• Journal of Intelligence and Information Systems
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• v.27 no.1
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• pp.191-207
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• 2021

Up to this day, mobile communications have evolved rapidly over the decades, mainly focusing on speed-up to meet the growing data demands of 2G to 5G. And with the start of the 5G era, efforts are being made to provide such various services to customers, as IoT, V2X, robots, artificial intelligence, augmented virtual reality, and smart cities, which are expected to change the environment of our lives and industries as a whole. In a bid to provide those services, on top of high speed data, reduced latency and reliability are critical for real-time services. Thus, 5G has paved the way for service delivery through maximum speed of 20Gbps, a delay of 1ms, and a connecting device of 106/㎢ In particular, in intelligent traffic control systems and services using various vehicle-based Vehicle to X (V2X), such as traffic control, in addition to high-speed data speed, reduction of delay and reliability for real-time services are very important. 5G communication uses high frequencies of 3.5Ghz and 28Ghz. These high-frequency waves can go with high-speed thanks to their straightness while their short wavelength and small diffraction angle limit their reach to distance and prevent them from penetrating walls, causing restrictions on their use indoors. Therefore, under existing networks it's difficult to overcome these constraints. The underlying centralized SDN also has a limited capability in offering delay-sensitive services because communication with many nodes creates overload in its processing. Basically, SDN, which means a structure that separates signals from the control plane from packets in the data plane, requires control of the delay-related tree structure available in the event of an emergency during autonomous driving. In these scenarios, the network architecture that handles in-vehicle information is a major variable of delay. Since SDNs in general centralized structures are difficult to meet the desired delay level, studies on the optimal size of SDNs for information processing should be conducted. Thus, SDNs need to be separated on a certain scale and construct a new type of network, which can efficiently respond to dynamically changing traffic and provide high-quality, flexible services. Moreover, the structure of these networks is closely related to ultra-low latency, high confidence, and hyper-connectivity and should be based on a new form of split SDN rather than an existing centralized SDN structure, even in the case of the worst condition. And in these SDN structural networks, where automobiles pass through small 5G cells very quickly, the information change cycle, round trip delay (RTD), and the data processing time of SDN are highly correlated with the delay. Of these, RDT is not a significant factor because it has sufficient speed and less than 1 ms of delay, but the information change cycle and data processing time of SDN are factors that greatly affect the delay. Especially, in an emergency of self-driving environment linked to an ITS(Intelligent Traffic System) that requires low latency and high reliability, information should be transmitted and processed very quickly. That is a case in point where delay plays a very sensitive role. In this paper, we study the SDN architecture in emergencies during autonomous driving and conduct analysis through simulation of the correlation with the cell layer in which the vehicle should request relevant information according to the information flow. For simulation: As the Data Rate of 5G is high enough, we can assume the information for neighbor vehicle support to the car without errors. Furthermore, we assumed 5G small cells within 50 ~ 250 m in cell radius, and the maximum speed of the vehicle was considered as a 30km ~ 200 km/hour in order to examine the network architecture to minimize the delay.

• Journal of Intelligence and Information Systems
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• v.19 no.2
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• pp.101-123
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• 2013

Recently due to the advancements of science and information technology, the socio-economic business areas are changing from the industrial economy to a knowledge economy. Furthermore, companies need to do creation of new value through continuous innovation, development of core competencies and technologies, and technological convergence. Therefore, the identification of major trends in technology research and the interdisciplinary knowledge-based prediction of integrated technologies and promising techniques are required for firms to gain and sustain competitive advantage and future growth engines. The aim of this paper is to understand the recent research trend in management of technology (MOT) and to foresee promising technologies with deep knowledge for both technology and business. Furthermore, this study intends to give a clear way to find new technical value for constant innovation and to capture core technology and technology convergence. Bibliometrics is a metrical analysis to understand literature's characteristics. Traditional bibliometrics has its limitation not to understand relationship between trend in technology management and technology itself, since it focuses on quantitative indices such as quotation frequency. To overcome this issue, the network focused bibliometrics has been used instead of traditional one. The network focused bibliometrics mainly uses "Co-citation" and "Co-word" analysis. In this study, a keywords network analysis, one of social network analysis, is performed to analyze recent research trend in MOT. For the analysis, we collected keywords from research papers published in international journals related MOT between 2002 and 2011, constructed a keyword network, and then conducted the keywords network analysis. Over the past 40 years, the studies in social network have attempted to understand the social interactions through the network structure represented by connection patterns. In other words, social network analysis has been used to explain the structures and behaviors of various social formations such as teams, organizations, and industries. In general, the social network analysis uses data as a form of matrix. In our context, the matrix depicts the relations between rows as papers and columns as keywords, where the relations are represented as binary. Even though there are no direct relations between papers who have been published, the relations between papers can be derived artificially as in the paper-keyword matrix, in which each cell has 1 for including or 0 for not including. For example, a keywords network can be configured in a way to connect the papers which have included one or more same keywords. After constructing a keywords network, we analyzed frequency of keywords, structural characteristics of keywords network, preferential attachment and growth of new keywords, component, and centrality. The results of this study are as follows. First, a paper has 4.574 keywords on the average. 90% of keywords were used three or less times for past 10 years and about 75% of keywords appeared only one time. Second, the keyword network in MOT is a small world network and a scale free network in which a small number of keywords have a tendency to become a monopoly. Third, the gap between the rich (with more edges) and the poor (with fewer edges) in the network is getting bigger as time goes on. Fourth, most of newly entering keywords become poor nodes within about 2~3 years. Finally, keywords with high degree centrality, betweenness centrality, and closeness centrality are "Innovation," "R&D," "Patent," "Forecast," "Technology transfer," "Technology," and "SME". The results of analysis will help researchers identify major trends in MOT research and then seek a new research topic. We hope that the result of the analysis will help researchers of MOT identify major trends in technology research, and utilize as useful reference information when they seek consilience with other fields of study and select a new research topic.

• 한국정보디스플레이학회:학술대회논문집
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• 2008.10a
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• pp.107-108
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• 2008

The spectacular development of AMLCDs, been made possible by a-Si:H technology, still faces two major drawbacks due to the intrinsic structure of a-Si:H, namely a low mobility and most important a shift of the transfer characteristics of the TFTs when submitted to bias stress. This has lead to strong research in the crystallization of a-Si:H films by laser and furnace annealing to produce polycrystalline silicon TFTs. While these devices show improved mobility and stability, they suffer from uniformity over large areas and increased cost. In the last decade we have focused on microcrystalline silicon (${\mu}c$-Si:H) for bottom gate TFTs, which can hopefully meet all the requirements for mass production of large area AMOLED displays [1,2]. In this presentation we will focus on the transfer of a deposition process based on the use of $SiF_4$-Ar-$H_2$ mixtures from a small area research laboratory reactor into an industrial gen 1 AKT reactor. We will first discuss on the optimization of the process conditions leading to fully crystallized films without any amorphous incubation layer, suitable for bottom gate TFTS, as well as on the use of plasma diagnostics to increase the deposition rate up to 0.5 nm/s [3]. The use of silicon nanocrystals appears as an elegant way to circumvent the opposite requirements of a high deposition rate and a fully crystallized interface [4]. The optimized process conditions are transferred to large area substrates in an industrial environment, on which some process adjustment was required to reproduce the material properties achieved in the laboratory scale reactor. For optimized process conditions, the homogeneity of the optical and electronic properties of the ${\mu}c$-Si:H films deposited on $300{\times}400\;mm$ substrates was checked by a set of complementary techniques. Spectroscopic ellipsometry, Raman spectroscopy, dark conductivity, time resolved microwave conductivity and hydrogen evolution measurements allowed demonstrating an excellent homogeneity in the structure and transport properties of the films. On the basis of these results, optimized process conditions were applied to TFTs, for which both bottom gate and top gate structures were studied aiming to achieve characteristics suitable for driving AMOLED displays. Results on the homogeneity of the TFT characteristics over the large area substrates and stability will be presented, as well as their application as a backplane for an AMOLED display.

• Applied Microscopy
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• v.15 no.2
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• pp.31-68
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• 1985

Authors are trying to unveil the ultrastructural organization of olfactory bulb, which has been summerized under light microscopic level or communicated only in some detail in different view point until now. For the critical point of view, since the phylogenetical approach will give the ultimate value in the correlative study between structural and functional bases (Brodal, 1969), the present study was carried out light and electron microscopic analyses of the structures of the neurons and synaptic organizations in olfactory bulbs from different animals in phylogenetical scale. We selected each one species from five animal classes: the house rabbit(Oryctolagus cuniculus var. domesticus [Gmelin]) from Mammalia, the domestic fowl (Gallus gallus domesticus Brisson) from Aves, the viper (Agkistrodon hylys [G.P. Pallas]) from Reptilia, a frog (Bombiana orientalis Boulenger) from Amphibia and the crussian carp (Carassius carassius [Linne]) from Pisces. For light microscopic study, samples were fixed in 10% formalin and paraffin sections were stained with hematoxylin-eosin. For the electron microscopic study, the tissues were fixed by perfusion through the heart or immersion with 1% paraform-aldehyde-glutaraldehyde mixture (phosphate buffer, pH 7.4), and final tissue block trimmed under dissecting microscope were osmicated (1% OsO4), they were embedded in Araldite or Epon 812, and ultrathin sections were made by LKB-V ultratome following the inspection of semi-thin sections stained with toluidine blue-borax solution. Ultra-thin sections contrasted with uranyl acetate and lead citrate were observed with JEM 100CX electron microscope. We have summerized our morphological analyses as follows: 1. The olfactory bulb of rabbit, viper and frog shows the eight layers of fila olfactoria, glomerular, external granular, external plexiform, mitral cell, internal plexiform, internal granular, medullary but domestic fowl shows the five layers of glomerular, fibrillar, mitral, granular and medullary and the three layers of fibrilla, glomerular and medullary in crussian carp. The sharpness of demarcation between the layers shows deferential tendency according to phylogenetical order. 2. Mitral cells of vertebrate have large triangular or oval shape with spherical nuclei which contain not so much chromatin. The cytoplasm contains numerous cell organelles, of which Nissl's bodies or granular endoplasmic reticula arranged as parallel strands. Development of granular endoplasmic reticula were declined as the phylogentical grade is going lower. 3. Tufted cells of all animal are mostly spindle or polygonal contour and contain oval nuclei which located in periphery of cytoplasm. The nuclei of rabbit, fowl, viper and frog has relatively space chromatin, but a nucleus of crussian carp contain irregularly aggregated chromatin in karyoplasm. Their cytoplasmic volume and cell organelle contents are in between those of mitral cell and granular cell. They contain moderate amount of mitochondria, granular endoplasmic reticula, a few Golgi complex, polysomes, lysosome, etc. 4. Granule of cells of all the vertebrate amimals studied exhibit similar features; cells and their dense nuclei show spherical or oval contour, and they have the thin rim of cytoplasm which contain only a few cell organelles. 5. In rabbit, the soma of mitral cells were in contact with boutons with two types of synaptic vesicles, that is, round and flat vesicles, especially flat vesicles in boutons were showing reciprocal synapses. However, in domestic fowls, vipers, frogs and crussian carps, there were found boutons showing only spherical synaptic vesicles. 6. The boutons containing round synaptic vesicles were made contact with the some of tufted cell of olfactory bulb in the rabbits, fowls, vipers and frogs, but no synaptic boutons were observed in soma of tufted cells in crussian carps. In the frogs, there were observed dendrites were contact with the soma of tufted cells. 7. In the neuropils of plexiform, granular and glomerular layers olfactory bulbs in the vertebrate, the synapses were axo-large dendrites, axo-median and small dendrites, dendrodendritic, and axo-axonal contacts. However, in the neuropil of crussian carps, synapses were observed only in glomerular layer.

• Korean Journal of Remote Sensing
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• v.39 no.5_4
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• pp.1135-1144
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• 2023

Many agricultural reservoirs in South Korea, constructed before 1970, have become aging facilities. The majority of small-scale reservoirs lack measurement systems to ascertain basic specifications and water levels, classifying them as unmeasured reservoirs. Furthermore, continuous sedimentation within the reservoirs and industrial development-induced water quality deterioration lead to reduced water supply capacity and changes in reservoir morphology. This study utilized Light Detection And Ranging (LiDAR) sensors, which provide elevation information and allow for the characterization of surface features, to construct high-resolution Digital Surface Model (DSM) and Digital Elevation Model (DEM) data of reservoir facilities. Additionally, bathymetric measurements based on multibeam echosounders were conducted to propose an updated approach for determining reservoir capacity. Drone-based LiDAR was employed to generate DSM and DEM data with a spatial resolution of 50 cm, enabling the display of elevations of hydraulic structures, such as embankments, spillways, and intake channels. Furthermore, using drone-based hyperspectral imagery, Normalized Difference Vegetation Index (NDVI) and Normalized Difference Water Index (NDWI) were calculated to detect water bodies and verify differences from existing reservoir boundaries. The constructed high-resolution DEM data were integrated with bathymetric measurements to create underwater contour maps, which were used to generate a Triangulated Irregular Network (TIN). The TIN was utilized to calculate the inundation area and volume of the reservoir, yielding results highly consistent with basic specifications. Considering areas that were not surveyed due to underwater vegetation, it is anticipated that this data will be valuable for future updates of reservoir capacity information.