• The KIPS Transactions:PartD
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• v.9D no.2
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• pp.259-266
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• 2002

The main issue in software development is the ability of software project effort and cost estimation in the early phase of software life cycle. The regression models for project effort and cost estimation are presented by function point that is a software sire. The data sets used to conduct previous studies are of ten small and not too recent. Applying these models to 789 project data developed from 1990 ; the models only explain fewer than 0.53 $R^2$(Coefficient of determination) of the data variation. Homogeneous group in accordance with project delivery rate (PDR) divides the data sets. Then this paper presents general effort estimation models using project delivery rate. The presented model has a random distribution of residuals and explains more than 0.93 $R^2$ of data variation in most of PDR ranges.

• The Journal of the Korea institute of electronic communication sciences
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• v.18 no.6
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• pp.1081-1086
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• 2023

The rapid growth and increasing complexity of modern networks have highlighted the limitations of traditional network architectures. The emergence of SDN (Software-Defined Network) in response to these challenges has changed the existing network environment. The SDN separates the control unit and the data unit, and adjusts the network operation using a centralized controller. However, this structure has also recently caused a huge amount of traffic due to the rapid spread of numerous Internet of Things (IoT) devices, which has not only slowed the transmission speed of the network but also made it difficult to ensure quality of service (QoS). Therefore, this paper proposes a method of load distribution by switching the IP and any server (processor) from the existing data processing scheduling technique, RR (Round-Robin), to mapping when a large amount of data flows in from a specific IP, that is, server overload and data loss.

• Korean Journal of Remote Sensing
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• v.38 no.5_1
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• pp.511-521
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• 2022

Cloud detection and removal from satellite images is an essential process for topographic observation and analysis. Threshold-based cloud detection techniques show stable performance because they detect using the physical characteristics of clouds, but they have the disadvantage of requiring all channels' images and long computational time. Cloud detection techniques using deep learning, which have been studied recently, show short computational time and excellent performance even using only four or less channel (RGB, NIR) images. In this paper, we confirm the performance dependence of the deep learning network according to the heterogeneous learning dataset with different resolutions. The DeepLabV3+ network was improved so that channel features of cloud detection were extracted and learned with two published heterogeneous datasets and mixed data respectively. As a result of the experiment, clouds' Jaccard index was low in a network that learned with different kind of images from test images. However, clouds' Jaccard index was high in a network learned with mixed data that added some of the same kind of test data. Clouds are not structured in a shape, so reflecting channel features in learning is more effective in cloud detection than spatial features. It is necessary to learn channel features of each satellite sensors for cloud detection. Therefore, cloud detection of heterogeneous sensors with different resolutions is very dependent on the learning dataset.

• Archives of Pharmacal Research
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• v.29 no.10
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• pp.890-897
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• 2006

In inflammatory responses, induction of cytokines and other immune regulator genes in macrophages by pathogen-associated signal such as lipopolysaccharide (LPS) plays a crucial role. In this study, the gene expression profile changes by LPS treatment in the macrophage/monocyte lineage cell line RAW264.7 was investigated. A 60-mer oligonucleotide microarray of which probes target 32381 mouse genes was used. A reverse transcription-in vitro translation labeling protocol and a chemileuminescence detection system were employed. The mRNA expression levels in RAW264.7 cells treated for 6 h with LPS and the control vehicle were compared. 747 genes were up-regulated and 523 genes were down-regulated by more than 2 folds. 320 genes showing more than 4-fold change by LPS treatment were further classified for the biological process, molecular function, and signaling pathway. The biological process categories that showed high number of increased genes include the immunity and defense, the nucleic acid metabolism, the protein metabolism and modification, and the signal transduction process. The chemokine-cytokine signaling, interleukin signaling, Toll receptor signaling, and apoptosis signaling pathways involved high number of genes differentially expressed in response to LPS. These expression profile data provide more comprehensive information on LPS-target genes in RAW264.7 cells, which will be useful in comparing gene expression changes induced by extracts and compounds from anti-inflammatory medicinal herbs.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.21 no.9
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• pp.1666-1673
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• 2017

Republic of Korea is divided into South Korea and North Korea, creating military conflicts and social conflicts. North Korea is conducting cyberattacks against South Korea and has hacked South Korea's defense network. In the world of cyberspace, the boundaries of the borders are becoming obscured, and cyberattacks and cyberterrorism for cyberwarfare operate with digital computing connected to points, time and space. Agenda and manual are needed for national cybersecurity. Also, it is necessary to study national cybersecurity laws and policies that can create and implement nationalcyber security policy. This paper investigates cyberterrorism situation in North and South Korean confrontation situation and damage to cyberwarfare in the world. We also study cybersecurity activities and cyberwarfare response agendas, manuals and new technologies at home and abroad. And propose national cybersecurity policy and propose policies so that '(tentative) The National Cybersecurity Law' is established. This study will be used as basic data of national cybersecurity law and policy.

• Korean Journal of Cognitive Science
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• v.16 no.2
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• pp.141-154
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• 2005

The purpose of this study was to investigate the effects of implicit and explicit situation awareness instruction on decision making and event related brain potentials. Psychophysiological data obtained from 36 intermediated level tennis players whose National Tennis Rating Program(NTTP) belong 2 to 2.5 were compared. Participants were randomly assigned to one of three experimental groups: (1) implicit situation awareness, (2) explicit situation awareness, and (3) control group. A total of 90 clips were presented via a beam project screen, and participants pressed one of three jelly bean buttons to indicate the direction of ball hit. Dependent measures were the latencies and amplitudes of P300 on Pz, Cz, and Fz. The results of this study indicated that participants in the implicit situation awareness produced tenser P300, than participants in the explicit situation awareness group. The findings also indicated that single defense showed longer P300 latencies than single attack as well as double defense. The P300-amplitude of treatment groups were longer than control group. The Cz area showed shorer P300 latencies than Pz and Fz areas. In addition, single defense situation demonstrated longer P300 latencies than single attack and double defence situations. Based on this study, it is believed that implicit and explicit situation awareness instruction influence decision making in different ways.

• Journal of the Korean Institute of Intelligent Systems
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• v.20 no.2
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• pp.226-233
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• 2010

The study of information fusion technology, which merges various types of data to recognize a situation more exactly, has begun in the area of national defense. Recently, the concept of information fusion is getting applied to other fields, and we are interested in maritime safety. In navigation, officers receive data about inside and outside of ship from several devices in bridge, and use it to recognize and predict the safety situation. However, too much and fast updated data might even fatigue mates, and there is the problem of inconsistency among data from several types of devices. This paper introduce how can use information fusion technology for the situation awareness and prediction of navigation safety, and show the realization possibility of Intelligent Navigation Safety Information System through an information fusion example in a specific situation scenario.

• Journal of the Institute of Electronics and Information Engineers
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• v.52 no.4
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• pp.99-105
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• 2015

As increasing the use of smart phones, the interest of iOS and Android operating system is growing up. In this paper, a novel steganographic method based on Android platform is proposed. Firstly, we analyze the skia based image format that is supporting 2D graphic libraries in Android operating system. Then, we propose a new data hiding method based on the Android bitmap image format. The proposed method hides the secret data on the four true color areas which include Alpha, Red, Green, Blue. In especial, we increase the embedding capacity of the secret data on the Alpha area with a less image distortion. The experimental results show that the proposed method has a higher embedding capacity and less distortion by changing the size of the secret bits on the Alpha area.

• Electronics and Telecommunications Trends
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• v.34 no.5
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• pp.14-25
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• 2019

As the Internet of Things, artificial intelligence and big data have received a lot of attention as key growth engines in the era of the fourth industrial revolution, data acquisition and utilization in mobile, automotive, robotics, manufacturing, agriculture, health care and national defense are becoming more important. Due to numerous data-based industrial changes, demand for sensor technologies is exploding, especially for intelligent sensor technologies that combine control, judgement, storage and communication functions with the sensors's own functions. Intelligent sensor technology can be defined as a convergence component technology that combines intelligent sensor units, intelligent algorithms, modules with signal processing circuits, and integrated plaform technologies. Intelligent sensor technology, which can be applied to variety of smart IT convergence services such as smart devices, smart homes, smart cars, smart factory, smart cities, and others, is evolving towards intelligent and convergence technologies that produce new high-value information through recognition, reasoning, and judgement based on artificial intelligence. As a result, development of intelligent sensor units is accelerating with strategies for miniaturization, low-power consumption and convergence, new form factor such as flexible and stretchable form, and integration of high-resolution sensor arrays. In the future, these intelligent sensor technologies will lead explosive sensor industries in the era of data-based artificial intelligence and will greatly contribute to enhancing nation's competitiveness in the global sensor market. In this report, we analyze and summarize the recent trends in intelligent sensor technologies, especially those for four core technologies.

• Journal of the Korea Society for Simulation
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• v.31 no.2
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• pp.11-20
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• 2022

There is a critical need for AI assistance in guard operations of Army base perimeters, which is exacerbated by changes in the national defense and security environment such as force reduction. In addition, the possibility for human error inherent to perimeter guard operations attests to the need for an innovative revamp of current systems. The purpose of this study is to propose a real-time object detection AI tailored to military CCTV surveillance with three unique characteristics. First, training data suitable for situations in which relatively small objects must be recognized is used due to the characteristics of military CCTV. Second, we utilize a data augmentation algorithm suited for military context applied in the data preparation step. Third, a noise reduction algorithm is applied to account for military-specific situations, such as camouflaged targets and unfavorable weather conditions. The proposed system has been field-tested in a real-world setting, and its performance has been verified.