the initiative to defend in the cyber domain because civilians already have a greater means for collecting information, which is known as being "intelligence inverse" in the cyber domain. To this end, we first define the intelligence inverse phenomenon and then analyze its main features. Then we investigate foreign countries' efforts to overcome the phenomenon and look at the current domestic situation. Based on these results, we describe the appropriate role of the National Intelligence Agency to handle cyber threats and offer a cyber threat intelligence model to share with civilians to help protect against these threats. Using the proposed model, we propose that the National Intelligence Agency should establish a base system that will respond to cyber threats more effectively.

• Journal of Korean Society of Industrial and Systems Engineering
• /
• v.45 no.2
• /
• pp.12-19
• /
• 2022

Artificial intelligence is driving the Fourth Industrial Revolution and is in the spotlight as a general-purpose technology. As the data collection from the battlefield increases rapidly, the need to us artificial intelligence is increasing in the military, but it is still in its early stages. In order to identify maritime targets, Republic of Korea navy acquires images by ISAR(Inverse Synthetic Aperture Radar) of maritime patrol aircraft, and humans make out them. The radar image is displayed by synthesizing signals reflected from the target after radiating radar waves. In addition, day/night and all-weather observations are possible. In this study, an artificial intelligence is used to identify maritime targets based on radar images. Data of radar images of 24 maritime targets in Republic of Korea and North Korea acquired by ISAR were pre-processed, and an artificial intelligence algorithm(ResNet-50) was applied. The accuracy of maritime targets identification showed about 99%. Out of the 81 warship types, 75 types took less than 5 seconds, and 6 types took 15 to 163 seconds.

• Journal of Intelligence and Information Systems
• /
• v.9 no.1
• /
• pp.195-209
• /
• 2003

Making traditional plan of target marketing based on association rule has brought restriction to obtain the target of marketing. This paper is to present inverse association rule as a new association rule for target marketing. Inverse association rule does not use information about relation between items that customers purchase, but use information about relation between items that customers do not purchase. By adding inverse association rule to target marketing, we generate new marketing strategy to look for new target of marketing. There are three steps to apply the marketing strategy proposed by this Paper to target marketing. Firstly, a database is converted to an inverse database. Although inverse association rules can be generated from a database, it is easier to explain inverse association rule in an inverse database than in a database. Secondly, association rules and inverse association rules are generated from inverse database. Finally, two types of rules which are created in the previous steps are applied to target marketing. From new marketing rule, this paper is to show direct marketing about target item and indirect marketing about another item associated with target item to sell target item. The reason is that sales of the item associated with target item have an influence on sales of target item.

• Journal of the Korean Society of Manufacturing Technology Engineers
• /
• v.25 no.6
• /
• pp.504-510
• /
• 2016

Robots are widely utilized in many fields, and various demands need customized robots. This study proposes an optimal design method based on swarm intelligence for selecting the kinematic parameter of a manipulator according to the task space trajectory desired by the user. The optimal design method is dealt with herein as an optimization problem. This study is based on swarm intelligence-based optimization algorithms (i.e., ant colony optimization (ACO) and particle swarm optimization algorithms) to determine the optimal kinematic parameters of the manipulator. The former is used to select the optimal kinematic parameter values, whereas the latter is utilized to solve the inverse kinematic problem when the ACO determines the parameter values. This study solves a design problem with the PUMA 560 when the desired task space trajectory is given and discusses its results in the simulation part to verify the performance of the proposed design.

• The Journal of the Institute of Internet, Broadcasting and Communication
• /
• v.14 no.1
• /
• pp.211-217
• /
• 2014

The smart revolution led by Smart Phone in our daily lives is changing the paradigm in general. These smart revolution has provided us a lot of convenience, but on the other hand also appearing an inverse function. The host of the future of young people, especially by the excessive use of smart devices, there is a risk of side effects increased. In this study, the empirical analysis has been done to know how the used time of smart devices and youth sports activities affect to the emotional intelligence. Using regression analysis, the used time of smart devices showed negative relationship and the time of youth sports activities affected positively with the emotional intelligence. Additional analysis of the amount of reading also affected positively to the motional intelligence as a conclusion. Through this study, as a conclusion, traditional activities, namely sports activities and reading to help the youth developing emotional intelligence, while the use of smart devices inhibits the development of emotional intelligence of youth.

• Journal of Mechanical Science and Technology
• /
• v.17 no.4
• /
• pp.528-537
• /
• 2003

This paper proposes a 3-PPR planar parallel manipulator, which consists of three active prismatic Joints, three passive prismatic joints, and three passive rotational joints. The analysis of the kinematics and the optimal design of the manipulator are also discussed. The proposed manipulator has the advantages of the closed type of direct kinematics and a void-free workspace with a convex type of borderline. For the kinematic analysis of the proposed manipulator, the direct kinematics, the inverse kinematics, and the inverse Jacobian of the manipulator are derived. After the rotational limits and the workspaces of the manipulator are investigated, the workspace of the manipulator is simulated. In addition, for the optimal design of the manipulator, the performance indices of the manipulator are investigated, and then an optimal design procedure Is carried out using Min-Max theory. Finally. one example using the optimal design is presented.

• Structural Engineering and Mechanics
• /
• v.28 no.2
• /
• pp.153-166
• /
• 2008

This paper suggests the use of wavelet multiresolution analysis (WMRA) and neural network for generation of artificial earthquake accelerograms from target spectrum. This procedure uses the learning capabilities of radial basis function (RBF) neural network to expand the knowledge of the inverse mapping from response spectrum to earthquake accelerogram. In the first step, WMRA is used to decompose earthquake accelerograms to several levels that each level covers a special range of frequencies, and then for every level a RBF neural network is trained to learn to relate the response spectrum to wavelet coefficients. Finally the generated accelerogram using inverse discrete wavelet transform is obtained. An example is presented to demonstrate the effectiveness of the method.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.15 no.10
• /
• pp.3482-3497
• /
• 2021

Artificial intelligence has emerged as the core of the 4th industrial revolution, and large amounts of data processing, such as big data technology and rapid data analysis, are inevitable. The most fundamental and universal data interpretation technique is an analysis of information through regression, which is also the basis of machine learning. Ridge regression is a technique of regression that decreases sensitivity to unique or outlier information. The time-consuming calculation portion of the matrix computation, however, basically includes the introduction of an inverse matrix. As the size of the matrix expands, the matrix solution method becomes a major challenge. In this paper, a new algorithm is introduced to enhance the speed of ridge regression estimator calculation through series expansion and computation recycle without adopting an inverse matrix in the calculation process or other factorization methods. In addition, the performances of the proposed algorithm and the existing algorithm were compared according to the matrix size. Overall, excellent speed-up of the proposed algorithm with good accuracy was demonstrated.

• Electronics and Telecommunications Trends
• /
• v.34 no.6
• /
• pp.100-107
• /
• 2019

Recently, reinforcement learning (RL) has expanded from the research phase of the virtual simulation environment to a wide range of applications, such as autonomous driving, natural language processing, recommendation systems, and disease diagnosis. However, RL is less likely to be used in these complex real-world environments. In contrast, inverse reinforcement learning (IRL) can obtain optimal policies in various situations; furthermore, it can use expert demonstration data to achieve its target task. In particular, IRL is expected to be a key technology for artificial general intelligence research that can successfully perform human intellectual tasks. In this report, we briefly summarize various IRL techniques and research directions.

• ETRI Journal
• /
• v.40 no.4
• /
• pp.511-521
• /
• 2018

The ability to realize human-motion imitation using robots is closely related to developments in the field of artificial intelligence. However, it is not easy to imitate human motions entirely owing to the physical differences between the human body and robots. In this paper, we propose a work chain-based inverse kinematics to enable a robot to imitate the human motion of upper limbs in real time. Two work chains are built on each arm to ensure that there is motion similarity, such as the end effector trajectory and the joint-angle configuration. In addition, a two-phase filter is used to remove the interference and noise, together with a self-collision avoidance scheme to maintain the stability of the robot during the imitation. Experimental results verify the effectiveness of our solution on the humanoid robot Nao-H25 in terms of accuracy and real-time performance.