• Proceedings of the Korean Society of Precision Engineering Conference
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• 2013.05a
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• pp.759-760
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• 2013

• Journal of Internet Computing and Services
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• v.24 no.5
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• pp.1-7
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• 2023

This paper proposes a small cell resource partitioning allocation method to solve interference to machine type communication devices (MTCD) and improve performance in 5G heterogeneous networks (HetNet) where macro base station (MBS) and many small cell base stations (SBS) are overlaid. In the 5G HetNet, since various types of MTCDs generate data traffic, the load on the MBS increases. Therefore, in order to reduce the MBS load, a cell range expansion (CRE) method is applied in which a bias value is added to the received signal strength from the SBS and MTCDs satisfying the condition is connected to the SBS. More MTCDs connecting to the SBS through the CRE will reduce the load on the MBS, but performance of MTCDs will degrade due to interference, so a method to solve this problem is needed. The proposed small cell resource partitioning allocation method allocates resources with less interference from the MBS to mitigate interference of MTCDs newly added in the SBS with CRE, and improve the overall MTCD performace using separating resources according to the performance of existing MTCDs in the SBS. Through simulation results, the proposed small cell resource partitioning allocation method shows performance improvement of 21% and 126% in MTCDs capacity connected to MBS and SBS respectively, compared to the existing resource allocation methods.

• Journal of the Korean Society for Precision Engineering
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• v.17 no.10
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• pp.41-48
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• 2000

Manufacturing devices must be integrated for constructing CIM environment, but integration of heterogeneous system meets several economical and technological difficulties. In this case, MMS(Manufacturing Message Specification) can be an effective method, but it has problems which MMS products are generally very expensive and majority of the existing manufacturing devices do not support MMS. This paper describes the development of a gateway for Non-MMS-Compatible CNC machine tools to serve MMS and the implementation of OSI(Open System Interconnection) upper layer on TCP/IP. The developed system is applied to construct cell controller with heterogeneous devices under CIM environment and to evaluate interoperability and portability.

• Proceedings of the Korean Society for Bioinformatics Conference
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• 2000.11a
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• pp.53-55
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• 2000

Xenie is the JAVA application software that integrates and represents 'gene to function'information of human gene. Xenie extracts data from several heterogeneous molecular biology databases and provides integrated information in human readable and machine usable way. We defined 7 semantic frame classes (Gene, Transcript, Polypeptide, Protein_complex, Isotype, Functional_object, and Cell) as a common schema for storing and integrating gene to function information and relationship. Each of 7 semantic frame classes has data fields that are supposed to store biological data like gene symbol, disease information, cofactors, and inhibitors, etc. By using these semantic classes, Xenie can show how many transcripts and polypeptide has been known and what the function of gene products is in General. In detail, Xenie provides functional information of given human gene in the fields of semantic objects that are storing integrated data from several databases (Brenda, GDB, Genecards, HGMD, HUGO, LocusLink, OMIM, PIR, and SWISS-PROT). Although Xenie provide fully readable form of XML document for human researchers, the main goal of Xenie system is providing integrated data for other bioinformatic application softwares. Technically, Xenie provides two kinds of output format. One is JAVA persistent object, the other is XML document, both of them have been known as the most favorite solution for data exchange. Additionally, UML designs of Xenie and DTD for 7 semantic frame classes are available for easy data binding to other bioinformatic application systems. Hopefully, Xenie's output can provide more detailed and integrated information in several bioinformatic systems like Gene chip, 2D gel, biopathway related systems. Furthermore, through data integration, Xenie can also make a way for other bioiformatic systems to ask 'function based query'that was originally impossible to be answered because of separatly stored data in heterogeneous databases.

• International Journal of Computer Science & Network Security
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• v.22 no.4
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• pp.139-146
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• 2022

Wireless access technologies are emerging to enable high data rates for mobile users and novel applications that encompass both human and machine-type interactions. An essential approach to meet the rising demands on network capacity and offer high coverage for wireless users on upcoming fifth generation (5G) networks is heterogeneous networks (HetNets), which are generated by combining the installation of macro cells with a large number of densely distributed small cells Deployment in 5G architecture has several issues because to the rising complexity of network topology in 5G HetNets with many distinct base station types. Aside from the numerous benefits that dense small cell deployment delivers, it also introduces key mobility management issues such as frequent handover (HO), failures, delays and pingpong HO. This article investigates 5G HetNet mobility management in terms of radio resource control. This article also discusses the key challenges for 5G mobility management.

• Archives of Plastic Surgery
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• v.38 no.4
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• pp.438-444
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• 2011

Purpose: Adipose-derived stromal cells (ASCs) are readily harvested from lipoaspirated tissue or subcutaneous adipose tissue fragments. The stromal vascular fraction (SVF) is a heterogeneous set of cell populations that surround and support adipose tissue, which includes the stromal cells, ASCs, that have the ability to differentiate into cells of several lineages and contains cells from the microvasculature. The mechanisms that drive the ASCs into the osteoblast lineage are still not clear, but the process has been more extensively studied in bone marrow stromal cells. The purpose of this study was to investigate the osteogenic capacity of adipose derived SVF cells and evaluate bone formation following implantation of SVF cells into the bone defect of human phalanx. Methods: Case 1 a 43-year-old male was wounded while using a press machine. After first operation, segmental bone defects of the left 3rd and 4th middle phalanx occurred. At first we injected the SVF cells combined with demineralized bone matrix (DBM) to defected 4th middle phalangeal bone lesion. We used P (L/DL)LA [Poly (70L-lactide-co-30DL-lactide) Co Polymer P (L/DL)LA] as a scaffold. Next, we implanted the SVF cells combined with DBM to repair left 3rd middle phalangeal bone defect in sequence. Case 2 was a 25-year-old man with crushing hand injury. Three months after the previous surgery, we implanted the SVF cells combined with DBM to restore right 3rd middle phalangeal bone defect by syringe injection. Radiographic images were taken at follow-up hospital visits and evaluated radiographically by means of computerized analysis of digital images. Results: The phalangeal bone defect was treated with autologous SVF cells isolated and applied in a single operative procedure in combination with DBM. The SVF cells were supported in place with mechanical fixation with a resorbable macroporous sheets acting as a soft tissue barrier. The radiographic appearance of the defect revealed a restoration to average bone density and stable position of pharyngeal bone. Densitometric evaluations for digital X-ray revealed improved bone densities in two cases with pharyngeal bone defects, that is, 65.2% for 4th finger of the case 1, 60.5% for 3rd finger of the case 1 and 60.1% for the case 2. Conclusion: This study demonstrated that adipose derived stromal vascular fraction cells have osteogenic potential in two clinical case studies. Thus, these reports show that cells from the SVF cells have potential in many areas of clinical cell therapy and regenerative medicine, albeit a lot of work is yet to be done.

• Korean Journal of Cognitive Science
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• v.33 no.1
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• pp.51-75
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• 2022

Transcranial direct current stimulation (tDCS) is a non-invasive brain stimulation that is able to alter neuronal activity in particular brain regions. Many studies have researched how tDCS modulates neuronal activity and reorganizes neural networks. However it is difficult to conclude the effect of brain stimulation because the studies are heterogeneous with respect to the stimulation parameter as well as individual difference. It is not fully in agreement with the effects of brain stimulation. In particular few studies have researched the reason of variability of brain stimulation in response to time so far. The study investigated individual variability of brain stimulation based on circadian rhythm and chronotype. Participants were divided into two groups which are morning type and evening type. The experiment was conducted by Zoom meeting which is video meeting programs. Participants were sent experiment tool which are Muse(EEG device), tdcs device, cell phone and cell phone holder after manuals for experimental equipment were explained. Participants were required to make a phone in frount of a camera so that experimenter can monitor online EEG data. Two participants who was difficult to use experimental devices experimented in a laboratory setting where experimenter set up devices. For all participants the accuracy of 98% was achieved by SVM using leave one out cross validation in classification in the the effects of morning stimulation and the evening stimulation. For morning type, the accuracy of 92% and 96% was achieved in classification in the morning stimulation and the evening stimulation. For evening type, it was 94% accuracy in classification for the effect of brain stimulation in the morning and the evening. Feature importance was different both in classification in the morning stimulation and the evening stimulation for morning type and evening type. Results indicated that the effect of brain stimulation can be explained with brain state and trait. Our study results noted that the tDCS protocol for target state is manipulated by individual differences as well as target state.

• Journal of Intelligence and Information Systems
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• v.24 no.4
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• pp.111-136
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• 2018

In this paper, we propose a methodology to extract answer information about queries from various types of unstructured documents collected from multi-sources existing on web in order to expand knowledge base. The proposed methodology is divided into the following steps. 1) Collect relevant documents from Wikipedia, Naver encyclopedia, and Naver news sources for "subject-predicate" separated queries and classify the proper documents. 2) Determine whether the sentence is suitable for extracting information and derive the confidence. 3) Based on the predicate feature, extract the information in the proper sentence and derive the overall confidence of the information extraction result. In order to evaluate the performance of the information extraction system, we selected 400 queries from the artificial intelligence speaker of SK-Telecom. Compared with the baseline model, it is confirmed that it shows higher performance index than the existing model. The contribution of this study is that we develop a sequence tagging model based on bi-directional LSTM-CRF using the predicate feature of the query, with this we developed a robust model that can maintain high recall performance even in various types of unstructured documents collected from multiple sources. The problem of information extraction for knowledge base extension should take into account heterogeneous characteristics of source-specific document types. The proposed methodology proved to extract information effectively from various types of unstructured documents compared to the baseline model. There is a limitation in previous research that the performance is poor when extracting information about the document type that is different from the training data. In addition, this study can prevent unnecessary information extraction attempts from the documents that do not include the answer information through the process for predicting the suitability of information extraction of documents and sentences before the information extraction step. It is meaningful that we provided a method that precision performance can be maintained even in actual web environment. The information extraction problem for the knowledge base expansion has the characteristic that it can not guarantee whether the document includes the correct answer because it is aimed at the unstructured document existing in the real web. When the question answering is performed on a real web, previous machine reading comprehension studies has a limitation that it shows a low level of precision because it frequently attempts to extract an answer even in a document in which there is no correct answer. The policy that predicts the suitability of document and sentence information extraction is meaningful in that it contributes to maintaining the performance of information extraction even in real web environment. The limitations of this study and future research directions are as follows. First, it is a problem related to data preprocessing. In this study, the unit of knowledge extraction is classified through the morphological analysis based on the open source Konlpy python package, and the information extraction result can be improperly performed because morphological analysis is not performed properly. To enhance the performance of information extraction results, it is necessary to develop an advanced morpheme analyzer. Second, it is a problem of entity ambiguity. The information extraction system of this study can not distinguish the same name that has different intention. If several people with the same name appear in the news, the system may not extract information about the intended query. In future research, it is necessary to take measures to identify the person with the same name. Third, it is a problem of evaluation query data. In this study, we selected 400 of user queries collected from SK Telecom 's interactive artificial intelligent speaker to evaluate the performance of the information extraction system. n this study, we developed evaluation data set using 800 documents (400 questions * 7 articles per question (1 Wikipedia, 3 Naver encyclopedia, 3 Naver news) by judging whether a correct answer is included or not. To ensure the external validity of the study, it is desirable to use more queries to determine the performance of the system. This is a costly activity that must be done manually. Future research needs to evaluate the system for more queries. It is also necessary to develop a Korean benchmark data set of information extraction system for queries from multi-source web documents to build an environment that can evaluate the results more objectively.