Predict product-service convergence with ML methodology (2017)

SVM 기반 제조-서비스 기술 융합 예측
- 2017 대한산업공학회 추계학술대회

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1. SVM 기반 제조-서비스 기술 융합 예측 제6회 산업융합 활성화 방안 및 사례연구 논문공모전 서한빈¹, 이학연²* 서울과학기술대학교 {¹데이터사이언스학과, ²글로벌융합산업공학과} *교신저자, hylee@seoultech.ac.kr 발표자료 제출버전, 20171030 695
2. 목차 2 1. 서론 2. 선행 연구 2.1 제조-서비스 융합 2.2 기술융합 2.2 링크 예측 3. 연구 방법 3.1 연구 프레임워크 3.2 분석 데이터 3.3 기술융합 네트워크 구축 3.4 기술융합 예측모델 개발 4. 연구 결과 4.1 제조-서비스 기술융합 관계 탐색 4.2 제조-서비스 기술융합 관계 예측 5. 결론 696
3. 1. 서론 ➢ 연구 배경 ▪ 제조업과 서비스업 이질적인 특성 존재, 하지만 최근 제조-서비스 융합 가속화 ✓기존 제조업과 서비스업 혁신프로세스는 서로 역방향, 기술혁신의 수요-공급 관계 (Barras, 1986) ✓제조-서비스 기술융합 현상 → 제품 · 서비스 혁신 & 기업-고객 상호작용 방식에 변화 (Bitner, 2001; Auernhammer & Stabe, 2002; Geum et al., 2011; Geum et al., 2013) ✓대표적으로 PSS(Product Service System)가 있으며, “가치 창출을 위한 비즈니스 모델” 개념으로 발전 (서한 빈 & 이학연, 2017) ▪ → 비즈니스 환경에서 제조-서비스 융합을 위한 전략수립을 위해 기술수준의 제조-서비스 융합에 대한 정량 적인 예측이 필요 ➢ 연구 동기 ▪ 제조-서비스 기술융합 관계를 예측하기 위한 정량적인 방법론 개발이 필요 ✓네트워크(network) 형태로 기술 융합을 측정하고 시각화 하려는 시도 多 ▪ 최근 네트워크 동적변화를 포착하기 위해 링크 예측(Link Prediction) 방법을 활용 ➢ 연구 목적 ▪ 제조-서비스 기술융합 구조 정의 ▪ 제조-서비스 기술융합 관계 예측 ✓SVM(Support Vector Machine) 알고리즘을 이용한 링크 예측 적용 3 697
4. 2.1 제조-서비스 융합 ➢ 제조-서비스 융합 현상: 기술 관점 예측 필요 ▪ 제조-서비스 융합: 제조업과 서비스업의 상호 융합하는 현상 ✓IBM, General Electric, Xerox 등 글로벌 제조기업의 서비스화(servitization) 사례 (Martinez et al., 2010; Geum et al., 2011; Geum et al., 2013) ▪ 서비스화(servitization of manufacturing) 전략 → 제품-서비스 시스템(product service system: PSS) ✓PSS: 기획단계에서부터 제품과 서비스를 하나의 시스템으로 개발하는 개념 ✓PSS는 최근 ‘가치 창출을 위한 비즈니스 모델’ 개념으로 발전 (서한빈 & 이학연, 2017) ▪ 특히 기술수준 제조-서비스 융합 예측 필요 ✓제조-서비스 기술융합은 제품혁신 · 서비스혁신을 주도하며, 기업과 고객사이 상호작용 방식에 변화 (Bitner, 2001; Auernhammer & Stabe, 2002; Geum et al., 2011; Geum et al., 2013) ✓많은 기업들이 핵심적인 현상이라고 여기는 제품과 서비스 융합 현상은 기술에 의해 유발 (Bores et al., 2003; Geum et al., 2013) ✓→ 비즈니스 환경 변화에 대한 능동적 · 수동적 대응을 위한 기업들의 계획과 전략 수립이 요구 ✓→ 특히 기술 관점 제조-서비스 융합 예측은 전략수립 과정에서 유용한 단서로서 활용 가능 4 2. 선행 연구 (1/3) 698
5. 2.2 기술융합 ➢ 기술융합(Technological Convergence) 정의 및 측정기준 ▪ 기술융합 정의: ‘서로 각기 다른 기술이나 산업에서 서로 다른 두 개 이상의 분야가 시간의 흐름에 따라 경계 가 흐려지게 되거나 새로운 분야로 병합되는 현상’ (Curran & Leker, 2011; Karvonen & Kässi, 2011; Geum et al., 2012; 윤정환 & 금영 정, 2016) ▪ 기술융합 측정 대용지표(proxy): 특허 문서(patent document) ✓∵ 특허문서는 기술 및 상업적 지식의 원천 (Ernst, 2003; Geum et al., 2013) ▪ 기술융합 측정기준 ✓특허클래스 동시분류(Co-classification) 관계 (Curran & Leker, 2011; Geum et al., 2012; Geum et al., 2013; Preschitschek et al., 2013; Park & Yoon, 2014; Lee et al., 2015; 윤정환 & 금영정, 2016) ✓특허 인용(Citation) 관계 (박인채 & 윤병운, 2016) (잠재적인 기술융합 정의) ✓→ 특허클래스 동시분류 관계는 (기술개발이 완료된) 기술융합 관계라고 볼 수 있는 반면, 인용관계(or 지식흐름)에 의한 정보는 기술융합이 발생할 수 있는 조건(잠재 변수)으로 볼 수 있음 ➢ 제조-서비스 기술융합: ‘현황분석’에 머문다는 한계 존재 ▪ 제조-서비스 융합 기술수준 분석 거의 이루어지지 않음 ✓∵ ‘제조 기술’ 범위 매우 방대한 반면, ‘서비스 기술’에 대한 체계적인 정의 부재 (Lee et al., 2011; Geum et al., 2013) ▪ Business Method 특허를 기준으로 기술 수준의 제조-서비스 융합을 측정하려는 시도 존재 (Geum et al., 2013) ✓서비스 기술: USPC 705 클래스; 제조 기술: ‘Backward citation of Service Technology’ ✓제조-서비스 기술 융합(동시분류) 관계 동적변화에 초점 ↔ 제조-서비스 기술융합 예측 부재 5 2. 선행 연구 (2/3) 699
6. 2.3 링크 예측 ➢ 링크 예측(Link Prediction) 정의 및 구분 ▪ 링크 예측 정의: 현재 네트워크에서 새롭게 연결되거나, 해체되는 연결관계(링크)를 예측하는 문제 ▪ 링크 예측 구분: 유사도기반 접근법 Vs 학습기반 접근법 (Wang et al., 2015) ✓유사도기반 접근법(Similarity based approaches): 노드 쌍 유사도 계산법에 따라 측정기준(Measure) 구분; 특정 cutoff 이상 노드 관계 → 새롭게 연결될 것이라 예측 ✓학습기반 접근법(Learning based approaches): 연결여부를 예측하는 이진 분류(Binary Classification) 문제  → 유사도기반 접근법 +𝜶 (도메인 속성에 따른 추가 변수) ➢ 링크 예측을 활용한 기술융합 관계 예측: 기술융합 잠재속성 반영 X ▪ 기술융합 관계 예측을 목적으로 링크 예측 방법을 적용한 시도 존재 (Lee et al., 2015) ✓네트워크 이웃기반 유사도인 Adamic-Adar Coefficient(Adamic & Adar, 2003) 사용(유사도 기반 접근법) ✓→ 네트워크 내부속성(노드 이웃 관계) 외 기술융합과 직 · 간접적으로 관련된 추가 변수 반영 불가 6 2. 선행 연구 (3/3) ❖ [그림] 일반적인 링크 예측 프레임워크(Source: Wang et al., 2015) 700
7. 3.1 연구 프레임워크 ➢ 연구 프레임워크 7 특허 DB 구축 데이터셋 추출 데이터 정제 기술구조 탐색 예측모델 학습 기술융합 관계 예측 • 분석단위 동시분류/인용관계 추출 • ‘기술융합’ 매트릭스 구축 • 변수생성: 특허 인용관계 변수 • “기술융합” 네트워크 구축 • 변수생성: 이웃 노드 기반 네트워크 변수 • 모델링 데이터셋 구축 • 모델 최적화(최적 파라미터 탐색) • 최종 예측모델 적용 • 기술융합 예측결과 응용 3. 연구 방법 (1/8) 701
8. 3.2 분석 데이터 (1/3) ➢ 데이터 출처: USPTO Bulk dataset ▪ 10년(2007.1. ~ 2016.12.)간 등록된 utility 특허 대상 ➢ 데이터 기간 분할: 5년 + 5년 ▪ 과거 5년(2007.1. ~ 2011.12.; 60개월) ✓예측 모델 학습(입력변수) 목적 ▪ 최근 5년(2012.1. ~ 2016.12.; 60개월) ✓예측 모델 학습(목적변수) 목적 ✓기술융합 관계 예측(forecast) 목적 ➢ 분석 단위: IPC 4 digit subclass ▪ IPC는 수집기간 내 수집가능한 분류정보 ✓최근(2016년 이후) 특허문서에 USPC 미 분류 ✓한편 과거(2013년 이전) 특허문서에는 CPC 미 분류 ▪ IPC class 단위 특허 데이터 정제 필요 ✓ 1. 동시분류 관계(목적 변수) ✓ 2. IPC class 단위 인용관계 정보(입력 변수) 8 3. 연구 방법 (2/8) Source: https://developer.uspto.gov/product/patent-grant-full-text-dataxml#product-files (USPTO Bulk dataset) 5 years (2007.1~2011.12) 5 years (2012.1~2016.12) (2017.1~) Period 1 Period 2 Period 3 Modeling Prediction 702
9. 3.2 분석 데이터 (2/3) ➢ “서비스 기술” 정의: Business Method 특허인 USPC 705에 대응되는 IPC subclass 집합 ▪ 선행연구(Geum et al., 2013) 참고해, ‘서비스 기술’을 USPC 705 클래스로 정의 ▪ USPC 705 클래스 → G06Q 외 11개 IPC 서브클래스 매핑 ✓‘US to IPC Concordance’(Concordances between US Patent Classification and the International Patent Classification Eighth Edition) 참고; uspto.gov 제공 9 3. 연구 방법 (3/8) Source: https://www.uspto.gov/web/patents/classification/uspc705/us705toipc8.htm (US to IPC Concordance) Subclass Subclass Description G06Q Data processing systems or methods, specially adapted for administrative, commercial, financial, managerial, supervisory or forecasting purposes; Systems or methods specially adapted for administrative, commercial, financial, managerial, supervisory or forecasting purposes, not otherwise provided for G06F Electric digital data processing G07B Ticket-issuing apparatus; Taximeters; Arrangements or apparatus for collecting fares, tolls or entrance fees at one or more control points; Franking apparatus G07F Coin-freed or like apparatus G07G Registering the receipt of cash, valuables, or tokens G06G Analogue computers G01G Weighing G01R Measuring electric variables; Measuring magnetic variables G07C Time or attendance registers; Registering or indicating the working of machines; Generating random numbers; Voting or lottery apparatus; Arrangements, systems or apparatus for checking not provided for elsewhere A01K Animal husbandry; Care of birds, fishes, insects; Fishing; Rearing or breeding animals, not otherwise provided for; New breeds of animals B65B Machines, apparatus or devices for, or methods of, packaging articles or materials; Unpacking H04M Telephonic communication ❖ [표] “서비스 기술” IPC subclass description 703
10. 3.2 분석 데이터 (3/3) ➢ “제조 기술” 정의: ‘서비스 기술’과 동시분류 관계 갖는 IPC subclass 집합 ▪ 선행연구(Geum et al., 2013)에서는 ‘제조 기술’의 범위를 ‘서비스 기술‘과 관련된 기술 범위로 한정 ✓∵ 특허 영역에서 ‘제조 기술‘의 범위는 (‘서비스 기술’에 비해) 매우 방대함 ▪ 분석기간(10년) 동안 cutoff(500회) 이상 동시분류 관계 갖는 H04L 외 72개 IPC 서브클래스 한정 ✓한편, (1회 이상 동시분류 갖는) ‘제조 기술‘ 후보 서브클래스는 715개 ▪ → 분석대상 기술(서브클래스)는 총 85개; (서비스 기술 12개 + 제조 기술 73개) 10 3. 연구 방법 (4/8) ❖ [표] “제조 기술” IPC subclass description 예시 Subclass Subclass Description H01L Semiconductor devices; Electric solid state devices not otherwise provided for H04L Transmission of digital information, e.g. telegraphic communication H04N Pictorial communication, e.g. television H04W Wireless communication networks A61K Preparations for medical, dental, or toilet purposes A61B Diagnosis; Surgery; Identification G06K Recognition of data; Presentation of data; Record carriers; Handling record carriers H04B Transmission G01N Investigating or analysing materials by determining their chemical or physical properties G02B Optical elements, systems, or apparatus G09G Arrangements or circuits for control of indicating devices using static means to present variable information C12N Microorganisms or enzymes; Compositions thereof; Propagating, preserving, or maintaining microorganisms; Mutation or genetic engineering; Culture media 704
11. 3.3 기술융합 네트워크 구축 ➢ “기술 융합” 정의: 임계치 이상 동시분류 관계 갖는 서브클래스 쌍(subclass pair) ▪ 선행연구(Curran & Leker, 2011; Geum et al., 2012; Geum et al., 2013; Preschitschek et al., 2013; Park & Yoon, 2014; Lee et al., 2015) 참고해, ‘기술 융합’ 관계를 특허클래스 동시분류 관계로 정의 ▪ 단위 분석기간(5년) 내 cutoff(250회) 이상 동시분류 관계횟수를 기준으로 ‘기술 융합’ 발생여부 구분 ✓단위 분석기간 별, ‘기술 융합’은 각각 3.08%(2007.1.~2011.12.), 10.67%(2012.1.~2016.12.) 발생 ➢ “제조-서비스 기술 네트워크” 구축 과정 ▪ 1. 특허 단위 (분석 대상) 서브클래스 집계 ▪ 2. 서브클래스 동시분류 매트릭스 계산 ▪ 3. ‘기술 융합‘ cutoff 기준 동시분류 횟수 이분화 ▪ 4. 기술 네트워크 시각화 11 3. 연구 방법 (5/8) Matrix P Class A Class B Class C Patent a 1 0 1 Patent b 1 1 1 Patent c 0 1 0 Patent d 0 1 1 Patent e 0 1 1 Matrix C Class A Class B Class C Class A 2 1 2 Class B 1 4 3 Class C 2 3 4 Matrix C’ Class A Class B Class C Class A - 0 1 Class B - - 1 Class C - - - A C B 𝐶 = 𝑃𝑇𝑃 [Ex.] Cutoff=1.5 Visualization 705
12. 3.4 기술융합 예측모델 개발 (1/3) ➢ (이웃 노드 기반) “네트워크” 변수 그룹; 10개 변수 ▪ 𝛤(𝑥) : node x의 이웃 노드 집합 일 때 ✓CN (Common Neighbors): 𝐶𝑁 𝑥, 𝑦 = Γ(𝑥) ∩ Γ(𝑦) ✓JC (Jaccard Coefficient): 𝐽𝐶 𝑥, 𝑦 = Γ(𝑥)∩Γ(𝑦) Γ(𝑥)∪Γ(𝑦) ✓SI (Sorensen Index): 𝑆𝐼 𝑥, 𝑦 = Γ(𝑥)∩Γ(𝑦) Γ(𝑥) + Γ(𝑦) ✓SC (Salton Cosine Similarity): 𝑆𝐶 𝑥, 𝑦 = Γ(𝑥)∩Γ(𝑦) Γ(𝑥) × Γ(𝑦) ✓LHN (Leicht-Holme-Nerman)(Leicht et al., 2006): 𝐿𝐻𝑁 𝑥, 𝑦 = Γ(𝑥)∩Γ(𝑦) Γ(𝑥) × Γ(𝑦) ✓HP (Hub Promoted)(Ravasz et al., 2002): 𝐻𝑃 𝑥, 𝑦 = Γ(𝑥)∩Γ(𝑦) min( Γ 𝑥 , Γ(𝑦) ) ✓HD (Hub Depressed)(Zhou et al., 2009): 𝐻𝐷 𝑥, 𝑦 = Γ(𝑥)∩Γ(𝑦) max( Γ 𝑥 , Γ(𝑦) ) ✓PA (Perferential Attachment): 𝑃𝐴 𝑥, 𝑦 = Γ(𝑥) × Γ(𝑦) ✓AA (Adamic-Adar Coefficient)(Adamic & Adar, 2003): 𝐴𝐴 𝑥, 𝑦 = σ𝑧∈Γ(𝑥)∩Γ(𝑦) 1 log Γ(𝑧) ✓RA (Resource Allocation)(Zhou et al., 2009): 𝑅𝐴 𝑥, 𝑦 = σ𝑧∈Γ(𝑥)∩Γ(𝑦) 1 Γ(𝑧) ▪ → SVM 이용해, 다차원 공간에서 각 변수 별 cutoff 독립적으로 반영하는 효과 기대 12 3. 연구 방법 (6/8) 706
13. 3.4 기술융합 예측모델 개발 (2/3) ➢ (기술 수준) “인용 관계” 변수 그룹; 4개 변수 ▪ 동시 인용(Co-Citation, CC)(Small, 1973): 분석범위 문서(특허)들이 동시에 인용되는(cited) 관계 ✓Raw Frequency CC  CC관계 특허문서 사이에서 서브클래스 쌍(subclass pair) 집계 ✓Association Strength CC  Association Strength(Van Eck & Waltman, 2007): 𝑠𝑖𝑗 = 𝑐𝑖𝑗 𝑤𝑖𝑤𝑗 ▪ 서지 결합(Bibliographic Coupling, BC)(Kessler, 1963): 분석범위 문서(특허)들이 동시에 인용하는(citing) 관계 ✓Raw Frequency BC ✓Association Strength BC  이상, CC 프로세스와 동일 ▪ → 인용관계(지식흐름)에 의한 기술 사이 유사성(연관성)은 기술융합 발생할 수 있는 잠재조건 13 3. 연구 방법 (7/8) (Note) 𝑐𝑖𝑗 : i와 j 동시 출현 수, 𝑤𝑖 , 𝑤𝑗 는 각각 i, j의 출현 수 1 2 3 4 a c b ㄱ ㄷ ㄴ 𝑃𝑐𝑖𝑡𝑖𝑛𝑔 = 1 0 0 1 1 1 1 1 0 0 0 1 𝑃𝑐𝑖𝑡𝑒𝑑 = 1 1 0 1 0 0 1 0 1 0 1 1 𝐶𝐶𝑃 = 𝑃𝑇𝑃 = 1 1 1 2 1 0 2 0 1 2 0 0 3 1 1 1 𝐵𝐶𝑃 = 𝑃𝑃𝑇 = 1 1 1 3 1 0 2 1 1 2 0 1 2 0 0 1 Relation BC Relation CC (Note) node 1, 2, 3, 4: 분석범위 문서 (Note) Matrix P row: node 1, 2, 3, 4 Matrix P column: node ㄱ, ㄴ, ㄷ (Note) Matrix P row: node a, b, c Matrix P column: node 1, 2, 3, 4 707
14. 3.4 기술융합 예측모델 개발 (3/3) ➢ 모델링 데이터셋 구축 ▪ 입력변수: ‘인용관계‘ 4개 변수 & ‘네트워크’ 10개 변수 @ 1기간(2007.1.~2011.12.) ▪ 목적변수: 기술 네트워크 내 연결여부 @ 2기간(2012.1.~2016.12.) ▪ 샘플링기법: SMOTE(synthetic minority over-sampling technique) (Chawla et al., 2002) ✓∵ Imbalanced Data (True class rate: 10.67%) ➢ 예측 알고리즘: SVM(support vector machine) ▪ Soft Margin SVM (Cortes & Vapnik, 1995) ✓목적 함수(Primal Form): 𝑎𝑟𝑔𝑚𝑖𝑛(𝕨,𝑏) 1 2 𝕨 2 + 𝐶 σ𝑖 𝜉𝑖 ✓제약조건(Primal Form): 𝑦𝑖 𝕨 ∙ 𝕩𝑖 − 𝑏 ≥ 1 − 𝜉𝑖 , 𝜉𝑖 ≥ 0 ▪ 커널 함수: Gaussian(radial basis function) Kernel (Boser et al., 1992) ✓𝑘 𝕩, 𝕩′ = exp −𝛾 𝕩 − 𝕩′ 2 , (𝑤ℎ𝑒𝑟𝑒, 𝛾 > 0) ▪ → 탐색 파라미터: 𝐶 𝑀𝑖𝑠𝑐𝑙𝑎𝑠𝑠𝑖𝑓𝑖𝑐𝑎𝑡𝑖𝑜𝑛 𝑝𝑒𝑛𝑎𝑙𝑡𝑦 , 𝛾(𝐾𝑒𝑟𝑛𝑒𝑙 𝑐𝑜𝑒𝑓𝑓𝑖𝑐𝑖𝑒𝑛𝑡) 14 3. 연구 방법 (8/8) 708
15. 4.1 제조-서비스 기술융합 관계 탐색 (1/5) ➢ 제조-서비스 기술 네트워크: 1기간(2007.1.~2011.12) 15 4. 연구 결과 (1/8) ▪ 𝐍𝐞𝐭. 𝐃𝐞𝐧𝐬𝐢𝒕𝒚 = 𝟏𝟏𝟎 𝟖𝟓 𝑪 𝟐 = 𝟑. 𝟎𝟖% ▪ Avg. Degree = 2.59 G. Physics B. Performing Operations; Transporting H. Electricity F. Mechanical Engineering; Lighting; Heating; Weapons; Blasting C. Chemistry; Metallurgy A. Human Necessities 709
16. 4.1 제조-서비스 기술융합 관계 탐색 (2/5) ➢ 제조-서비스 기술 네트워크: 2기간(2012.1.~2016.12) 16 4. 연구 결과 (2/8) ▪ 𝐍𝐞𝐭. 𝐃𝐞𝐧𝐬𝐢𝒕𝒚 = 𝟑𝟖𝟏 𝟖𝟓 𝑪 𝟐 = 𝟏𝟎. 𝟔𝟕% ▪ Avg. Degree = 8.97 G. Physics B. Performing Operations; Transporting H. Electricity F. Mechanical Engineering; Lighting; Heating; Weapons; Blasting C. Chemistry; Metallurgy A. Human Necessities 710
17. 4.1 제조-서비스 기술융합 관계 탐색 (3/5) ➢ 서비스 기술 ‘기술융합’ 빈도 순위 ▪ → 특정 서비스 기술의 급격한 증가/감소는 보이지 않음(순위 변동 없음) ▪ → 데이터 처리와 관련된 G06F 기술은 일반화된 기술로 자리 잡고 있는 경향을 보임 17 4. 연구 결과 (3/8) 순위 서브클래스 서브클래스 설명 연결중심성 (1기간) 연결중심성 (2기간) 1 G06F Electric digital data processing 0.4048 0.7976 2 G01R Measuring electric variables; Measuring magnetic variables 0.0952 0.2857 3 H04M Telephonic communication 0.0714 0.2381 4 G06Q Data processing systems or methods, specially adapted for administrative, commercial, financial, managerial, supervisory or forecasting purposes; Systems or methods specially adapted for administrative, commercial, financial, managerial, supervisory or forecasting purposes, not otherwise provided for 0.0357 0.1786 5 G06G Analogue computers 0.0119 0.1071 6 G07F Coin-freed or like apparatus 0.0119 0.0833 7 A01K Animal husbandry; Care of birds, fishes, insects; Fishing; Rearing or breeding animals, not otherwise provided for; New breeds of animals 0.0000 0.0357 8 B65B Machines, apparatus or devices for, or methods of, packaging articles or materials; Unpacking 0.0000 0.0238 9 G01G Weighing 0.0000 0.0238 10 G07B Ticket-issuing apparatus; Taximeters; Arrangements or apparatus for collecting fares, tolls or entrance fees at one or more control points; Franking apparatus 0.0000 0.0119 11 G07C Time or attendance registers; Registering or indicating the working of machines; Generating random number s; Voting or lottery apparatus; Arrangements, systems or apparatus for checking not provided for elsewhere 0.0000 0.0000 12 G07G Registering the receipt of cash, valuables, or tokens 0.0000 0.0000 ❖ [표] “서비스 기술” 연결중심성 순위 711
18. 4.1 제조-서비스 기술융합 관계 탐색 (4/5) ➢ 제조 기술 ‘기술융합‘ 빈도 순위 ▪ → G08B, H04W, G01C 기술은 최근 기술융합이 활발한 제조기술이라 볼 수 있음(상위10 진입) ▪ → 한편 H04J, G09G, H04Q 기술은 최근 기술융합이 침체한 제조기술이라 볼 수 있음(상위10 퇴출) 18 4. 연구 결과 (4/8) ❖ [표] “제조 기술” 연결중심성 상위10: 1기간(2007.1.~2011.12.) 순위 서브 클래스 서브클래스 설명 연결 중심성 1 H04L Transmission of digital information, e.g. telegraphic commu nication 0.1548 2 H04N Pictorial communication, e.g. television 0.1429 3 G06K Recognition of data; Presentation of data; Record carriers; H andling record carriers 0.1190 3 H04B Transmission 0.1190 5 G01N Investigating or analysing materials by determining their ch emical or physical properties 0.0952 5 H01L Semiconductor devices; Electric solid state devices not other wise provided for 0.0952 7 H04J Multiplex communication 0.0833 8 A61B Diagnosis; Surgery; Identification 0.0714 8 G02B Optical elements, systems, or apparatus 0.0714 8 G09G Arrangements or circuits for control of indicating devices using static means to present variable information 0.0714 8 H04Q Selecting 0.0714 ❖ [표] “제조 기술” 연결중심성 상위10: 2기간(2012.1.~2016.12.) 순위 서브 클래스 서브클래스 설명 연결 중심성 1 H04N Pictorial communication, e.g. television 0.3929 2 G06K Recognition of data; Presentation of data; Record carriers; Handling record carriers 0.3571 3 H04L Transmission of digital information, e.g. telegraphic communication 0.3333 4 H04B Transmission 0.2857 5 G01N Investigating or analysing materials by determining their chemical or physical properties 0.2381 5 G08B Signalling or calling systems; Order telegraphs; Alarm systems 0.2381 7 H04W Wireless communication networks 0.2262 8 G02B Optical elements, systems, or apparatus 0.2024 8 H01L Semiconductor devices; Electric solid state devices not other wise provided for 0.2024 10 A61B Diagnosis; Surgery; Identification 0.1786 10 G01C Measuring distances, levels or bearings; Surveying; Navigation; Gyroscopic instruments; Photogrammetry or videogrammetry 0.1786 712
19. 4.1 제조-서비스 기술융합 관계 탐색 (5/5) ➢ 신생 기술융합 관계 탐색 ▪ 제조-서비스 신생 기술융합 관계: 84쌍 발견 ▪ 응용분야 예시 19 4. 연구 결과 (5/8) Applications Service subclass Mfg. subclass Service description Mfg. description Case A. G06F B60T Electric digital data processing Vehicle brake control systems or parts thereof; Brake control systems or parts thereof, in general; … F16H Gearing Case B. G06Q H04L Data processing systems or methods, specially adapted for …; Systems or methods specially adapted for a… Transmission of digital information, e.g. telegraphic communication H04W Wireless communication networks ❖ [표] ‘제조-서비스’ 신생 기술융합 관계, 응용분야 예시 ✓ Case A. 자율주행 차량 제어 ✓ Case B. 클라우드 컴퓨팅 기술 및 서비스 Figure Source: Case A.(Jo et al., 2014); Case B.(Cloud Computing from Wikipedia, Image created by Sam Johnston, 2009) 713
20. 4.2 제조-서비스 기술융합 관계 예측 (1/3) ➢ 모델 최적화(파라미터 탐색) 변수 ▪ 모델 평가기준(목적변수, max 𝐹𝛽 ): 𝐹𝛽 = 1 + 𝛽2 𝑝𝑟𝑒𝑐𝑖𝑠𝑖𝑜𝑛×𝑟𝑒𝑐𝑎𝑙𝑙 𝛽2𝑝𝑟𝑒𝑐𝑖𝑠𝑖𝑜𝑛+𝑟𝑒𝑐𝑎𝑙𝑙 (𝑤ℎ𝑒𝑟𝑒, 𝛽 = 0.1) ▪ 탐색 파라미터(독립변수) ✓Misclassification penalty 𝐶 ∈ 10−3, 10−2, ⋯ , 102, 103 ✓Kernel coefficient 𝛾 ∈ {10−3, 10−2, ⋯ , 102, 103} ▪ 최종 모델 평가점수: 𝟎. 𝟗𝟒𝟗𝟑 ± 𝟎. 𝟎𝟎𝟔𝟓 ✓모델 학습/평가 방식: Stratified K-Fold Cross Validation (𝑘 = 5) 20 4. 연구 결과 (6/8) 순위 Parameter 𝑪 Parameter 𝜸 평가점수_평균 평가점수_표준편차 1 100 10 0.9493 0.0065 2 100 100 0.9491 0.0064 3 1000 100 0.9468 0.0047 4 10 100 0.9459 0.0084 5 1000 10 0.9456 0.0049 6 10 10 0.9358 0.0102 7 1 100 0.9346 0.0082 8 1000 1 0.9341 0.0076 … … … … … 49 0.001 1000 0.7641 0.0066 ❖ [표] 모델 평가점수 결과 714
21. 4.2 제조-서비스 기술융합 관계 예측 (2/3) ➢ 제조-서비스 기술 네트워크: 3기간(예측, 2017.1.~) 21 4. 연구 결과 (7/8) ▪ 𝐍𝐞𝐭. 𝐃𝐞𝐧𝐬𝐢𝒕𝒚 = 𝟖𝟕𝟑 𝟖𝟓 𝑪 𝟐 = 𝟐𝟒. 𝟒𝟓% ▪ Avg. Degree = 20.54 G. Physics B. Performing Operations; Transporting H. Electricity F. Mechanical Engineering; Lighting; Heating; Weapons; Blasting C. Chemistry; Metallurgy A. Human Necessities 715
22. 4.2 제조-서비스 기술융합 관계 예측 (3/3) ➢ 신생 기술융합 관계 예측 ▪ 제조-서비스 신생 기술융합 관계: 132쌍 예상[부록 첨부] ▪ 예상 응용분야 예시 ✓인공지능 적용 가능 제조-서비스 융합분야(AI 의학/헬스케어, 3D 프린팅 기술) 22 4. 연구 결과 (8/8) Applications Service subclass Mfg. subclass Service description Mfg. description AI 의학/헬스케어 G06G A61B Analogue computers Diagnosis; Surgery; Identification G06F A61K Electric digital data processing Preparations for medical, dental, or toilet purposes 3D 프린팅 G06F B29C Electric digital data processing Shaping or joining of plastics; Shaping of material in a plastic state, not otherwise provided for; After-treatment of the shaped products, e.g. repairing G06Q B41J Data processing systems or methods, specially adapted for administ rative, commercial, financial, managerial, supervisory or forecasting purposes; Systems or methods specially adapted for administrative, commercial, financial, managerial, supervisory or forecasting purpos es, not otherwise provided for Typewriters; Selective printing mechanisms, i.e. mechanisms printing otherwise than from a forme; Correction of typographical errors ❖ [표] ‘제조-서비스’ 신생 기술융합 예측 관계, 응용분야 예시 • Figure Source: https://www.cygnismedia.com/blog/how-artificial-intelligence-transforming-modern-healthcare/ (AI의학/헬스케어, 左); https://3dprint.com/82272/what-3d-printing-works/ (3D프린팅, 右); https://www.forbes.com/sites/falonfatemi/2017/07/26/these-5-fields-will-be-the-first-hotbeds-for-artificial-intelligence/#43d4b6ed7110 (AI, 中) 716
23. 5. 결론 ➢ 연구 요약 ▪ 제조-서비스 융합현상을 기술 관점에서 분석하고, 향후 융합관계를 예측 ✓1. 제조-서비스 기술 네트워크 구축  특허 IPC 동시분류 관계 기준 ✓2. SVM 알고리즘을 이용한 기술융합 관계 예측 모델 개발  Common Neighbors, Jaccard Coefficient, Adamic-Adar Coefficient 등 이웃 노드 기반 네트워크 변수  동시인용(co-citation), 서지결합(bibliographic coupling)과 같은 인용 관계 변수 ➢ 연구 의의 ▪ “제조-서비스” 기술융합 관계에 대한 실증적인 분석에서 나아가, 관계 변화에 대해 예측 ▪ 네트워크 속성 뿐만 아니라, ‘기술융합‘의 잠재속성인 인용관계 정보를 반영한 링크예측 모델 개발 ➢ 한계점 및 향후 연구 ▪ 한계점 ✓분석 범위가 한정적이기 때문에, 새롭게 포함되는 기술을 포함한 구조를 반영하는데 한계 ✓연결여부를 판단하는 단순 이진분류 문제이기 때문에, 중요 관계를 파악하는데 어려움 ▪ 향후 연구 ✓분석 범위에 대한 제한하지 않고, 분석 모집단을 확장해 기술융합 관계에 대해 분석 ✓이분화 된 네트워크 대신, Weighted Edge 값을 갖는 네트워크에 기반해 예측 모델 개발 23 717
24. 24 ❖ 참고문헌 (1/2) • 박인채, 윤병운. (2016). 잠재적 융합관계 정의를 통한 기술융합 연구테마 예측. 대한산업공학회 춘계공동학술대회 논문집, , 5230-5246. • 서한빈, 이학연. (2017). 제품서비스시스템(PSS) 연구 동향. 대한산업공학회 춘계공동학술대회 논문집, , 997-1017. • 윤정환, 금영정. (2016). 특허 정보 동시분류분석을 통한 기술융합의 동태적 분석방법에 관한 연구. 대한산업공학회 추계학술대회 논문집, , 383-391. • Adamic, L. A., & Adar, E. (2003). Friends and neighbors on the web. Social networks, 25(3), 211-230. • Aiello, L. M., Barrat, A., Schifanella, R., Cattuto, C., Markines, B., & Menczer, F. (2012). Friendship prediction and homophily in social media. ACM Transactions on the Web (TWEB), 6(2), 9. • Auernhammer, K. & Stabe, M. (2002). Integrated development of products and services, In: Mařík, V., Camarinha-Matos, L., and Afsarmanesh, H. (Eds), Knowledge and Technology Integration in Production and Services: Balancing Knowledge and Technology in Product and Service Life Cycle, Springer • Barras, R. (1986). Towards a theory of innovation in services. Research policy, 15(4), 161-173. • Bitner, M. J. (2001). Service and technology: opportunities and paradoxes. Managing Service Quality, 11(6), 375-379. • Bores, C., Saurina, C. & Torres, R. (2003). Technological convergence: a strategic perspective, Technovation, 23(1), 1-13. • Boser, B. E., Guyon, I. M., & Vapnik, V. N. (1992, July). A training algorithm for optimal margin classifiers. In Proceedings of the fifth annual workshop on Computational learning theory (pp. 144-152). ACM. • Chawla, N. V., Bowyer, K. W., Hall, L. O., & Kegelmeyer, W. P. (2002). SMOTE: synthetic minority over-sampling technique. Journal of artificial intelligence research, 16, 321-357. • Cortes, C., & Vapnik, V. (1995). Support-vector networks. Machine learning, 20(3), 273-297. • Curran, C. S., & Leker, J. (2011). Patent indicators for monitoring convergence–examples from NFF and ICT. Technological Forecasting and Social Change, 78(2), 256-273. • Ernst, H. (2003). Patent information for strategic technology management. World patent information, 25(3), 233-242. • Geum, Y., Lee, S., Kang, D. & Park, Y. (2011). The customization framework for road mapping product-service integration. Service Business, 5(3), 213-236. • Geum, Y., Kim, C., Lee, S., & Kim, M. S. (2012). Technological convergence of IT and BT: evidence from patent analysis. Etri Journal, 34(3), 439-449. • Geum, Y., Kim, M. S., Park, Y., & Lee, S. (2013). The Convergence of Manufacturing and Service Technologies: A Patent Analysis Approach. Information Management and Business Review, 5(2), 99. • Grupp, H. (1996). Spillover effects and the science base of innovations reconsidered: an empirical approach. Journal of Evolutionary Economics, 6(2), 175- 197. • Hanslmayr, S., Leipold, P., & Bäuml, K. H. (2010). Anticipation boosts forgetting of voluntarily suppressed memories. Memory, 18(3), 252-257. • Karvonen, M., & Kässi, T. (2011). Patent analysis for analysing technological convergence. foresight, 13(5), 34-50. • Kessler, M. M. (1963). Bibliographic coupling between scientific papers. Journal of the Association for Information Science and Technology, 14(1), 10-25. • Jo, K., Kim, J., Kim, D., Jang, C., & Sunwoo, M. (2014). Development of autonomous car—Part I: Distributed system architecture and development process. IEEE Transactions on Industrial Electronics, 61(12), 7131-7140. 718
25. 25 ❖ 참고문헌 (2/2) • Lee, S., Geum, Y., Kim, M. S. & Kim, J. (2011). How technologies can facilitate service innovation? The Proceedings of the 4th ISPIM Innovation Symposium, Wellington, New Zealand • Lee, W. S., Han, E. J., & Sohn, S. Y. (2015). Predicting the pattern of technology convergence using big-data technology on large-scale triadic patents. Technological Forecasting and Social Change, 100, 317-329. • Leicht, E. A., Holme, P., & Newman, M. E. (2006). Vertex similarity in networks. Physical Review E, 73(2), 026120. • Martinez, V., Bastl, M., Kingston, J. & Evan, S. (2010). Challenges in transforming manufacturing organizations into product-service providers. Journal of Manufacturing Technology Management, 21, 449-469. • Mori, J., Kajikawa, Y., Kashima, H., & Sakata, I. (2012). Machine learning approach for finding business partners and building reciprocal relationships. Expert Systems with Applications, 39(12), 10402-10407. • Park, H., & Yoon, J. (2014). Assessing coreness and intermediarity of technology sectors using patent co-classification analysis: the case of Korean national R&D. Scientometrics, 98(2), 853-890. • Preschitschek, N., Niemann, H., Leker, J., & G. Moehrle, M. (2013). Anticipating industry convergence: semantic analyses vs IPC co-classification analyses of patents. foresight, 15(6), 446-464. • Ravasz, E., Somera, A. L., Mongru, D. A., Oltvai, Z. N., & Barabási, A. L. (2002). Hierarchical organization of modularity in metabolic networks. science, 297(5586), 1551-1555. • Small, H. (1973). Co‐citation in the scientific literature: A new measure of the relationship between two documents. Journal of the Association for Information Science and Technology, 24(4), 265-269. • Tang, J., Wu, S., Sun, J., & Su, H. (2012, August). Cross-domain collaboration recommendation. In Proceedings of the 18th ACM SIGKDD international conference on Knowledge discovery and data mining (pp. 1285-1293). ACM. • Van Eck, N. J., & Waltman, L. (2007). VOS: A new method for visualizing similarities between objects. In Advances in data analysis (pp. 299-306). Springer, Berlin, Heidelberg. • Wang, P., Xu, B., Wu, Y., & Zhou, X. (2015). Link prediction in social networks: the state-of-the-art. Science China Information Sciences, 58(1), 1-38. • Wu, S., Sun, J., & Tang, J. (2013, February). Patent partner recommendation in enterprise social networks. In Proceedings of the sixth ACM international conference on Web search and data mining (pp. 43-52). ACM. • Zhou, T., Lü, L., & Zhang, Y. C. (2009). Predicting missing links via local information. The European Physical Journal B-Condensed Matter and Complex Systems, 71(4), 623-630. 719
26. 26 ❖ 부록: ‘제조-서비스’ 신생 기술융합 예측 관계 (1/3) No. Service subclass Mfg. subclass Service description Mfg. description 1 A01K A61B Animal husbandry; Care of birds, fishes, insects; Fishing; Rearing or breeding animals, not other wise provided for; New breeds of animals Diagnosis; Surgery; Identification 2 A61K Preparations for medical, dental, or toilet purposes 3 C12Q Measuring or testing processes involving enzymes or microorganisms; Compositions or test papers therefor; Processes of preparing such compositions; Condition-responsive control in microbiological or e nzymological processes 4 B65B A61K Machines, apparatus or devices for, or methods of, packaging articles or materials; Unpacking Preparations for medical, dental, or toilet purposes 5 A61M Devices for introducing media into, or onto, the body; Devices for transducing body media or for taking media from the body; Devices for producing or ending sleep or stupor 6 B29C Shaping or joining of plastics; Shaping of material in a plastic state, not otherwise provided for; After-treatment of the shaped products, e.g. repairing 7 G01G B60R Weighing Vehicles, vehicle fittings, or vehicle parts, not otherwise provided for 8 G01F Measuring volume, volume flow, mass flow, or liquid level; Metering by volume 9 G01R A61M Measuring electric variables; Measuring magnetic variables Devices for introducing media into, or onto, the body; Devices for transducing body media or for taking media from the body; Devices for producing or ending sleep or stupor 10 A63F Card, board or roulette games; Indoor games using small moving playing bodies; Video games; Games not otherwise provided for 11 B41J Typewriters; Selective printing mechanisms, i.e. mechanisms printing otherwise than from a forme; Correction of typographical errors 12 B60R Vehicles, vehicle fittings, or vehicle parts, not otherwise provided for 13 B60T Vehicle brake control systems or parts thereof; Brake control systems or parts thereof, in general; Arrangement of braking elements on vehicles in general; Portable devices for preventing unwanted move ment of vehicles; Vehicle modifications to facilitate cooling of brakes 14 F16H Gearing 15 C12Q Measuring or testing processes involving enzymes or microorganisms; Compositions or test papers therefor; Processes of preparing such compositions; Condition-responsive control in microbiological or e nzymological processes 16 F02D Controlling combustion engines 17 G01C Measuring distances, levels or bearings; Surveying; Navigation; Gyroscopic instruments; Photogrammetry or videogrammetry 18 G01L Measuring force, stress, torque, work, mechanical power, mechanical efficiency, or fluid pressure 19 G01S Radio direction-finding; Radio navigation; Determining distance or velocity by use of radio waves; Locating or presence-detecting by use of the reflection or reradiation of radio waves; Analogous arrange ments using other waves 20 G03B Apparatus or arrangements for taking photographs or for projecting or viewing them; Apparatus or arrangements employing analogous techniques using waves other than optical waves; Accessories there for 21 G03F Photomechanical production of textured or patterned surfaces, e.g. for printing, for processing of semiconductor devices; Materials therefor; Originals therefor; Apparatus specially adapted therefor 22 G03G Electrography; Electrophotography; Magnetography 23 G05B Control or regulating systems in general; Functional elements of such systems; Monitoring or testing arrangements for such systems or elements 24 G05F Systems for regulating electric or magnetic variables 25 G06N Computer systems based on specific computational models 26 G06T Image data processing or generation, in general 27 G07D Handling of coins or of paper currency or similar valuable papers, e.g. testing, sorting by denominations, counting, dispensing, changing or depositing 28 G08G Traffic control systems 29 G09B Educational or demonstration appliances; Appliances for teaching, or communicating with, the blind, deaf or mute; Models; Planetaria; Globes; Maps; Diagrams 30 G09G Arrangements or circuits for control of indicating devices using static means to present variable information 31 G10L Speech analysis or synthesis; Speech recognition; Speech or voice processing; Speech or audio coding or decoding 32 H01R Electrically-conductive connections; Structural associations of a plurality of mutually-insulated electrical connecting elements; Coupling devices; Current collectors 33 H02M Apparatus for conversion between ac and ac, between ac and dc, or between dc and dc, and for use with mains or similar power supply systems; Conversion of dc or ac input power into surge output po wer; Control or regulation thereof 34 H03M Coding, decoding or code conversion, in general 35 H04H Broadcast communication 36 H04K Secret communication; Jamming of communication 37 H04Q Selecting 38 H05K Printed circuits; Casings or constructional details of electric apparatus; Manufacture of assemblages of electrical components 39 G06F A61K Electric digital data processing Preparations for medical, dental, or toilet purposes 40 B29C Shaping or joining of plastics; Shaping of material in a plastic state, not otherwise provided for; After-treatment of the shaped products, e.g. repairing 41 B65D Containers for storage or transport of articles or materials, e.g. bags, barrels, bottles, boxes, cans, cartons, crates, drums, jars, tanks, hoppers, forwarding containers; Accessories, closures, or fittings therefor ; Packaging elements; Packages 42 C12N Microorganisms or enzymes; Compositions thereof; Propagating, preserving, or maintaining microorganisms; Mutation or genetic engineering; Culture media 43 C12Q Measuring or testing processes involving enzymes or microorganisms; Compositions or test papers therefor; Processes of preparing such compositions; Condition-responsive control in microbiological or e nzymological processes 720
27. 27 ❖ 부록: ‘제조-서비스’ 신생 기술융합 예측 관계 (2/3) No. Service subclass Mfg. subclass Service description Mfg. description 44 G06F G07D Electric digital data processing Handling of coins or of paper currency or similar valuable papers, e.g. testing, sorting by denominations, counting, dispensing, changing or depositing 45 H01M Processes or means, e.g. batteries, for the direct conversion of chemical energy into electrical energy 46 H01Q Aerials 47 H02H Emergency protective circuit arrangements 48 G06G A61B Analogue computers Diagnosis; Surgery; Identification 49 B25J Manipulators; Chambers provided with manipulation devices 50 B60K Arrangement or mounting of propulsion units or of transmissions in vehicles; Arrangement or mounting of plural diverse prime-movers in vehicles; Auxiliary drives for vehicles; Instrumentation or dashboa rds for vehicles; Arrangements in connection with cooling, air intake, gas exhaust or fuel supply of propulsion units in vehicles 51 B65G Transport or storage devices, e.g. conveyors for loading or tipping, shop conveyor systems or pneumatic tube conveyors 52 G01D Measuring not specially adapted for a specific variable; Arrangements for measuring two or more variables not covered by a single other subclass; Tariff metering apparatus; Transferring or transducing arr angements not specially adapted for a specific variable; Measuring or testing not otherwise provided for 53 G01F Measuring volume, volume flow, mass flow, or liquid level; Metering by volume 54 G01S Radio direction-finding; Radio navigation; Determining distance or velocity by use of radio waves; Locating or presence-detecting by use of the reflection or reradiation of radio waves; Analogous arrange ments using other waves 55 G05B Control or regulating systems in general; Functional elements of such systems; Monitoring or testing arrangements for such systems or elements 56 G05D Systems for controlling or regulating non-electric variables 57 G06E Optical computing devices 58 G06T Image data processing or generation, in general 59 G06Q A61M Data processing systems or methods, specially a dapted for administrative, commercial, financial, managerial, supervisory or forecasting purposes; Systems or methods specially adapted for admin istrative, commercial, financial, managerial, super visory or forecasting purposes, not otherwise pr ovided for Devices for introducing media into, or onto, the body; Devices for transducing body media or for taking media from the body; Devices for producing or ending sleep or stupor 60 B41J Typewriters; Selective printing mechanisms, i.e. mechanisms printing otherwise than from a forme; Correction of typographical errors 61 B60Q Arrangement of signalling or lighting devices, the mounting or supporting thereof or circuits therefor, for vehicles in general 62 B60W Conjoint control of vehicle sub-units of different type or different function; Control systems specially adapted for hybrid vehicles; Road vehicle drive control systems for purposes not related to the control of a particular sub-unit 63 B65G Transport or storage devices, e.g. conveyors for loading or tipping, shop conveyor systems or pneumatic tube conveyors 64 F02D Controlling combustion engines 65 B60R Vehicles, vehicle fittings, or vehicle parts, not otherwise provided for 66 F16H Gearing 67 G01B Measuring length, thickness or similar linear dimensions; Measuring angles; Measuring areas; Measuring irregularities of surfaces or contours 68 G01F Measuring volume, volume flow, mass flow, or liquid level; Metering by volume 69 G01N Investigating or analysing materials by determining their chemical or physical properties 70 G01P Measuring linear or angular speed, acceleration, deceleration or shock; Indicating presence or absence of movement; Indicating direction of movement 71 G01S Radio direction-finding; Radio navigation; Determining distance or velocity by use of radio waves; Locating or presence-detecting by use of the reflection or reradiation of radio waves; Analogous arrange ments using other waves 72 G01V Geophysics; Gravitational measurements; Detecting masses or objects; Tags 73 G02B Optical elements, systems, or apparatus 74 G03B Apparatus or arrangements for taking photographs or for projecting or viewing them; Apparatus or arrangements employing analogous techniques using waves other than optical waves; Accessories there for 75 G03F Photomechanical production of textured or patterned surfaces, e.g. for printing, for processing of semiconductor devices; Materials therefor; Originals therefor; Apparatus specially adapted therefor 76 G08C Transmission systems for measured values, control or similar signals 77 G09G Arrangements or circuits for control of indicating devices using static means to present variable information 78 G10L Speech analysis or synthesis; Speech recognition; Speech or voice processing; Speech or audio coding or decoding 79 H01H Electric switches; Relays; Selectors; Emergency protective devices 80 H01L Semiconductor devices; Electric solid state devices not otherwise provided for 81 H01Q Aerials 82 H01R Electrically-conductive connections; Structural associations of a plurality of mutually-insulated electrical connecting elements; Coupling devices; Current collectors 83 H03K Pulse technique 84 H03M Coding, decoding or code conversion, in general 85 H04J Multiplex communication 86 H04Q Selecting 87 H04R Loudspeakers, microphones, gramophone pick-ups or like acoustic electromechanical transducers; Deaf-aid sets; Public address systems 88 H05K Printed circuits; Casings or constructional details of electric apparatus; Manufacture of assemblages of electrical components 721
28. 28 ❖ 부록: ‘제조-서비스’ 신생 기술융합 예측 관계 (3/3) No. Service subclass Mfg. subclass Service description Mfg. description 89 G07B A63F Ticket-issuing apparatus; Taximeters; Arr angements or apparatus for collecting f ares, tolls or entrance fees at one or mo re control points; Franking apparatus Card, board or roulette games; Indoor games using small moving playing bodies; Video games; Games not otherwise provided for 90 G07D Handling of coins or of paper currency or similar valuable papers, e.g. testing, sorting by denominations, counting, dispensing, changing or depositing 91 G09B Educational or demonstration appliances; Appliances for teaching, or communicating with, the blind, deaf or mute; Models; Planetaria; Globes; Maps; Diagrams 92 H04B Transmission 93 H04N Pictorial communication, e.g. television 94 G07C A61B Time or attendance registers; Registerin g or indicating the working of machines; Generating random numbers; Voting or lottery apparatus; Arrangements, system s or apparatus for checking not provide d for elsewhere Diagnosis; Surgery; Identification 95 B25J Manipulators; Chambers provided with manipulation devices 96 B60T Vehicle brake control systems or parts thereof; Brake control systems or parts thereof, in general; Arrangement of braking elements on vehicles in general; Portable devices for preventing unwanted movement of vehicles; Vehicle modifications to facilitate cooling of brakes 97 G01C Measuring distances, levels or bearings; Surveying; Navigation; Gyroscopic instruments; Photogrammetry or videogrammetry 98 G01N Investigating or analysing materials by determining their chemical or physical properties 99 G01S Radio direction-finding; Radio navigation; Determining distance or velocity by use of radio waves; Locating or presence-detecting by use of the reflection or reradiation of radio waves; Analogous arrangements us ing other waves 100 G06T Image data processing or generation, in general 101 G08G Traffic control systems 102 H02J Circuit arrangements or systems for supplying or distributing electric power; Systems for storing electric energy 103 H04B Transmission 104 H04N Pictorial communication, e.g. television 105 H04Q Selecting 106 G07F A61B Coin-freed or like apparatus Diagnosis; Surgery; Identification 107 G01S Radio direction-finding; Radio navigation; Determining distance or velocity by use of radio waves; Locating or presence-detecting by use of the reflection or reradiation of radio waves; Analogous arrangements us ing other waves 108 G06N Computer systems based on specific computational models 109 G06T Image data processing or generation, in general 110 G08B Signalling or calling systems; Order telegraphs; Alarm systems 111 H04B Transmission 112 H04N Pictorial communication, e.g. television 113 H04W Wireless communication networks 114 H04M B41J Telephonic communication Typewriters; Selective printing mechanisms, i.e. mechanisms printing otherwise than from a forme; Correction of typographical errors 115 B60T Vehicle brake control systems or parts thereof; Brake control systems or parts thereof, in general; Arrangement of braking elements on vehicles in general; Portable devices for preventing unwanted movement of vehicles; Vehicle modifications to facilitate cooling of brakes 116 F02D Controlling combustion engines 117 F16H Gearing 118 G01C Measuring distances, levels or bearings; Surveying; Navigation; Gyroscopic instruments; Photogrammetry or videogrammetry 119 G01N Investigating or analysing materials by determining their chemical or physical properties 120 G01S Radio direction-finding; Radio navigation; Determining distance or velocity by use of radio waves; Locating or presence-detecting by use of the reflection or reradiation of radio waves; Analogous arrangements us ing other waves 121 G01V Geophysics; Gravitational measurements; Detecting masses or objects; Tags 122 G02B Optical elements, systems, or apparatus 123 G02F Devices or arrangements, the optical operation of which is modified by changing the optical properties of the medium of the devices or arrangements for the control of the intensity, colour, phase, polarisation or direction of light, e.g. switching, gating, modulating or demodulating; Techniques or procedures for the operation thereof; Frequency-changing; Non-linear optics; Optical logic elements; Optical analogue/digital c onverters 124 G03B Apparatus or arrangements for taking photographs or for projecting or viewing them; Apparatus or arrangements employing analogous techniques using waves other than optical waves; Accessories therefor 125 G05B Control or regulating systems in general; Functional elements of such systems; Monitoring or testing arrangements for such systems or elements 126 G06T Image data processing or generation, in general 127 G08C Transmission systems for measured values, control or similar signals 128 G08G Traffic control systems 129 G11C Static stores 130 H01H Electric switches; Relays; Selectors; Emergency protective devices 131 H01L Semiconductor devices; Electric solid state devices not otherwise provided for 132 H02J Circuit arrangements or systems for supplying or distributing electric power; Systems for storing electric energy 722