• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.22 no.1
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• pp.192-207
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• 2023

Commercialization of level-4 (Lv.4) autonomous driving applications requires the definition of a safe road environment under which autonomous vehicles can operate safely. Thus, a risk assessment model is required to determine whether the operation of autonomous vehicles can provide safety to is sufficiently prepared for future real-life traffic problems. Although the risk factors of autonomous vehicles were selected and graded, the decision-making method was applied as qualitative data using a survey of experts in the field of autonomous driving due to the cause of the accident and difficulty in obtaining autonomous driving data. The fuzzy linguistic representation of decision-makers and the fuzzy analytic hierarchy process (AHP), which converts uncertainty into quantitative figures, were implemented to compensate for the AHP shortcomings of the multi-standard decision-making technique. Through the process of deriving the weights of the upper and lower attributes, the road alignment, which is a physical infrastructure, was analyzed as the most important risk factor in the operation risk of autonomous vehicles. In addition, the operation risk of autonomous vehicles was derived through the example of the risk of operating autonomous vehicles for the 5 areas to be evaluated.

• Convergence Security Journal
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• v.22 no.5
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• pp.95-105
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• 2022

The Army, Navy, and Air Force are making various efforts to develop a weapon system that incorporates the 4th industrial revolution technology so that it can be used in multi-domain operations. In order to effectively demonstrate the integrated combat power through the weapon system to which the new technology is applied, it is necessary to establish a network environment in which each weapon system can transmit and receive information smoothly. For this, it is essential to analyze the Information Exchange Requirement(IER) of each weapon system, but many IER analysis studies did not sufficiently reflect the various considerations of the actual tactical network. Therefore, this study closely analyzes the research methods and results of the existing information exchange requirements analysis studies. In IER analysis, the size of the message itself, the size of the network protocol header, the transmission/reception structure of the tactical network, the information distribution process, and the message occurrence frequency. In order to be able to use it for future IER prediction, we present a technique for calculating the information exchange requirement as a probability distribution using the Poisson distribution and the probability generating function. In order to prove the validity of this technique, the results of the probability distribution calculation using the message list and network topology samples are compared with the simulation results using Network Simulator 2.

• The Journal of the Convergence on Culture Technology
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• v.10 no.2
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• pp.167-172
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• 2024

In major wars of the 21st century, drones are expanding beyond surveillance and reconnaissance to include land and air as well as sea and underwater for purposes such as precision strikes, suicide attacks, and cognitive warfare. These drones will perform multi-domain operations, and to this end, they will continue to develop by improving the level of autonomy and strengthening scalability based on the High-Low Mix concept. Recently, drones have been used as a major means in major wars around the world, and there seems to be a good chance that they will evolve into game changers in the future. North Korea has also been making significant efforts to operate reconnaissance and attack drones for a long time. North Korea has recently continued to engage in provocations using drones, and its capabilities are gradually becoming more sophisticated. In addition, with the recent emergence of new strategic Drones, wartime and peacetime threats such as North Korea's use of these to secure surveillance, reconnaissance and early warning capabilities against South Korea and new types of provocations are expected to be strengthened. Through this study, we hope to provide implications by analyzing the capabilities of North Korea's strategic Drones, predicting their operation patterns, and conducting active follow-up research on the establishment of a comprehensive strategy, such as our military's drone deployment and counter-drone system solutions.

• Journal of Life Science
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• v.19 no.1
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• pp.101-110
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• 2009

The regulation of gene expression plays an important role in cell cycle controls. In this study, a novel $mas2^+$ (mitosis associated protein) gene, a homolog of human SMARCAD1 was isolated and characterized from a fission yeast Schizosaccharomyces pombe (S. pombe) using gene-specific polymerase chain reaction. The isolated gene contained a complete open reading frame capable of encoding 922 amino acid residues with a typical promoter, as judged by nucleotide sequence analysis. It was also found that an SNF2 domain is located, which is involved in the chromosome remodeling. The quantitative analysis of the $mas2^+$ transcript against $adh1^+$ showed that the expression level of $mas2^+$ is high before septum formation in S. pombe. When $mas2^+$ null mutant cells were grown at 27 and $35^{\circ}C$, the cytokinesis of $mas2^+$ null mutant was greatly delayed and a large number of multi-septate and mis-segregated cells were produced. In addition, the number of multi-septate cells significantly increased. When cells were cultured in YES rich medium to increase proliferation, the abnormal phenotypes $mas2^+$ null mutant dramatically increased. These phenotypes could be rescued by an over-expression of the mast gene. The Mas2 protein localized in the nuclei of S. pombe, as evidenced by Mas2-EGFP signals. These results suggest that the $mas2^+$ is homologous to human SMARCAD1 gene and involved in septum formation and chromosome remodeling control.

• Journal of Intelligence and Information Systems
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• v.19 no.4
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• pp.123-132
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• 2013

As the smartphones are equipped with various sensors such as the accelerometer, GPS, gravity sensor, gyros, ambient light sensor, proximity sensor, and so on, there have been many research works on making use of these sensors to create valuable applications. Human activity recognition is one such application that is motivated by various welfare applications such as the support for the elderly, measurement of calorie consumption, analysis of lifestyles, analysis of exercise patterns, and so on. One of the challenges faced when using the smartphone sensors for activity recognition is that the number of sensors used should be minimized to save the battery power. When the number of sensors used are restricted, it is difficult to realize a highly accurate activity recognizer or a classifier because it is hard to distinguish between subtly different activities relying on only limited information. The difficulty gets especially severe when the number of different activity classes to be distinguished is very large. In this paper, we show that a fairly accurate classifier can be built that can distinguish ten different activities by using only a single sensor data, i.e., the smartphone accelerometer data. The approach that we take to dealing with this ten-class problem is to use the ensemble of nested dichotomy (END) method that transforms a multi-class problem into multiple two-class problems. END builds a committee of binary classifiers in a nested fashion using a binary tree. At the root of the binary tree, the set of all the classes are split into two subsets of classes by using a binary classifier. At a child node of the tree, a subset of classes is again split into two smaller subsets by using another binary classifier. Continuing in this way, we can obtain a binary tree where each leaf node contains a single class. This binary tree can be viewed as a nested dichotomy that can make multi-class predictions. Depending on how a set of classes are split into two subsets at each node, the final tree that we obtain can be different. Since there can be some classes that are correlated, a particular tree may perform better than the others. However, we can hardly identify the best tree without deep domain knowledge. The END method copes with this problem by building multiple dichotomy trees randomly during learning, and then combining the predictions made by each tree during classification. The END method is generally known to perform well even when the base learner is unable to model complex decision boundaries As the base classifier at each node of the dichotomy, we have used another ensemble classifier called the random forest. A random forest is built by repeatedly generating a decision tree each time with a different random subset of features using a bootstrap sample. By combining bagging with random feature subset selection, a random forest enjoys the advantage of having more diverse ensemble members than a simple bagging. As an overall result, our ensemble of nested dichotomy can actually be seen as a committee of committees of decision trees that can deal with a multi-class problem with high accuracy. The ten classes of activities that we distinguish in this paper are 'Sitting', 'Standing', 'Walking', 'Running', 'Walking Uphill', 'Walking Downhill', 'Running Uphill', 'Running Downhill', 'Falling', and 'Hobbling'. The features used for classifying these activities include not only the magnitude of acceleration vector at each time point but also the maximum, the minimum, and the standard deviation of vector magnitude within a time window of the last 2 seconds, etc. For experiments to compare the performance of END with those of other methods, the accelerometer data has been collected at every 0.1 second for 2 minutes for each activity from 5 volunteers. Among these 5,900 ($=5{\times}(60{\times}2-2)/0.1$) data collected for each activity (the data for the first 2 seconds are trashed because they do not have time window data), 4,700 have been used for training and the rest for testing. Although 'Walking Uphill' is often confused with some other similar activities, END has been found to classify all of the ten activities with a fairly high accuracy of 98.4%. On the other hand, the accuracies achieved by a decision tree, a k-nearest neighbor, and a one-versus-rest support vector machine have been observed as 97.6%, 96.5%, and 97.6%, respectively.

• Journal of Intelligence and Information Systems
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• v.26 no.2
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• pp.131-145
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• 2020

In line with the trend of industrial innovation, IoT technology utilized in a variety of fields is emerging as a key element in creation of new business models and the provision of user-friendly services through the combination of big data. The accumulated data from devices with the Internet-of-Things (IoT) is being used in many ways to build a convenience-based smart system as it can provide customized intelligent systems through user environment and pattern analysis. Recently, it has been applied to innovation in the public domain and has been using it for smart city and smart transportation, such as solving traffic and crime problems using CCTV. In particular, it is necessary to comprehensively consider the easiness of securing real-time service data and the stability of security when planning underground services or establishing movement amount control information system to enhance citizens' or commuters' convenience in circumstances with the congestion of public transportation such as subways, urban railways, etc. However, previous studies that utilize image data have limitations in reducing the performance of object detection under private issue and abnormal conditions. The IoT device-based sensor data used in this study is free from private issue because it does not require identification for individuals, and can be effectively utilized to build intelligent public services for unspecified people. Especially, sensor data stored by the IoT device need not be identified to an individual, and can be effectively utilized for constructing intelligent public services for many and unspecified people as data free form private issue. We utilize the IoT-based infrared sensor devices for an intelligent pedestrian tracking system in metro service which many people use on a daily basis and temperature data measured by sensors are therein transmitted in real time. The experimental environment for collecting data detected in real time from sensors was established for the equally-spaced midpoints of 4×4 upper parts in the ceiling of subway entrances where the actual movement amount of passengers is high, and it measured the temperature change for objects entering and leaving the detection spots. The measured data have gone through a preprocessing in which the reference values for 16 different areas are set and the difference values between the temperatures in 16 distinct areas and their reference values per unit of time are calculated. This corresponds to the methodology that maximizes movement within the detection area. In addition, the size of the data was increased by 10 times in order to more sensitively reflect the difference in temperature by area. For example, if the temperature data collected from the sensor at a given time were 28.5℃, the data analysis was conducted by changing the value to 285. As above, the data collected from sensors have the characteristics of time series data and image data with 4×4 resolution. Reflecting the characteristics of the measured, preprocessed data, we finally propose a hybrid algorithm that combines CNN in superior performance for image classification and LSTM, especially suitable for analyzing time series data, as referred to CNN-LSTM (Convolutional Neural Network-Long Short Term Memory). In the study, the CNN-LSTM algorithm is used to predict the number of passing persons in one of 4×4 detection areas. We verified the validation of the proposed model by taking performance comparison with other artificial intelligence algorithms such as Multi-Layer Perceptron (MLP), Long Short Term Memory (LSTM) and RNN-LSTM (Recurrent Neural Network-Long Short Term Memory). As a result of the experiment, proposed CNN-LSTM hybrid model compared to MLP, LSTM and RNN-LSTM has the best predictive performance. By utilizing the proposed devices and models, it is expected various metro services will be provided with no illegal issue about the personal information such as real-time monitoring of public transport facilities and emergency situation response services on the basis of congestion. However, the data have been collected by selecting one side of the entrances as the subject of analysis, and the data collected for a short period of time have been applied to the prediction. There exists the limitation that the verification of application in other environments needs to be carried out. In the future, it is expected that more reliability will be provided for the proposed model if experimental data is sufficiently collected in various environments or if learning data is further configured by measuring data in other sensors.

• Investigative Magnetic Resonance Imaging
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• v.8 no.2
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• pp.94-99
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• 2004

Purpose : To investigate the signal enhancement ratio by NOE effect on in vivo $^{31}P$ MRS in human heart muscle and liver. we also evaluated the enhancement ratios of different phosphorus metabolites, which are important in 31P MRS for each organ. Materials and Methods : Ten normal subjects (M:F = 8:2, age range = 24-32 yrs) were included for in vivo $^{31}P$ MRS measurements on a 1.5 T whole-body MRI/MRS system using $^1H-^{31}P$ dual tuned surface coil. Two-dimensional Chemical Shift Imaging (2D CSI) pulse sequence for $^{31}P$ MRS was employed in all $^{31}P$ MRS measurements. First, $^{31}P$ MRS performed without NOE effect and then the same 2D CSI data acquisitions were repeated with NOE effect. After postprocessing the MRS raw data in the time domain, the signal enhancements in percent were estimated from the major metabolites. Results : The calculated NOE enhancement for liver $^{31}P$ MRS were $\alpha-ATP\;(7\%),\;\beta-ATP\;(9\%),\;\gamma-ATP\;(17\%),\;Pi\;(1\%),\;PDE\;(19\%)$ and $PME\;(31\%)$. Because there is no creatine kinase activity in liver, PCr signal is absent. For cardiac $^{31}P$ MRS, whole body coil gave better scout images and thus better localization than surface coil. In $^{31}P$cardiac multi-voxel spectra, DPG signal increased from left to right according to the amount of blood included. The calculated enhancement for cardiac $^{31}P$ MRS were : $\alpha-ATP\;(12\%),\;\beta-ATP\;(19\%),\;\gamma-ATP\;(30\%),\;PCr\;(34\%),\;Pi\;(20\%),\;(PDE)\;(51\%),\;and\;DPG\;(72\%)$. Conclusion : Our results revealed that the NOE effect was more pronounced in heart muscle than in liver with different coupling to 1H spin system and thus different heteronuclear cross-relaxation.

• Microbiology and Biotechnology Letters
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• v.41 no.1
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• pp.17-25
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• 2013

The thermotolerant methylotrophic yeast Hansenula polymorpha is an attractive model organism for various fundamental studies, such as the genetic control of enzymes involved in methanol metabolism, peroxisome biogenesis, nitrate assimilation, and resistance to heavy metals and oxidative stresses. In addition, H. polymorpha has been highlighted as a promising recombinant protein expression host, especially due to the availability of strong and tightly regulatable promoters. In this study, we investigated the possibility of employing human serum albumin (HSA) as the fusion tag for the secretory expression of heterologous proteins in H. polymorpha. A set of four expression cassettes, which contained the methanol oxidase (MOX) promoter, translational HSA fusion tag, and the terminator of MOX, were constructed. The expression cassettes were also designed to contain sequences for accessory elements including His8-tag, $2{\times}(Gly_4Ser_1)$ linkers, tobacco etch virus protease recognition sites (Tev), multi-cloning sites, and strep-tags. To determine the effects of the size of the HSA fusion tag on the secretory expression of the target protein, each cassette contained the HSA gene fragment truncated at a specific position based on its domain structure. By using the Green fluorescence protein gene as the reporter, the properties of each expression cassette were compared in various conditions. Our results suggest that the translational HSA fusion tag is an efficient tool for the secretory expression of recombinant proteins in H. polymorpha.

• Land and Housing Review
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• v.3 no.4
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• pp.369-378
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• 2012

In France, there are many forms of organizations based on the intercommunal solidarity for city development and management. The purpose of the collaboration among Communes is to achieve high quality and well-equipped service-delivery system through co-operation of public services needed grand finances : water supply and sewage system and waste disposal system etc. The cooperation among French Communes and its effects, even though these were owing to the existing French local administration system, continued throughout regional co-management and social co-development process. This study suggested some characteristics and implications of the collaborative-style French new-town development and management organizations focused on the EPA, SAN and CA. First, the role of developmental corporation like EPA and its collaborative structure of decision-making are meaningful, because in these ways many related Communes could share a goal of new town development. Second, the way of new town corporation (SAN) is important in the sense of enabling the Communes to collaborate with each others while maintaining autonomy, so those are not simply state-directed objects, which was very difficult in the former French local administration system. Finally, transforming to CA (Communautes d'agglomeration:city community), EPA as an intercommunal corporation is possible to extend its purpose to the domain of regional planning including new town and periphery areas and change its position to a subject which can practice Commune's sustainable development according to stages of city's development and maturity. The most important implication of this study on urban development in Korea is that administrative consultative council or association among local governments and related authorities need to be established and effectively operate because multi-stakeholders could share a goal of urban development and management through that.

• Fiber Technology and Industry
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• v.2 no.4
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• pp.490-508
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• 1998

One of the latest fields of research in the area of output devices is tactual display devices [13,31]. These tactual or haptic devices allow the user to receive haptic feedback output from a variety of sources. This allows the user to actually feel virtual objects and manipulate them by touch. This is an emerging technology and will be instrumental in enhancing the realism of wearable augmented environments for certain applications. Tactual displays have previously been used for scientific visualization in virtual environments by chemists and engineers to improve perception and understanding of force fields and of world models populated with the impenetrable. In addition to tactual displays, the use of wearable audio displays that allow sound to be spatialized are being developed. With wearable computers, designers will soon be able to pair spatialized sound to virtual representations of objects when appropriate to make the wearable computer experience even more realistic to the user. Furthermore, as the number and complexity of wearable computing applications continues to grow, there will be increasing needs for systems that are faster, lighter, and have higher resolution displays. Better networking technology will also need to be developed to allow all users of wearable computers to have high bandwidth connections for real time information gathering and collaboration. In addition to the technology advances that make users need to wear computers in everyday life, there is also the desire to have users want to wear their computers. In order to do this, wearable computing needs to be unobtrusive and socially acceptable. By making wearables smaller and lighter, or actually embedding them in clothing, users can conceal them easily and wear them comfortably. The military is currently working on the development of the Personal Information Carrier (PIC) or digital dog tag. The PIC is a small electronic storage device containing medical information about the wearer. While old military dog tags contained only 5 lines of information, the digital tags may contain volumes of multi-media information including medical history, X-rays, and cardiograms. Using hand held devices in the field, medics would be able to call this information up in real time for better treatment. A fully functional transmittable device is still years off, but this technology once developed in the military, could be adapted tp civilian users and provide ant information, medical or otherwise, in a portable, not obstructive, and fashionable way. Another future device that could increase safety and well being of its users is the nose on-a-chip developed by the Oak Ridge National Lab in Tennessee. This tiny digital silicon chip about the size of a dime, is capable of 'smelling' natural gas leaks in stoves, heaters, and other appliances. It can also detect dangerous levels of carbon monoxide. This device can also be configured to notify the fire department when a leak is detected. This nose chip should be commercially available within 2 years, and is inexpensive, requires low power, and is very sensitive. Along with gas detection capabilities, this device may someday also be configured to detect smoke and other harmful gases. By embedding this chip into workers uniforms, name tags, etc., this could be a lifesaving computational accessory. In addition to the future safety technology soon to be available as accessories are devices that are for entertainment and security. The LCI computer group is developing a Smartpen, that electronically verifies a user's signature. With the increase in credit card use and the rise in forgeries, is the need for commercial industries to constantly verify signatures. This Smartpen writes like a normal pen but uses sensors to detect the motion of the pen as the user signs their name to authenticate the signature. This computational accessory should be available in 1999, and would bring increased peace of mind to consumers and vendors alike. In the entertainment domain, Panasonic is creating the first portable hand-held DVD player. This device weight less than 3 pounds and has a screen about 6' across. The color LCD has the same 16:9 aspect ratio of a cinema screen and supports a high resolution of 280,000 pixels and stereo sound. The player can play standard DVD movies and has a hour battery life for mobile use. To summarize, in this paper we presented concepts related to the design and use of wearable computers with extensions to smart spaces. For some time, researchers in telerobotics have used computer graphics to enhance remote scenes. Recent advances in augmented reality displays make it possible to enhance the user's local environment with 'information'. As shown in this paper, there are many application areas for this technology such as medicine, manufacturing, training, and recreation. Wearable computers allow a much closer association of information with the user. By embedding sensors in the wearable to allow it to see what the user sees, hear what the user hears, sense the user's physical state, and analyze what the user is typing, an intelligent agent may be able to analyze what the user is doing and try to predict the resources he will need next or in the near future. Using this information, the agent may download files, reserve communications bandwidth, post reminders, or automatically send updates to colleagues to help facilitate the user's daily interactions. This intelligent wearable computer would be able to act as a personal assistant, who is always around, knows the user's personal preferences and tastes, and tries to streamline interactions with the rest of the world.