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    μΆœν•˜μ€‘λŸ‰κ³Ό ν™”λ¬Όμ°¨μ’…μ˜ 결합선택λͺ¨ν˜• μΆ”μ • - κ΅­λ‚΄ μ œμ‘°μ—… ν™”μ£Όλ₯Ό λŒ€μƒμœΌλ‘œ -

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    ν•™μœ„λ…Όλ¬Έ (박사)-- μ„œμšΈλŒ€ν•™κ΅ ν™˜κ²½λŒ€ν•™μ› : ν™˜κ²½κ³„νšν•™κ³Ό, 2015. 2. κΉ€μ„±μˆ˜.ν™”λ¬Όμˆ˜μš”λͺ¨ν˜•μ€ λ³΅μž‘ν•˜κ³  λ‹€μ–‘ν•œ μš”μΈλ“€λ‘œ 인해 μ—¬κ°μˆ˜μš”λͺ¨ν˜•κ³Ό 달리 κ·Έκ°„ 많이 λ°œμ „ν•˜μ§€ λͺ»ν•˜μ˜€μœΌλ‚˜, μ—°κ΅¬λŠ” μ§€μ†μ μœΌλ‘œ μˆ˜ν–‰λ˜μ–΄μ™”λ‹€. μžλ£Œμ— μžˆμ–΄μ„œλŠ” λ¬Όλ₯˜μ‘°μ‚¬ 자료λ₯Ό 주둜 μ‚¬μš©ν•˜μ˜€λ‹€λ©΄ μ΅œκ·Όμ—λŠ” μžλ™μ§‘κ³„μžλ£Œλ„ λ³‘ν–‰ν•˜μ—¬ μ‚¬μš©ν•˜λŠ” 좔세이고, λͺ¨ν˜•ν™”에 μžˆμ–΄μ„œλ„ 집계λͺ¨ν˜•μ—μ„œ 비집계λͺ¨ν˜•μœΌλ‘œ ν–‰νƒœλ₯Ό ν‘œν˜„ν•¨μ— μžˆμ–΄μ„œλ„ 기쑴의 λ™μ§ˆμ μΈ ν–‰νƒœ ν‘œν˜„μ—μ„œ 이질적인 ν–‰νƒœ ν‘œν˜„ 연ꡬ μœ„μ£Όλ‘œ λ³€ν™”ν•˜κ³  μžˆλ‹€. μ΄λŸ¬ν•œ ν™”λ¬Όμˆ˜μš”λͺ¨ν˜• 쀑 큰 과제 μ€‘μ˜ ν•˜λ‚˜κ°€ μ–΄λ–»κ²Œ μΆœν•˜μ€‘λŸ‰, μš΄μ†‘μˆ˜λ‹¨ 및 μ°¨μ’… 선택과정을 잘 λͺ¨ν˜•ν™” ν•˜λŠ” 것이닀. λͺ¨ν˜• κ²°κ³Όλ₯Ό 톡해 ν™”μ£Όμ˜ 졜적 μ°¨μ’…μ„ νƒν–‰νƒœλ₯Ό νŒŒμ•…ν•  수 있고, λͺ¨ν˜• μΆ”μ •μ˜ μ‚°μΆœλ¬ΌμΈ 탄λ ₯μ„±, μ‹œκ°„κ°€μΉ˜ 및 λΆ„λ‹΄μœ¨ 등을 톡해 정책적 μ‹œμ‚¬μ μ„ μ œμ‹œν•  수 μžˆλ‹€. κ·ΈλŸΌμ—λ„ λΆˆκ΅¬ν•˜κ³  κ΅­λ‚΄ ν™”λ¬Όμ˜ μΆœν•˜μ€‘λŸ‰μ„ κ³ λ €ν•˜μ—¬ μ˜μ—…μš© ν™”λ¬Όμ°¨μ’… κ°„μ˜ κ²½μŸκ΄€κ³„λ₯Ό κ²°μ •ν•˜λŠ” 연ꡬ가 맀우 λ―Έν‘ν•œ 싀정이닀. 이에 λ³Έ 논문은 κ΅­λ‚΄ μ œμ‘°μ—… ν™”μ£Όλ“€μ˜ λ‹€μ–‘ν•œ μ˜μ‚¬κ²°μ •μ΄ 반영된 κ΄€λ ¨ 사업체 λ¬Όλ₯˜ν˜„황쑰사 μžλ£Œκ°€ ꡬ좕됨에 따라 ν™”μ£Όκ°€ μΆœν•˜μ‹œ μΆœν•˜μ€‘λŸ‰μ— 따라 κ·Έλ“€μ˜ 트럭 차쒅을 μ„ νƒν•˜λŠ” 지와 μ΄λŸ¬ν•œ 선택이 μ–΄λ–€ ν™˜κ²½μ—μ„œ λ‹€μ–‘ν•˜κ²Œ λ³€ν™”λ˜λŠ” 지λ₯Ό λΆ„μ„ν•˜κΈ° μœ„ν•΄ 결합선택λͺ¨ν˜•μ„ κ΅¬μΆ•ν•˜μ˜€λ‹€. λ”λΆˆμ–΄ κ΅­λ‚΄ μ‹œμž₯의 νŠΉμ„±μ— μ ν•©ν•œ μ—°κ΅¬λ²”μœ„ μ„€μ •, λͺ¨ν˜• μ„€μ •, 자료 ꡬ좕, λͺ¨ν˜•μ˜ 검증과정에 λŒ€ν•΄μ„œ μƒμ„Έν•˜κ²Œ μ œμ‹œν•˜μ˜€λ‹€. λ˜ν•œ, μ‹œκ°„ 및 μš΄μž„μš”μΈ 이외에 μ°¨λŸ‰ νŠΉμ„± 및 ν™”μ£Ό νŠΉμ„±, μΆœν•˜ν™”λ¬Ό νŠΉμ„±μ— 따라 μΆœν•˜μ€‘λŸ‰μ— λ”°λ₯Έ ν™”μ£Όμ˜ 졜적 μ°¨μ’…μ„ νƒν–‰νƒœλ₯Ό λΆ„μ„ν•˜μ˜€λ‹€. λ”λΆˆμ–΄ λͺ¨ν˜•μ˜ 좔정결과인 탄λ ₯μ„±, μ‹œκ°„κ°€μΉ˜ 및 λΆ„λ‹΄μœ¨ 등을 톡해 정책적 μ‹œμ‚¬μ μ„ μ œμ‹œν•˜μ˜€λ‹€. λ³Έ λ…Όλ¬Έμ˜ 뢄석 κ²°κ³Όλ‘œλŠ” 첫째, κ΅­λ‚΄ 화물뢀문에 μžˆμ–΄μ„œλ„ 사업체 λ¬Όλ₯˜ν˜„황쑰사 자료λ₯Ό 톡해 μ˜μ‚¬κ²°μ •μžλ“€μ˜ 닀양성을 λ°˜μ˜ν•˜μ—¬ 결합선택λͺ¨ν˜•μ˜ ꡬ좕이 κ°€λŠ₯ν•˜λ‹€λŠ” 것을 ν™•μΈν•˜μ˜€λ‹€. λ‹€ν•­λ‘œμ§“λͺ¨ν˜•μ΄ μ ν•©ν•œ κ²ƒμœΌλ‘œ λ‚˜νƒ€λ‚¬μœΌλ©°, ν™”μ£Ό νŠΉμ„±, μΆœν•˜ν™”λ¬Ό νŠΉμ„± λ“±μ˜ λ‹€μ–‘ν•œ λ³€μˆ˜κ°€ μ±„νƒλ˜μ—ˆλ‹€. λ”λΆˆμ–΄ κΈ΄κΈ‰μš΄μ†‘ 및 과적 κ΄€λ ¨ μš”μΈμ΄ μΆœν•˜μ€‘λŸ‰ 선택에 영ν–₯을 λ―ΈμΉ˜λŠ” μš”μΈμ΄λ©°, λͺ¨ν˜• 좔정에 μžˆμ–΄μ„œ 신쀑을 κΈ°ν•΄μ•Ό ν•˜λŠ” μš”μΈμž„μ„ μ•Œ 수 μžˆμ—ˆλ‹€. λ‘˜μ§Έ, ν™”λ¬Όμžλ™μ°¨ν†΅ν–‰μ‹€νƒœμ‘°μ‚¬ μžλ£Œμ™€ ν™”λ¬Όμš΄μ†‘μ‹œμž₯ μ‹€νƒœμ‘°μ‚¬μ˜ 화주업체쑰사 자료λ₯Ό ν†΅ν•΄μ„œλ„ ν†΅ν–‰μ‹œκ°„ 및 μš΄μž„λ³€μˆ˜μ— λŒ€ν•œ λŒ€μ²΄μžλ£Œλ‘œμ„œ μ μš©κ°€λŠ₯성을 λ°œκ²¬ν•˜μ˜€λ‹€. 과거에 적용된 1μ°¨ ν•¨μˆ˜μ‹λ³΄λ‹€ 2μ°¨ ν•¨μˆ˜μ‹μ΄ 보닀 적합성이 λ†’λ‹€λŠ” 것도 ν™•μΈν•˜μ˜€λ‹€. μ…‹μ§Έ, κ΅­λ‚΄ ν™”λ¬Ό μš΄μ†‘μ— μžˆμ–΄μ„œ μ€‘μš”ν•œ 역할을 ν•˜κ³  μžˆλŠ” μ œμ‘°μ—…μ˜ λ‹€μ–‘ν•œ μ—…μ’…κ³Ό κ±°λ¦¬λŒ€λ³„ νŠΉμ„±μ— λ”°λ₯Έ ν™”μ£Όμ˜ μ˜μ—…μš© ν™”λ¬Όμ°¨μ˜ μ΄μš©ν–‰νƒœμ— λŒ€ν•΄μ„œλ„ 뢄석을 μˆ˜ν–‰ν•˜μ˜€λ‹€. κ΅­λ‚΄ ν™”λ¬Όμš΄μ†‘μ‹œμž₯에 μ ν•©ν•œ 과적 μ—¬λΆ€ λ³€μˆ˜μ™€ μΆœν•˜μ‹œ μžκ°€μš© ν™”λ¬Όμ°¨ 동일톀급 μ†Œμœ  λ³€μˆ˜λ₯Ό μƒˆλ‘­κ²Œ μ„€μ •ν•˜μ—¬ μ μš©ν•˜μ˜€λ‹€. μ„œλΉ„μŠ€ νŠΉμ„±, ν™”μ£Ό νŠΉμ„±, μΆœν•˜ν™”λ¬Ό νŠΉμ„±μ— κ΄€ν•œ 11개 λ³€μˆ˜λ“€μ— λŒ€ν•΄μ„œ κ²€ν† ν•œ κ²°κ³Ό μΆœν•˜μ‹œ 동일 적재λŠ₯λ ₯ μžκ°€μš© ν™”λ¬Όμ°¨ μ†Œμœ μ—¬λΆ€ λ³€μˆ˜μ™€ 과적 μ—¬λΆ€ λ³€μˆ˜κ°€ μ£Όμš” 영ν–₯μš”μΈμž„μ„ μ•Œ 수 μžˆμ—ˆλ‹€. κ΅­λ‚΄ ν™”λ¬Όμžλ™μ°¨ μš΄μ†‘μ‹œμž₯μ—μ„œλŠ” κ΅­λ‚΄ ν™”μ£Όλ“€μ˜ μžκ°€μš© ν™”λ¬Όμ°¨ μ†Œμ†Œν˜•, μ†Œν˜• 및 μ€‘ν˜• ν™”λ¬Όμ°¨ λ³΄μœ λΉ„μœ¨μ΄ λ†’κΈ° λ•Œλ¬Έμ— μ˜μ—…μš© μš΄μ†‘μ—…μ²΄λŠ” λŒ€ν˜•ν™”λ¬Όμ°¨ 쀑μž₯거리 μ‹œμž₯μ—μ„œ 경쟁λ ₯이 μžˆλŠ” κ²ƒμœΌλ‘œ λ‚˜νƒ€λ‚¬λ‹€. λ˜ν•œ, κ±°λ¦¬λŒ€λ³„ 및 μ—…μ’…λ³„λ‘œ ν™”μ£Όμ˜ μ„ νƒν–‰νƒœκ°€ λ‹€μ†Œ 차이가 μžˆμŒμ„ μ•Œ 수 μžˆμ—ˆλ‹€. λ„·μ§Έ, ν™”μ£Όκ°€ μΆœν•˜μ€‘λŸ‰κ³Ό 화물차쒅을 κ³ λ €ν•˜μ—¬ μ˜μ‚¬κ²°μ •μ„ 함에 μžˆμ–΄μ„œ ν†΅ν–‰μ‹œκ°„μ€ μš΄μž„μ— λΉ„ν•΄ 보닀 μ€‘μš”ν•œ μš”μΈμœΌλ‘œ λΆ„μ„λ˜μ—ˆλ‹€. μš°λ¦¬λ‚˜λΌλŠ” ꡭ토면적이 μž‘κΈ° λ•Œλ¬Έμ— μ œμ‘°μ—… ν™”μ£Όκ°€ μš΄μž„λ³΄λ‹€λŠ” μ‹œκ°„μ— μƒλŒ€μ μœΌλ‘œ λ―Όκ°ν•˜κ²Œ λ°˜μ‘ν•˜κ³  μžˆμŒμ„ μ•Œ 수 μžˆμ—ˆλ‹€. μš΄μž„κ΄€λ ¨ μš”μΈμ€ μž‘μ€ μΆœν•˜μ€‘λŸ‰μ˜ μ†Œν˜• μ°¨λŸ‰μ—λŠ” 큰 영ν–₯을 λ―ΈμΉ˜μ§€ μ•ŠμœΌλ‚˜, 큰 μΆœν•˜μ€‘λŸ‰μ˜ λŒ€ν˜• μ°¨λŸ‰μ—λŠ” μ–΄λŠ 정도 영ν–₯을 μ£ΌλŠ” κ²ƒμœΌλ‘œ λ‚˜νƒ€λ‚¬λ‹€. 탄λ ₯μ„±μ˜ μˆ˜μΉ˜κ°€ μ–΄λŠ 정도 크게 λ‚˜νƒ€λ‚˜ μš΄μž„μ΄ μƒμŠΉν•˜λ©΄ 동일 적재λŠ₯λ ₯의 ν™”λ¬Όμ°¨μ—μ„œλŠ” λ¬Όλ™λŸ‰μ΄ μž‘μ€ μΆœν•˜μ€‘λŸ‰μ€ λ§Žμ€ μΆœν•˜μ€‘λŸ‰μœΌλ‘œ 이동할 것이며, 동일 μΆœν•˜μ€‘λŸ‰μ΄λΌλ©΄ 적재λŠ₯λ ₯이 큰 ν™”λ¬Όμ°¨μ—μ„œ μž‘μ€ ν™”λ¬Όμ°¨λ‘œ 이동할 κ²ƒμœΌλ‘œ νŒλ‹¨λœλ‹€. λ˜ν•œ, ν˜Όμž‘λ„κ°€ κ°€μ€‘λ˜λ©΄ μ€‘λŒ€ν˜• μΆœν•˜μ€‘λŸ‰μ΄ 큰 ν™”λ¬Όμ°¨μ—μ„œ 적은 μΆœν•˜μ€‘λŸ‰μ˜ ν™”λ¬Όμ°¨λ‘œ 이동할 κ²ƒμœΌλ‘œ λΆ„μ„λ˜μ—ˆλ‹€. ν–₯ν›„ μ‹œκ°„ λ˜λŠ” μš΄μž„μ— λ³€ν™”κ°€ 있으면 μ†Œν˜• μ°¨λŸ‰κ³Ό λŒ€ν˜• μ°¨λŸ‰μ˜ μ΄μš©λΉˆλ„λŠ” μ¦κ°€ν•˜κ³ , μ€‘ν˜• μ°¨λŸ‰μ˜ μ΄μš©λΉˆλ„λŠ” κ°μ†Œν•  κ²ƒμœΌλ‘œ μ˜ˆμƒλ˜μ—ˆλ‹€. λ§ˆμ§€λ§‰μœΌλ‘œ, 과적에 λŒ€ν•œ μš”μΈμ€ ν™”μ£Όμ—κ²Œ 큰 영ν–₯μš”μΈμœΌλ‘œ λΆ„μ„λ˜μ—ˆλ‹€. λ”°λΌμ„œ κ΅­λ‚΄ ν™”λ¬Όμ°¨μ’…κ³Ό κ΄€λ ¨ λͺ¨ν˜• μΆ”μ •μ‹œ λ°˜λ“œμ‹œ κ³ λ €ν•΄μ•Όν•  λ³€μˆ˜λ‘œμ„œ μ‚¬λ£Œλœλ‹€. λ˜ν•œ λ³Έ μ—°κ΅¬μ—μ„œ κ°œλ°œν•œ μΆœν•˜μ€‘λŸ‰μ„ κ³ λ €ν•œ 업쒅별 차쒅선택λͺ¨ν˜•μ„ μ‹€μ œ 산업단지 κ°œλ°œκ³„νš λ“±μ˜ μ‹€μ œ 사둀에 μ μš©ν•˜λ©΄ μˆ˜μš” μΆ”μ •κ²°κ³Όμ˜ 정확도λ₯Ό 높일 수 μžˆμŒμ„ ν™•μΈν•˜μ˜€λ‹€. λ³Έ μ—°κ΅¬μ˜ ν•œκ³„μ™€ ν–₯ν›„ μ—°κ΅¬κ³Όμ œλŠ” λ‹€μŒκ³Ό κ°™λ‹€. 첫째, μ„ νƒλŒ€μ•ˆ 집합을 섀정함에 μžˆμ–΄μ„œ 자료의 λΆ€μ‘±κ³Ό ν•œκ³„λ‘œ λ‹€μ–‘ν•œ ν™”λ¬Όμžλ™μ°¨ 적재λŠ₯λ ₯을 κ³ λ €ν•˜μ§€ λͺ»ν•˜μ—¬ μ°¨μ’…κ΄€λ ¨ μ„ νƒλŒ€μ•ˆμ΄ κ°μ†Œλœ 점은 ν•œκ³„λΌκ³  ν•  수 μžˆλ‹€. λ‘˜μ§Έ, μ—°κ΅¬μ˜ λ²”μœ„μ— μžˆμ–΄μ„œλ„ ν•œκ³„κ°€ μ‘΄μž¬ν•œλ‹€. 업쒅에 μžˆμ–΄μ„œ κ΅­λ‚΄ μ œμ‘°μ—…μ˜ 5개 μ—…μ’…λ§Œμ„ λΆ„μ„ν•˜μ˜€μœΌλ‚˜, μ œμ‘°μ—…μ™Έμ— λ†λ¦Όμˆ˜μΆ•μ—…, κ΄‘μ—…, 도맀업, μ„œλΉ„μŠ€μ—…, 택배업 λ“±μ˜ λ‹€μ–‘ν•œ 업쒅을 κ³ λ €ν•  ν•„μš”κ°€ μžˆλ‹€. λ˜ν•œ, λ‚΄μˆ˜ ν™”λ¬Όλ§Œμ„ λΆ„μ„ν•˜μ˜€μœΌλ‚˜, μˆ˜μΆœμž… ν™”λ¬ΌκΉŒμ§€ 연ꡬ λŒ€μƒμ— ν¬ν•¨ν•œλ‹€λ©΄ 쒀더 ν¬κ΄„μ μœΌλ‘œ 해석할 수 μžˆμ„ 것이닀. ν•œνŽΈ, ν•΄μ™Έ 연ꡬ듀과 같이 일뢀 ν’ˆλͺ© λ˜λŠ” 업쒅이라도 λ„λ‘œ 화물차외에 철도, μ—°μ•ˆν•΄μš΄, 항곡 μš΄μ†‘μˆ˜λ‹¨κΉŒμ§€ ν¬ν•¨ν•˜μ—¬ μΆœν•˜μ€‘λŸ‰μ„ κ³ λ €ν•΄ μ—°κ΅¬ν•˜λ©΄ μš΄μ†‘μˆ˜λ‹¨ κ°„μ˜ 변화뢄을 ν¬ν•¨ν•œ 보닀 κ΄‘μ˜μ˜ κ²°κ³Όλ₯Ό μ‚΄νŽ΄λ³Ό 수 μžˆμ„ 것이닀. μ…‹μ§Έ, μ‹œκ°„κ³Ό μš΄μž„μ— λŒ€ν•œ μ‹€μΈ‘μΉ˜λ₯Ό ν™œμš©ν•˜λ©΄ λͺ¨ν˜•μ˜ 예츑λ ₯이 보닀 λ†’μ•„μ§ˆ κ²ƒμœΌλ‘œ μ˜ˆμƒν•œλ‹€. λ”λΆˆμ–΄ μš΄μž„μ— μΆ”κ°€ν•΄ ν•΄μ™Έμ˜ κ΄€λ ¨ 연ꡬ와 같이 μ΄μžλΉ„μš©, ν™˜μ λΉ„μš©, μ£Όλ¬ΈλΉ„μš© λ“±μ˜ 타 λ¬Όλ₯˜λΉ„μš©κΉŒμ§€ κ³ λ €ν•œλ‹€λ©΄ μ˜μ‚¬κ²°μ • κ³Όμ •μ—μ„œ 보닀 μ€‘μš”ν•œ λΉ„μš©μš”μΈμ΄ 무엇인지도 뢄석할 수 μžˆμ„ 것이닀. λ§ˆμ§€λ§‰μœΌλ‘œ, λ³Έ μ—°κ΅¬μ—μ„œλŠ” λ‹€ν•­λ‘œμ§“λͺ¨ν˜•λ§Œμ„ μ„€μ •ν•˜μ—¬ μ—°κ΅¬ν•˜μ˜€μœΌλ―€λ‘œ μ€‘μ²©λ‘œμ§“λͺ¨ν˜•μ΄λ‚˜ ν˜Όν•©λ‘œμ§“λͺ¨ν˜• λ“± λ‹€μ–‘ν•œ λ‘œμ§“λͺ¨ν˜•μ„ μ μš©ν•˜μ—¬ 비ꡐ λΆ„μ„ν•˜μ§€ λͺ»ν•œ ν•œκ³„κ°€ μ‘΄μž¬ν•œλ‹€.β… . μ„œλ‘  1 1. μ—°κ΅¬μ˜ λ°°κ²½ 및 λͺ©μ  1 2. μ—°κ΅¬μ˜ λ²”μœ„ 및 방법 5 3. μ—°κ΅¬μ˜ ꡬ성 6 β…‘. 이둠 및 μ„ ν–‰μ—°κ΅¬μ˜ κ³ μ°° 8 1. 이둠 8 1) ν™”λ¬Όμˆ˜μš” λͺ¨ν˜•μ˜ λΆ„λ₯˜ 8 2) ν™”λ¬Όμˆ˜λ‹¨μ„ νƒ 영ν–₯μš”μΈ 11 2. 선행연ꡬ 13 1) κ΄€λ ¨ μ„ ν–‰μ—°κ΅¬μ˜ μ„ μ • 13 2) μΆœν•˜μ€‘λŸ‰μ„ λ°°μ œν•œ ν™”λ¬Ό μš΄μ†‘μˆ˜λ‹¨μ„ νƒμ— κ΄€ν•œ 연ꡬ 13 3) μΆœν•˜μ€‘λŸ‰μ„ κ³ λ €ν•œ ν™”λ¬Ό μš΄μ†‘μˆ˜λ‹¨μ„ νƒμ— κ΄€ν•œ 연ꡬ 16 4) λ³Έ μ—°κ΅¬μ˜ 차별성 25 β…’. μΆœν•˜μ€‘λŸ‰κ³Ό ν™”λ¬Όμ°¨μ’… 결합선택λͺ¨ν˜•μ˜ μ„€μ • 27 1. λͺ¨ν˜•μ˜ μ„€μ • 27 2. μ„ νƒλŒ€μ•ˆ μ§‘ν•©μ˜ μ„€μ • 31 3. ν™”μ£Ό νŠΉμ„± 및 μΆœν•˜ν™”λ¬Ό νŠΉμ„± λ…λ¦½λ³€μˆ˜ 38 1) μš΄μ†‘μ‹œκ°„ 39 2) ν†€λ‹Ήμš΄μž„ 40 3) μ’…μ‚¬μž 규λͺ¨ 40 4) 톀당가격 40 5) μΆœν•˜λΉˆλ„ 41 6) ν™”λ¬Ό λ¬Όλ™λŸ‰ 41 7) μ°½κ³  λ³΄μœ μ—¬λΆ€ 41 8) μΆœν•˜μ‹œ μžκ°€μš© ν™”λ¬Όμ°¨ 동일 적재λŠ₯λ ₯ λ³΄μœ μ—¬λΆ€ 41 9) μΆœν•˜μ§€μ—­ μˆ˜λ„κΆŒ μ—¬λΆ€ 42 10) μˆ˜ν•˜μΈ μ—…μ’… 도맀업 μ—¬λΆ€ 42 11) 과적 μ—¬λΆ€ 42 4. μ‹œμž₯λΆ„ν•  44 5. λͺ¨ν˜•μ˜ 좔정방법 47 β…£. 자료의 ꡬ좕 및 기술적 뢄석 51 1. 자료의 ꡬ좕 52 1) μ„œλΉ„μŠ€ μˆ˜μ€€ νŠΉμ„± 자료 53 2) ν™”μ£Ό νŠΉμ„± 및 μΆœν•˜ ν™”λ¬ΌνŠΉμ„± 자료 65 2. 자료의 기술적 뢄석 68 1) μ’…μ†λ³€μˆ˜ 기술적 뢄석 68 2) ν™”μ£Ό νŠΉμ„± 기술적 뢄석 72 3) μΆœν•˜ ν™”λ¬ΌνŠΉμ„± 기술적 뢄석 77 β…€. λͺ¨ν˜•μ˜ μΆ”μ •κ²°κ³Ό 85 1. μΆœν•˜μ€‘λŸ‰κ³Ό μ˜μ—…μš© ν™”λ¬Όμ°¨μ’… 선택λͺ¨ν˜• μΆ”μ •κ²°κ³Ό 85 1) 전체 λͺ¨ν˜•μ˜ μΆ”μ •κ²°κ³Ό 85 2) κ±°λ¦¬λŒ€λ³„ λͺ¨ν˜•μ˜ μΆ”μ •κ²°κ³Ό 90 3) 업쒅별 λͺ¨ν˜•μ˜ μΆ”μ •κ²°κ³Ό 94 4) 과적을 λ°°μ œν•œ λͺ¨ν˜•μ˜ μΆ”μ •κ²°κ³Ό 104 2. 탄λ ₯μ„± 해석 106 3. λͺ¨ν˜•μ˜ 비ꡐ평가 115 1) 탄λ ₯μ„± 검증 κ²°κ³Ό 115 2) μ‹œκ°„κ°€μΉ˜ 검증 κ²°κ³Ό 117 3) μ‹œμž₯λΆ„ν•  κ²€μ • κ²°κ³Ό 121 4. λͺ¨ν˜•μ˜ 적용 123 β…₯. κ²°λ‘  126 1. 연ꡬ결과와 μ‹œμ‚¬μ  126 1) 연ꡬ결과 126 2) μ‹œμ‚¬μ  130 2. μ—°κ΅¬μ˜ ν•œκ³„ 및 ν–₯ν›„ 연ꡬ방ν–₯ 131 μ°Έκ³ λ¬Έν—Œ 133 뢀둝 141 [뢀둝 A] κ΅­λ‚΄ ν™”λ¬Όμš΄μ†‘ κ΄€λ ¨ μ°Έκ³  자료 141 [뢀둝 B] 자료 ꡬ좕 κ΄€λ ¨ μ‘°μ‚¬ν‘œ 147 [뢀둝 C] μ‚°μ—…μ—…μ’… ꡬ뢄(제9μ°¨ ν•œκ΅­ν‘œμ€€μ‚°μ—…λΆ„λ₯˜) 165 Abstract 166Docto

    Predicting the defibrillation success of ventricular fibrillation ecg signal using time-frequency analysis

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    μ˜κ³΅ν•™κ³Ό/박사[ν•œκΈ€]λ³Έ 논문은 μ‹¬μ‹€μ„Έλ™μ‹œ μΈ‘μ •λœ μ‹¬μ „λ„μ˜ μ‹œ-주파수 뢄석을 톡해 얻은 νŒŒλΌλ―Έν„°μ— κ·Όκ±°ν•œ μ œμ„Έλ™ 성곡λ₯  μ˜ˆμΈ‘μ— κ΄€ν•œ 연ꡬ이닀. 일반적으둜 심싀세동을 μ •μ§€μ‹œν‚¬ 수 μžˆλŠ” κ°€μž₯ 효과적인 방법은 전기적인 μ œμ„Έλ™μ„ κ°€ν•˜λŠ” κ²ƒμ΄λ‚˜ λΆˆν•„μš”ν•œ μ œμ„Έλ™μ˜ λ°˜λ³΅μ„ ν”Όν•˜κ³  효과적인 μ œμ„Έλ™ μ‹œκ°„μ„ μ•ŒκΈ° μœ„ν•΄μ„œλŠ” μ œμ„Έλ™ 성곡에 λŒ€ν•œ 예츑이 맀우 μ€‘μš”ν•˜λ‹€. μ œμ„Έλ™ 성곡λ₯ μ„ μ •ν™•ν•˜κ²Œ μ˜ˆμΈ‘ν•˜κΈ° μœ„ν•΄μ„œλŠ” 관상동λ§₯κ΄€λ₯˜μ••(coronary perfusion pressure)μ΄λ‚˜ μ‹¬κ·Όν˜ˆλ₯˜μ–‘(myocardial bloo dflow)κ³Ό 같은 심μž₯의 ν˜ˆμ—­ν•™μ  λ³€μˆ˜λ“€μ„ μ‚¬μš©ν•΄μ•Ό ν•˜μ§€λ§Œ 병원 λ°–μ΄λ‚˜ 응급 μƒν™©μ—μ„œ μΈ‘μ •ν•˜κΈ° μ–΄λ €μš°λ―€λ‘œ λΉ„κ΄€ν˜ˆμ λ°©λ²•μœΌλ‘œ 츑정이 κ°€λŠ₯ν•œ 심전도λ₯Ό μ΄μš©ν•˜κ²Œ λœλ‹€. μ‹€ν—˜λ™λ¬Όμ— 심싀세동을 μœ λ°œμ‹œν‚¨ ν›„ 4뢄이 κ²½κ³Όν•œ 뒀에 에피넀프린 νˆ¬μ—¬μ™€ μ‹¬νμ†Œμƒμˆ μ„ μ‹œν–‰ν•˜λ©° λŒ€λ™λ§₯μ••, μš°μ‹¬λ°©μ••, 심전도λ₯Ό μΈ‘μ •ν•˜μ˜€λ‹€. 총 15회의 μ‹€ν—˜μ„ μ‹€μ‹œν•˜μ˜€μœΌλ©° κ·Έ 쀑 μ†Œμƒμ— μ„±κ³΅ν•œ μ‹€ν—˜μ€ 9회, μ†Œμƒμ— μ‹€νŒ¨ν•œ μ‹€ν—˜μ€ 6회 μ΄μ—ˆλ‹€. 관상동λ§₯κ΄€λ₯˜μ••μ€ λŒ€λ™λ§₯μ••κ³Ό μš°μ‹¬λ°©μ••μ˜ μ‚°μˆ μ μΈ 차이λ₯Ό μ΄μš©ν•˜μ—¬ κ³„μ‚°ν•˜μ˜€κ³  μ†Œμƒμ„±κ³΅(return of spontaneous circulation : ROSC)을 μ˜ˆμΈ‘ν•˜κΈ° μœ„ν•΄ μ‹¬μ „λ„μ˜ μ‹œ-주파수 μ˜μ—­μ—μ„œ νŒŒλΌλ―Έν„°λ“€μ„ μΆ”μΆœ 및 λΆ„μ„ν•˜μ˜€λ‹€. μ‹œ-주파수 뢄석을 μœ„ν•΄μ„œ Smoothed pseudo Wigner-Ville distribution(SPWV D)을 μ΄μš©ν•˜μ˜€λ‹€. μ œμ„Έλ™ 성곡λ₯  μ˜ˆμΈ‘μ„ μœ„ν•΄ μ‚¬μš©ν•  νŒŒλΌλ―Έν„°λ₯Ό μΆ”μΆœν•˜κΈ° μœ„ν•΄ 각 μ‹œκ°„ μΆ•μ˜ νŒŒμ›ŒμŠ€νŽ™νŠΈλŸΌ λ°€λ„μ—μ„œ μ€‘κ°„μ£ΌνŒŒμˆ˜, μ΅œλŒ€μ£ΌνŒŒμˆ˜, 주파수 κ±°μΉ κΈ°, 1/f 기울기λ₯Ό κ΅¬ν•˜μ˜€μœΌλ©° 주파수 κ΅¬κ°„λ“€μ—μ„œμ˜ λ³€ν™”λ₯Ό μ•Œμ•„λ³΄κΈ° μœ„ν•΄μ„œ 2~4㎐, 4~6㎐, 6~8㎐, 8~10㎐, 10~12㎐, 12~15㎐ 주파수 ꡬ간 면적을 전체 νŒŒμ›ŒμŠ€νŽ™νŠΈλŸΌ 면적에 λŒ€ν•œ λΉ„μœ¨λ‘œ κ³„μ‚°ν•˜μ—¬ λͺ¨λ‘ 10개의 νŒŒλΌλ―Έν„°λ“€μ„ μΆ”μΆœν•˜μ˜€λ‹€. μ†Œμƒμ„±κ³΅κ³Ό μ†Œμƒμ‹€νŒ¨ 그룹의 차이λ₯Ό λ‚˜νƒ€λ‚΄λŠ” νŒŒλΌλ―Έν„°λ₯Ό μ°ΎκΈ° μœ„ν•΄ λ…λ¦½ν‘œλ³Έ t-κ²€μ •(independent sample t-test)을 μ΄μš©ν•œ κ²°κ³Ό 4개의 νŒŒλΌλ―Έν„°(μ€‘κ°„μ£ΌνŒŒμˆ˜, 1/f 기울기, 2~4㎐, 8~10㎐ λŒ€μ—­λΉ„)μ—μ„œ p<0.05의 유의 μˆ˜μ€€μ„ λ‚˜νƒ€λ‚΄μ—ˆλ‹€. 관상동λ§₯κ΄€λ₯˜μ••κ³Ό λ„€ 개의 νŒŒλΌλ―Έν„°λ“€μ˜ 상관관계λ₯Ό λΆ„μ„ν•œ κ²°κ³Όμ—μ„œλŠ” μ€‘κ°„μ£ΌνŒŒμˆ˜, 2~4㎐ λŒ€μ—­λΉ„, 8~10㎐ λŒ€μ—­λΉ„κ°€ 각각 0.56, -0.49, 0.31의 μƒκ΄€κ³„μˆ˜λ₯Ό λ‚˜νƒ€λƒˆμœΌλ©° 1/f κΈ°μšΈκΈ°λŠ” -0.07둜 μœ μ˜μˆ˜μ€€μ˜ κ²°κ³Όλ₯Ό 보이지 λͺ»ν–ˆλ‹€. μΆ”μΆœν•œ νŒŒλΌλ―Έν„°λ“€κ³Ό 관상동λ§₯κ΄€λ₯˜μ••κ³Όμ˜ 관계λ₯Ό νšŒκ·€λ°©μ •μ‹μ„ μ΄μš©ν•˜μ—¬ κ³„μ‚°ν•œ μ„ ν˜•νšŒκ·€λΆ„μ„κ²°κ³Όμ—μ„œ κ²°μ •κ³„μˆ˜(R2)κ°€ 55%μ˜€κ³  1/f κΈ°μšΈκΈ°μ™€ 8~10㎐ λŒ€μ—­λΉ„κ°€ p<0.05 의 μœ μ˜μ„±μ„ λ³΄μ˜€λ‹€. μ œμ„Έλ™ 성곡을 μ˜ˆμΈ‘ν•  수 μžˆλŠ” κ°€μž₯ μ ν•©ν•œ νŒŒλΌλ―Έν„°μ˜ 쑰합을 μ°ΎκΈ° μœ„ν•΄μ„œ μ‹¬μ „λ„μ˜ μ‹œ-주파수 μ˜μ—­μ—μ„œ μΆ”μΆœν•œ λ„€ 개의 νŒŒλΌλ―Έν„°λ‘œ μ—¬μ„― 개의 쑰합을 λ§Œλ“€μ—ˆμœΌλ©° μ†Œμƒμ„±κ³΅κ³Ό μ†Œμƒμ‹€νŒ¨ 그룹의 뢄리 및 νŒλ³„ λŠ₯λ ₯을 linear discriminant an alysis(LDA)와 계측적 ꡰ집뢄석(hierarchial clustering analysis)λ₯Ό μ΄μš©ν•˜μ—¬ ν‰κ°€ν•˜μ˜€λ‹€. μ€‘κ°„μ£ΌνŒŒμˆ˜μ™€ 2~4Hz λŒ€μ—­λΉ„μ˜ 쑰합이 전체 μ‹€ν—˜κ΅¬κ°„μ—μ„œ 민감도 86.6%, νŠΉμ΄λ„ 85.5%둜 κ°€μž₯ λ†’μ•˜μœΌλ©° 5λΆ„ μ΄ν›„μ—μ„œλŠ” 90%μ΄μƒμ˜ 민감도와 νŠΉμ΄λ„λ₯Ό(민감도:91.2%, νŠΉμ΄λ„: 95.4%) λ‚˜νƒ€λƒˆλ‹€. λ³Έ μ—°κ΅¬μ˜ 결과둜 심전도 νŒŒλΌλ―Έν„°λ“€μ˜ 쑰합을 μ΄μš©ν•œ 뢄석을 톡해 μ†Œμƒμ„±κ³΅μ— λŒ€ν•œ νŒλ³„μ΄ κ°€λŠ₯함을 λ³΄μ˜€μœΌλ©° μ‹€μ‹œκ°„ 뢄석을 ν†΅ν•œ μ‹¬μ‹€μ„Έλ™μ‹œ 처치효과 뢄석, μžλ™ μ œμ„Έλ™κΈ° 개발 등에 이용될 수 μžˆμ„ 것이닀. [영문]Fibrillation of ventricle of the heart is a result of chaotic electrical activity of the heart chamber, resulting in loss of coordinated myocardial contraction. Electrical defibrillation is the only effective method of terminating the ventricular fibrillation (VF). Previous studies suggested that cardiopulmonary resuscitation (CPR) and epinephrine administration before counter-shock was more effective method than immediate counter-shock to prolonged ventricular fibrillation. Therefore, the method for evaluating the success rate of defibrillation attempt was needed. Coronary perfusion pressure is the best predictor of the success of cardiac resuscitation. In out-of-hospital, however, there is few non-invasive or practical invasive option for measuring coronary perfusion pressure. Therefore, we measured electrocardiogram (ECG) as predictors of restoration of spontaneous circulation (ROSC). The purpose of this study was to predict the defibrillation success of ventricular fibrillation ECG signal using time-frequency analysis. In this study, coronary perfusion pressure and electrocardiogram were measured during CPR. Parameters extracted from time-frequency domain were served as predictor of resuscitation success. The experiment was performed with 15 mongrel dogs(ROSC: 9, non-ROSC: 6). Time-frequency distribution (TFD) of ECG signals was estimated from the Smoothed pseudo Wigner Ville distribution (SPWVD). Median frequency, peak frequency, 1/f slope, frequency band ratios(2~4㎐, 4~6㎐, 6~8㎐, 8~10㎐, 10~12㎐, 12~15㎐) were extracted from each TFD as a function of time. Independent t-test was used to determine the differences in ROSC and non-ROSC groups. In the statistical results, we selected four significant parameters - median frequency, 1/f slope, 2~4㎐ band ratio, 8~10㎐ band ratio. The relationship between coronary perfusion pressure and ECG parameters was analyzed with linear regression analysis. R-square value was 55%. 1/f slope and 8~10㎐ band ratio had the significant relationship with coronary perfusion pressure. We attempted to predict defibrillation success by combining features extracted from TFD. For a given feature combinations, we evaluated discriminant ability using linear discriminant and clustering analysis. The combination of median frequency and 2~4㎐ band ratio gave the best predictive potential (sensitivity: 86.6%, specificity: 85.5%). After 5-min induced VF, the same combination of feature showed a higher predictive potential (sensitivity: 91.2%, specificity: 95.4%). In these results, we proposed a method to evaluate an outcome predictor for ROSC in cardiac arrest animals. On this basis, it is possible to evaluate the effects therapy during VF, development of automated external defibrillator.ope

    A Joint Model Selecting Shipment and Truck Size : Focusing on Shippers in the Korean Manufacturing Industry

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    λ³Έ μ—°κ΅¬λŠ” κ΅­λ‚΄ μ œμ‘°μ—… ν™”μ£Όλ₯Ό λŒ€μƒμœΌλ‘œ ν•œ 2011λ…„μ˜ 사업체 λ¬Όλ₯˜ν˜„황쑰사 자료λ₯Ό μ΄μš©ν•΄ μΆœν•˜μ€‘λŸ‰κ³Ό ν™”λ¬Όμ°¨μ’…μ˜ κ°œλ³„ 결합선택 λ‘œμ§“λͺ¨ν˜•μ„ μΆ”μ •ν•˜μ˜€λ‹€. λ˜ν•œ 이듀 ν™”μ£Όμ˜ κ²°ν•©μ„ νƒν–‰νƒœμ— 영ν–₯을 λ―ΈμΉ˜λŠ” μš”μΈλ“€μΈ μš΄μ†‘μ„œλΉ„μŠ€ νŠΉμ„±, ν™”μ£Ό νŠΉμ„± 및 μΆœν•˜ν™”λ¬Ό νŠΉμ„±λ“€μ„ λΆ„μ„ν•˜μ˜€λ‹€. 연ꡬ κ²°κ³Ό κ΅­λ‚΄ μ œμ‘°μ—…μ˜ ν™”λ¬Όμš΄μ†‘λΆ€λ¬Έμ— λŒ€ν•΄μ„œλ„ ν•΄μ™Έμ˜ μ„ ν–‰ μ—°κ΅¬λ“€μ²˜λŸΌ μΆœν•˜μ€‘λŸ‰κ³Ό ν™”λ¬Όμ°¨μ’…μ˜ 결합선택λͺ¨ν˜•μ΄ νƒ€λ‹Ήν•œ κ²ƒμœΌλ‘œ λ‚˜νƒ€λ‚¬λ‹€. λ˜ν•œ μ΄λŸ¬ν•œ κ²°ν•©μ„ νƒν˜•νƒœμ— μš΄μ†‘μ‹œκ°„κ³Ό μš΄μž„λΏλ§Œ μ•„λ‹ˆλΌ ν™”μ£Όκ°€ μΆœν•˜ν•  λ•Œ μ΄μš©ν•˜λŠ” μ˜μ—…μš© ν™”λ¬Όμ°¨μ’…κ³Ό λ™μΌν•œ μžκ°€μš© ν™”λ¬Όμ°¨μ˜ 보유 여뢀와 과적 μ—¬λΆ€ 등도 큰 영ν–₯을 λ―ΈμΉ˜λŠ” κ²ƒμœΌλ‘œ λ‚˜νƒ€λ‚¬λ‹€. This paper estimates a disaggregate freight transport logit model selecting shipment and truck size using a dataset provided by the 2011 Korean Commodity Flow Survey. The paper also investigates possible determinants of the joint choice of domestic manufacturing shippers, which include transport service attributes, shipper characteristics, and shipment characteristics. The results indicate that the joint choice model is most feasible for the Korean road freight transport sector of manufactured goods. This joint model also shows transport time and freight rates, the ownership of the same truck as the commercial truck hired by a shipper, and whether the vehicle is overloaded as significant determinants.N

    The Improvement of Stepwise Validation Methods for Traffic O/D Estimation

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