• Title/Summary/Keyword: Network matching

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A study on camping brand's BI formation and branding strategy - Focused on related word research based on big data for sensible approach & market research for cognitive approach (캠핑 브랜드의 브랜드 아이덴티티(BI) 구축 및 전략 - 감성·인지적 접근을 기반으로 한 빅 데이터 및 마켓조사를 중심으로 -)

  • Choi, Soo-Ah;Lee, Ae-Jin
    • Journal of Communication Design
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    • v.63
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    • pp.336-347
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    • 2018
  • Nowadays, in Korea, the number of campers is increased over 5 million. Many Korean camping brands have excellent qualities however, a lot of times weak brand identities to be globally known. The purpose of this study is to provide helpful sources to have strong brand identities, add more values based on related word research from big data and market research. The data is to be analysed by sensible & cognitive approaches. The keywords for the sensible research are 'camping, camp, camping brand, and camping design'. Then 17 representative oversea brands and 10 Korean brands were analysed for the market researches. From related word research from big data, we can find out the thinking process of potential consumers, how people communicates to exchange information, and what can be the sources to add brand values. Also from the market researches, we were able to find that successful brands have distinctive brand identities, stories, logos with representable colors and they continuous produce signature designs and own way of color matching.

A Study on Expression Interpolation Algorithm of Hazard Mapping for Damaged from flood According to Real Rainfall Linkage (실측 강우 연계에 따른 호우피해예상도 표출 보간 알고리즘에 관한 연구)

  • Lim, So Mang;Yu, Wan Sik;Hwang, Eui Ho
    • Proceedings of the Korea Water Resources Association Conference
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    • 2018.05a
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    • pp.381-381
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    • 2018
  • 우리나라에서는 지속적인 자연재해로 각기 다른 필요성과 목적에 따라 다양한 형태의 홍수 침수 관련 지도가 작성되어 왔다. 연구 성과로 작성된 계획 빈도 및 상위 2개 빈도의 호우피해예상도를 실측 강우와 연계하여 재난관리단계별 대응단계에 활용하기 위해 실시간 피해위험구역을 표출하고자 한다. 본 연구는 실시간으로 피해위험구역을 표출하기 위해 실측 강우와 연계된 호우피해예상도에 공간 보간 알고리즘을 적용하고자 한다. 호우피해예상도란 돌발호우나 태풍으로 인하여 홍수가 발생하면 인명 및 재산피해를 최소화하기 위해 홍수지역을 미리 예측 가능하도록 제작된 지도이다. 지형자료(DEM), 하천 중심선(Stream Centerline), 하천 횡단면(Cross-Section Line), 제방고(Bank), 수문기상 자료(Hydrological Data), 조도계수(Roughness) 등을 사용하여 하천법 제 21조와 하천법시행령 제 17조를 근거로 작성된다. 본 연구에서는 호우피해예상도에 IDW(Inverse Distance Weighted, 역거리가중법) 보간, TIN(Triangulated Irregular Network system, 불규칙삼각망) 보간, Kriging 보간 방법 적용 알고리즘을 제시하고자 하였다. 호우피해예상도에 보간 알고리즘을 적용하기 위해 보간 방법에 따른 적용사례를 분석하였으며 그 결과, 보간 알고리즘을 적용한 호우피해예상도 보간을 통하여 계획빈도 및 상위 2개 빈도 이외의 빈도(하위빈도-계획빈도, 계획빈도-상위빈도 구간)에 대한 호우피해예상도의 피해위험구역 구현 방안을 제시하였다. 호우피해예상도에 IDW, TIN, Kriging 보간 알고리즘을 적용하여 계획빈도 및 상위빈도 이외의 빈도에 대한 피해위험구역을 표출 할 수 있다. 표출된 계획빈도 및 상위빈도 이외의 빈도를 지점확률강우량-빈도에 대한 Matching table을 통하여 실측 강우와 연계 가능하다. 본 연구 결과는 추후 풍수해피해예측시스템에 활용하여 재난관리단계별 예방 및 대응 단계에 활용 할 수 있을 것으로 판단된다.

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A Study on Implementation of Remote Control System using Wireless Technologies (무선통신을 이용한 원격제어 기술 구현)

  • Jang, Dong-won;Cho, In-Kwee
    • Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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    • 2016.10a
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    • pp.307-309
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    • 2016
  • This paper present about the system for sensing and controlling a wireless power transfer system using bluetooth protocol in robot, healthcare, smart-grid, and autonomous car. Recently a variety of applications using the Internet of Things (Internet of Things) and machine to machine (Machine to Machine) have been raised in many industries. To do this, it requires the fusion technology which is constituted with control, computing and networking. Embedded system is centered existing control system and Cyber Physical System(CPS) is the systems which was converged of a computing technologies using a wired or wireless network. CPS was adopted in the future government-led technology in the United States and Europe and is being pursued in cooperation with institutes, industries, and academia. In this paper, we implement and describe a technique for controlling the system for transmitting power wirelessly by sensing method using the matching of CPS technology concepts.

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A pilot study of an automated personal identification process: Applying machine learning to panoramic radiographs

  • Ortiz, Adrielly Garcia;Soares, Gustavo Hermes;da Rosa, Gabriela Cauduro;Biazevic, Maria Gabriela Haye;Michel-Crosato, Edgard
    • Imaging Science in Dentistry
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    • v.51 no.2
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    • pp.187-193
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    • 2021
  • Purpose: This study aimed to assess the usefulness of machine learning and automation techniques to match pairs of panoramic radiographs for personal identification. Materials and Methods: Two hundred panoramic radiographs from 100 patients (50 males and 50 females) were randomly selected from a private radiological service database. Initially, 14 linear and angular measurements of the radiographs were made by an expert. Eight ratio indices derived from the original measurements were applied to a statistical algorithm to match radiographs from the same patients, simulating a semi-automated personal identification process. Subsequently, measurements were automatically generated using a deep neural network for image recognition, simulating a fully automated personal identification process. Results: Approximately 85% of the radiographs were correctly matched by the automated personal identification process. In a limited number of cases, the image recognition algorithm identified 2 potential matches for the same individual. No statistically significant differences were found between measurements performed by the expert on panoramic radiographs from the same patients. Conclusion: Personal identification might be performed with the aid of image recognition algorithms and machine learning techniques. This approach will likely facilitate the complex task of personal identification by performing an initial screening of radiographs and matching ante-mortem and post-mortem images from the same individuals.

Design and Fabrication of DLP Array Antenna for 3.5 GHz Band (3.5 GHz 대역에서 동작하는 DLP 배열 안테나의 설계 및 제작)

  • Yoon, Joong-Han
    • The Journal of the Korea institute of electronic communication sciences
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    • v.16 no.6
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    • pp.1037-1044
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    • 2021
  • In this paper, we propose DLP(Dual Linear Polarization) array antenna for 3.5 GHz band. The proposed antenna has 1×4 array antenna and design two port network. A cross shape is inserted at the bottom of the patch for impedance matching. The size of each patch antenna is 18.85 mm(W1)×18.85 mm(L1), array antenna is designed on the FR-4 substrate, which is 236.0 mm(W)×60.2 mm(L), thickness (h) 1.6 mm, and the dielectric constant is 4.3. From the fabrication and measurement results, bandwidths of 70 MHz (3.54 to 3.61 GHz) for input port 1, 75 MHz (3.55 to 3.625 GHz) for input port 2 are obtained on the basis of -10 dB return loss and transmission coefficient S21 is under the -20 dB. Also, cross polarization between two port obtained.

Question Similarity Measurement of Chinese Crop Diseases and Insect Pests Based on Mixed Information Extraction

  • Zhou, Han;Guo, Xuchao;Liu, Chengqi;Tang, Zhan;Lu, Shuhan;Li, Lin
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.15 no.11
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    • pp.3991-4010
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    • 2021
  • The Question Similarity Measurement of Chinese Crop Diseases and Insect Pests (QSM-CCD&IP) aims to judge the user's tendency to ask questions regarding input problems. The measurement is the basis of the Agricultural Knowledge Question and Answering (Q & A) system, information retrieval, and other tasks. However, the corpus and measurement methods available in this field have some deficiencies. In addition, error propagation may occur when the word boundary features and local context information are ignored when the general method embeds sentences. Hence, these factors make the task challenging. To solve the above problems and tackle the Question Similarity Measurement task in this work, a corpus on Chinese crop diseases and insect pests(CCDIP), which contains 13 categories, was established. Then, taking the CCDIP as the research object, this study proposes a Chinese agricultural text similarity matching model, namely, the AgrCQS. This model is based on mixed information extraction. Specifically, the hybrid embedding layer can enrich character information and improve the recognition ability of the model on the word boundary. The multi-scale local information can be extracted by multi-core convolutional neural network based on multi-weight (MM-CNN). The self-attention mechanism can enhance the fusion ability of the model on global information. In this research, the performance of the AgrCQS on the CCDIP is verified, and three benchmark datasets, namely, AFQMC, LCQMC, and BQ, are used. The accuracy rates are 93.92%, 74.42%, 86.35%, and 83.05%, respectively, which are higher than that of baseline systems without using any external knowledge. Additionally, the proposed method module can be extracted separately and applied to other models, thus providing reference for related research.

Joint Reasoning of Real-time Visual Risk Zone Identification and Numeric Checking for Construction Safety Management

  • Ali, Ahmed Khairadeen;Khan, Numan;Lee, Do Yeop;Park, Chansik
    • International conference on construction engineering and project management
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    • 2020.12a
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    • pp.313-322
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    • 2020
  • The recognition of the risk hazards is a vital step to effectively prevent accidents on a construction site. The advanced development in computer vision systems and the availability of the large visual database related to construction site made it possible to take quick action in the event of human error and disaster situations that may occur during management supervision. Therefore, it is necessary to analyze the risk factors that need to be managed at the construction site and review appropriate and effective technical methods for each risk factor. This research focuses on analyzing Occupational Safety and Health Agency (OSHA) related to risk zone identification rules that can be adopted by the image recognition technology and classify their risk factors depending on the effective technical method. Therefore, this research developed a pattern-oriented classification of OSHA rules that can employ a large scale of safety hazard recognition. This research uses joint reasoning of risk zone Identification and numeric input by utilizing a stereo camera integrated with an image detection algorithm such as (YOLOv3) and Pyramid Stereo Matching Network (PSMNet). The research result identifies risk zones and raises alarm if a target object enters this zone. It also determines numerical information of a target, which recognizes the length, spacing, and angle of the target. Applying image detection joint logic algorithms might leverage the speed and accuracy of hazard detection due to merging more than one factor to prevent accidents in the job site.

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Development of Deep Learning-based Automatic Classification of Architectural Objects in Point Clouds for BIM Application in Renovating Aging Buildings (딥러닝 기반 노후 건축물 리모델링 시 BIM 적용을 위한 포인트 클라우드의 건축 객체 자동 분류 기술 개발)

  • Kim, Tae-Hoon;Gu, Hyeong-Mo;Hong, Soon-Min;Choo, Seoung-Yeon
    • Journal of KIBIM
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    • v.13 no.4
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    • pp.96-105
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    • 2023
  • This study focuses on developing a building object recognition technology for efficient use in the remodeling of buildings constructed without drawings. In the era of the 4th industrial revolution, smart technologies are being developed. This research contributes to the architectural field by introducing a deep learning-based method for automatic object classification and recognition, utilizing point cloud data. We use a TD3D network with voxels, optimizing its performance through adjustments in voxel size and number of blocks. This technology enables the classification of building objects such as walls, floors, and roofs from 3D scanning data, labeling them in polygonal forms to minimize boundary ambiguities. However, challenges in object boundary classifications were observed. The model facilitates the automatic classification of non-building objects, thereby reducing manual effort in data matching processes. It also distinguishes between elements to be demolished or retained during remodeling. The study minimized data set loss space by labeling using the extremities of the x, y, and z coordinates. The research aims to enhance the efficiency of building object classification and improve the quality of architectural plans by reducing manpower and time during remodeling. The study aligns with its goal of developing an efficient classification technology. Future work can extend to creating classified objects using parametric tools with polygon-labeled datasets, offering meaningful numerical analysis for remodeling processes. Continued research in this direction is anticipated to significantly advance the efficiency of building remodeling techniques.

Comparing the Benefits and Drawbacks of Stem Cell Therapy Based on the Cell Origin or Manipulation Process: Addressing Immunogenicity

  • Sung-Ho Chang;Chung Gyu Park
    • IMMUNE NETWORK
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    • v.23 no.6
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    • pp.44.1-44.16
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    • 2023
  • Mesenchymal stem cells (MSCs) are effective in treating autoimmune diseases and managing various conditions, such as engraftment of allogeneic islets. Additionally, autologous and HLA-matched allogeneic MSCs can aid in the engraftment of human allogeneic kidneys with or without low doses of tacrolimus, respectively. However, HLA alloantigens are problematic because cell therapy uses more HLA-mismatched allogeneic cells than autologous for convenience and standardization. In particular, HLA-mismatched MSCs showed increased Ag-specific T/B cells and reduced viability faster than HLA-matched MSCs. In CRISPR/Cas9-based cell therapy, Cas9 induce T cell activation in the recipient's immune system. Interestingly, despite their immunogenicity being limited to the cells with foreign Ags, the accumulation of HLA alloantigen-sensitized T/B cells may lead to allograft rejection, suggesting that alloantigens may have a greater scope of adverse effects than foreign Ags. To avoid alloantigen recognition, the β2-microglobulin knockout (B2MKO) system, eliminating class-I MHC, was able to avoid rejection by alloreactive CD8 T cells compared to controls. Moreover, universal donor cells in which both B2M and Class II MHC transactivator (CIITA) were knocked out was more effective in avoiding immune rejection than single KO. However, B2MKO and CIITA KO system remain to be controlled and validated for adverse effects such as the development of tumorigenicity due to deficient Ag recognition by CD8 T and CD4 T cells, respectively. Overall, better HLA-matching or depletion of HLA alloantigens prior to cell therapy can reduce repetitive transplantation through the long-term survival of allogeneic cell therapy, which may be especially important for patients seeking allogeneic transplantation.

CPW-Fed Super-wideband Semicircular-Disc-Shaped Dipole Antenna (CPW-급전 초광대역 반원-디스크-모양 다이폴 안테나)

  • Junho Yeo;Jong-Ig Lee
    • Journal of Advanced Navigation Technology
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    • v.28 no.3
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    • pp.356-361
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    • 2024
  • This paper deals with the design and fabrication of a coplanar waveguide (CPW)-fed super-wideband semicircular-disk-shaped dipole antenna operating in a frequency band of 2.4 GHz or higher. To feed the antenna, a CPW feed line was appended to the center of the lower arm of the semicircular-disk-shaped dipole antenna. For miniaturization, square patches were added to the ends of the two arms of the semicircular-disk-shaped dipole, whereas the slot width of the CPW feed line at the center of the dipole antenna was increased to improve impedance matching in the 5.4-6.3 GHz band. The simulated frequency band of the proposed antenna for a voltage standing wave ratio (VSWR) less than 2 was 2.369-30 GHz(170.7%), whereas the fabricated antenna was maintained VSWR less than 2 in the frequency range of 2.378-20 GHz when measured using a network analyzer operating up to 20 GHz so it can be applied as a super-wideband antenna for next-generation mobile communications.