Overview

Dataset statistics

Number of variables19
Number of observations1191
Missing cells0
Missing cells (%)0.0%
Duplicate rows2
Duplicate rows (%)0.2%
Total size in memory180.4 KiB
Average record size in memory155.1 B

Variable types

Categorical6
Numeric2
Text9
DateTime1
Boolean1

Dataset

Description2023년 해양수산 RND 논문 목록 파일로서 논문을 등록한 기관의 참여과제 정보와 학술지명, 주저자, 교신저자, 공동저자 등의 논문 정보 제공 파일
Author해양수산과학기술진흥원
URLhttps://www.data.go.kr/data/15121138/fileData.do

Alerts

상태 has constant value ""Constant
Dataset has 2 (0.2%) duplicate rowsDuplicates
예산년도 is highly overall correlated with 과제접수번호 and 1 other fieldsHigh correlation
과제접수번호 is highly overall correlated with 예산년도High correlation
성과년도 is highly overall correlated with 예산년도High correlation
논문(학술지)구분 is highly overall correlated with 과학기술논문색인지수(SCI(E))구분High correlation
과학기술논문색인지수(SCI(E))구분 is highly overall correlated with 논문(학술지)구분High correlation
논문(학술지)구분 is highly imbalanced (53.2%)Imbalance

Reproduction

Analysis started2023-12-12 05:07:24.248151
Analysis finished2023-12-12 05:07:27.951557
Duration3.7 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

성과년도
Categorical

HIGH CORRELATION 

Distinct4
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size9.4 KiB
2022
934 
2020
124 
2021
 
73
2023
 
60

Length

Max length4
Median length4
Mean length4
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2020
2nd row2020
3rd row2020
4th row2020
5th row2020

Common Values

ValueCountFrequency (%)
2022 934
78.4%
2020 124
 
10.4%
2021 73
 
6.1%
2023 60
 
5.0%

Length

2023-12-12T14:07:28.031254image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T14:07:28.155979image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2022 934
78.4%
2020 124
 
10.4%
2021 73
 
6.1%
2023 60
 
5.0%

예산년도
Real number (ℝ)

HIGH CORRELATION 

Distinct7
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2021.67
Minimum2016
Maximum2023
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size10.6 KiB
2023-12-12T14:07:28.269506image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2016
5-th percentile2020
Q12022
median2022
Q32022
95-th percentile2022
Maximum2023
Range7
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.81442865
Coefficient of variation (CV)0.00040284945
Kurtosis4.1703234
Mean2021.67
Median Absolute Deviation (MAD)0
Skewness-1.7402653
Sum2407809
Variance0.66329403
MonotonicityNot monotonic
2023-12-12T14:07:28.425335image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=7)
ValueCountFrequency (%)
2022 852
71.5%
2021 143
 
12.0%
2020 115
 
9.7%
2023 57
 
4.8%
2019 22
 
1.8%
2016 1
 
0.1%
2017 1
 
0.1%
ValueCountFrequency (%)
2016 1
 
0.1%
2017 1
 
0.1%
2019 22
 
1.8%
2020 115
 
9.7%
2021 143
 
12.0%
2022 852
71.5%
2023 57
 
4.8%
ValueCountFrequency (%)
2023 57
 
4.8%
2022 852
71.5%
2021 143
 
12.0%
2020 115
 
9.7%
2019 22
 
1.8%
2017 1
 
0.1%
2016 1
 
0.1%

과제접수번호
Real number (ℝ)

HIGH CORRELATION 

Distinct179
Distinct (%)15.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean20196211
Minimum19992001
Maximum20220628
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size10.6 KiB
2023-12-12T14:07:28.627320image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum19992001
5-th percentile20150356
Q120180456
median20210427
Q320210646
95-th percentile20220534
Maximum20220628
Range228627
Interquartile range (IQR)30190

Descriptive statistics

Standard deviation29558.609
Coefficient of variation (CV)0.001463572
Kurtosis17.521263
Mean20196211
Median Absolute Deviation (MAD)9828
Skewness-3.2476226
Sum2.4053688 × 1010
Variance8.7371139 × 108
MonotonicityNot monotonic
2023-12-12T14:07:28.854265image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20210427 75
 
6.3%
20200615 71
 
6.0%
20210631 53
 
4.5%
20160400 41
 
3.4%
20180456 28
 
2.4%
20170305 27
 
2.3%
20200610 27
 
2.3%
20220357 26
 
2.2%
20220526 25
 
2.1%
20180447 24
 
2.0%
Other values (169) 794
66.7%
ValueCountFrequency (%)
19992001 10
0.8%
20110183 8
 
0.7%
20130291 10
0.8%
20140257 4
 
0.3%
20150212 2
 
0.2%
20150242 1
 
0.1%
20150340 21
1.8%
20150356 7
 
0.6%
20150394 20
1.7%
20160233 1
 
0.1%
ValueCountFrequency (%)
20220628 3
 
0.3%
20220603 6
0.5%
20220596 1
 
0.1%
20220579 1
 
0.1%
20220573 1
 
0.1%
20220570 4
0.3%
20220567 2
 
0.2%
20220566 8
0.7%
20220560 1
 
0.1%
20220559 4
0.3%

사업명
Text

Distinct83
Distinct (%)7.0%
Missing0
Missing (%)0.0%
Memory size9.4 KiB
2023-12-12T14:07:29.256052image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length41
Median length29
Mean length18.02267
Min length8

Characters and Unicode

Total characters21465
Distinct characters251
Distinct categories9 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique7 ?
Unique (%)0.6%

Sample

1st row해양과학조사 및 예보기술개발
2nd row해양과학조사 및 예보기술개발
3rd row해양과학조사 및 예보기술개발
4th row해양과학조사 및 예보기술개발
5th row해양과학조사 및 예보기술개발
ValueCountFrequency (%)
및 489
 
10.2%
기술개발 456
 
9.5%
개발 227
 
4.7%
기반 165
 
3.4%
해양과학조사 156
 
3.3%
예보기술개발 156
 
3.3%
해양환경 123
 
2.6%
극지 121
 
2.5%
스마트 108
 
2.3%
해양 104
 
2.2%
Other values (226) 2694
56.1%
2023-12-12T14:07:29.840653image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
3618
 
16.9%
기 1237
 
5.8%
발 971
 
4.5%
개 960
 
4.5%
술 925
 
4.3%
해 871
 
4.1%
양 782
 
3.6%
및 489
 
2.3%
학 327
 
1.5%
과 307
 
1.4%
Other values (241) 10978
51.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 17494
81.5%
Space Separator 3618
 
16.9%
Uppercase Letter 145
 
0.7%
Lowercase Letter 75
 
0.3%
Dash Punctuation 70
 
0.3%
Other Punctuation 26
 
0.1%
Close Punctuation 17
 
0.1%
Open Punctuation 17
 
0.1%
Decimal Number 3
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
기 1237
 
7.1%
발 971
 
5.6%
개 960
 
5.5%
술 925
 
5.3%
해 871
 
5.0%
양 782
 
4.5%
및 489
 
2.8%
학 327
 
1.9%
과 307
 
1.8%
스 285
 
1.6%
Other values (217) 10340
59.1%
Uppercase Letter
ValueCountFrequency (%)
I 31
21.4%
T 21
14.5%
N 18
12.4%
L 14
9.7%
C 14
9.7%
G 14
9.7%
A 14
9.7%
S 12
 
8.3%
P 4
 
2.8%
B 3
 
2.1%
Lowercase Letter
ValueCountFrequency (%)
a 12
16.0%
p 12
16.0%
u 12
16.0%
e 12
16.0%
l 12
16.0%
c 12
16.0%
o 3
 
4.0%
Other Punctuation
ValueCountFrequency (%)
· 20
76.9%
, 6
 
23.1%
Space Separator
ValueCountFrequency (%)
3618
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 70
100.0%
Close Punctuation
ValueCountFrequency (%)
) 17
100.0%
Open Punctuation
ValueCountFrequency (%)
( 17
100.0%
Decimal Number
ValueCountFrequency (%)
2 3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 17494
81.5%
Common 3751
 
17.5%
Latin 220
 
1.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
기 1237
 
7.1%
발 971
 
5.6%
개 960
 
5.5%
술 925
 
5.3%
해 871
 
5.0%
양 782
 
4.5%
및 489
 
2.8%
학 327
 
1.9%
과 307
 
1.8%
스 285
 
1.6%
Other values (217) 10340
59.1%
Latin
ValueCountFrequency (%)
I 31
14.1%
T 21
 
9.5%
N 18
 
8.2%
L 14
 
6.4%
C 14
 
6.4%
G 14
 
6.4%
A 14
 
6.4%
a 12
 
5.5%
S 12
 
5.5%
p 12
 
5.5%
Other values (7) 58
26.4%
Common
ValueCountFrequency (%)
3618
96.5%
- 70
 
1.9%
· 20
 
0.5%
) 17
 
0.5%
( 17
 
0.5%
, 6
 
0.2%
2 3
 
0.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 17494
81.5%
ASCII 3951
 
18.4%
None 20
 
0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
3618
91.6%
- 70
 
1.8%
I 31
 
0.8%
T 21
 
0.5%
N 18
 
0.5%
) 17
 
0.4%
( 17
 
0.4%
L 14
 
0.4%
C 14
 
0.4%
G 14
 
0.4%
Other values (13) 117
 
3.0%
Hangul
ValueCountFrequency (%)
기 1237
 
7.1%
발 971
 
5.6%
개 960
 
5.5%
술 925
 
5.3%
해 871
 
5.0%
양 782
 
4.5%
및 489
 
2.8%
학 327
 
1.9%
과 307
 
1.8%
스 285
 
1.6%
Other values (217) 10340
59.1%
None
ValueCountFrequency (%)
· 20
100.0%

과제명(총괄)
Text

Distinct182
Distinct (%)15.3%
Missing0
Missing (%)0.0%
Memory size9.4 KiB
2023-12-12T14:07:30.213198image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length71
Median length48
Mean length24.442485
Min length6

Characters and Unicode

Total characters29111
Distinct characters409
Distinct categories10 ?
Distinct scripts3 ?
Distinct blocks4 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique54 ?
Unique (%)4.5%

Sample

1st row동해남부 해저활성단층 연구 및 해저지진 발생 가능성 평가
2nd row해양수치모델링과 지능정보기술을 활용한 해양예측 정확도 향상 연구
3rd row해양수치모델링과 지능정보기술을 활용한 해양예측 정확도 향상 연구
4th row해양수치모델링과 지능정보기술을 활용한 해양예측 정확도 향상 연구
5th row해양수치모델링과 지능정보기술을 활용한 해양예측 정확도 향상 연구
ValueCountFrequency (%)
및 434
 
6.5%
개발 349
 
5.2%
기술개발 279
 
4.2%
기반 208
 
3.1%
연구 152
 
2.3%
해양 122
 
1.8%
구축 83
 
1.2%
스마트 83
 
1.2%
과학기술 75
 
1.1%
영향평가기술개발 75
 
1.1%
Other values (686) 4843
72.3%
2023-12-12T14:07:30.783463image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
5538
 
19.0%
기 1214
 
4.2%
해 1086
 
3.7%
발 912
 
3.1%
개 827
 
2.8%
술 653
 
2.2%
양 535
 
1.8%
및 434
 
1.5%
구 359
 
1.2%
연 318
 
1.1%
Other values (399) 17235
59.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 22558
77.5%
Space Separator 5538
 
19.0%
Uppercase Letter 379
 
1.3%
Decimal Number 146
 
0.5%
Other Punctuation 136
 
0.5%
Dash Punctuation 116
 
0.4%
Open Punctuation 100
 
0.3%
Close Punctuation 100
 
0.3%
Lowercase Letter 37
 
0.1%
Connector Punctuation 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
기 1214
 
5.4%
해 1086
 
4.8%
발 912
 
4.0%
개 827
 
3.7%
술 653
 
2.9%
양 535
 
2.4%
및 434
 
1.9%
구 359
 
1.6%
연 318
 
1.4%
수 315
 
1.4%
Other values (350) 15905
70.5%
Uppercase Letter
ValueCountFrequency (%)
N 47
12.4%
S 39
10.3%
I 35
9.2%
T 29
 
7.7%
W 28
 
7.4%
M 27
 
7.1%
A 26
 
6.9%
H 23
 
6.1%
G 23
 
6.1%
L 22
 
5.8%
Other values (10) 80
21.1%
Lowercase Letter
ValueCountFrequency (%)
s 12
32.4%
o 6
16.2%
f 4
 
10.8%
t 3
 
8.1%
k 3
 
8.1%
e 2
 
5.4%
u 2
 
5.4%
a 1
 
2.7%
d 1
 
2.7%
r 1
 
2.7%
Other values (2) 2
 
5.4%
Decimal Number
ValueCountFrequency (%)
2 47
32.2%
1 45
30.8%
0 22
15.1%
3 21
14.4%
5 5
 
3.4%
8 3
 
2.1%
9 2
 
1.4%
4 1
 
0.7%
Other Punctuation
ValueCountFrequency (%)
· 65
47.8%
, 60
44.1%
？ 9
 
6.6%
. 2
 
1.5%
Space Separator
ValueCountFrequency (%)
5538
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 116
100.0%
Open Punctuation
ValueCountFrequency (%)
( 100
100.0%
Close Punctuation
ValueCountFrequency (%)
) 100
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 22558
77.5%
Common 6137
 
21.1%
Latin 416
 
1.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
기 1214
 
5.4%
해 1086
 
4.8%
발 912
 
4.0%
개 827
 
3.7%
술 653
 
2.9%
양 535
 
2.4%
및 434
 
1.9%
구 359
 
1.6%
연 318
 
1.4%
수 315
 
1.4%
Other values (350) 15905
70.5%
Latin
ValueCountFrequency (%)
N 47
11.3%
S 39
 
9.4%
I 35
 
8.4%
T 29
 
7.0%
W 28
 
6.7%
M 27
 
6.5%
A 26
 
6.2%
H 23
 
5.5%
G 23
 
5.5%
L 22
 
5.3%
Other values (22) 117
28.1%
Common
ValueCountFrequency (%)
5538
90.2%
- 116
 
1.9%
( 100
 
1.6%
) 100
 
1.6%
· 65
 
1.1%
, 60
 
1.0%
2 47
 
0.8%
1 45
 
0.7%
0 22
 
0.4%
3 21
 
0.3%
Other values (7) 23
 
0.4%

Most occurring blocks

ValueCountFrequency (%)
Hangul 22556
77.5%
ASCII 6479
 
22.3%
None 74
 
0.3%
Compat Jamo 2
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
5538
85.5%
- 116
 
1.8%
( 100
 
1.5%
) 100
 
1.5%
, 60
 
0.9%
2 47
 
0.7%
N 47
 
0.7%
1 45
 
0.7%
S 39
 
0.6%
I 35
 
0.5%
Other values (37) 352
 
5.4%
Hangul
ValueCountFrequency (%)
기 1214
 
5.4%
해 1086
 
4.8%
발 912
 
4.0%
개 827
 
3.7%
술 653
 
2.9%
양 535
 
2.4%
및 434
 
1.9%
구 359
 
1.6%
연 318
 
1.4%
수 315
 
1.4%
Other values (349) 15903
70.5%
None
ValueCountFrequency (%)
· 65
87.8%
？ 9
 
12.2%
Compat Jamo
ValueCountFrequency (%)
ㆍ 2
100.0%

주관연구기관
Text

Distinct87
Distinct (%)7.3%
Missing0
Missing (%)0.0%
Memory size9.4 KiB
2023-12-12T14:07:31.038519image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length23
Median length19
Mean length11.556675
Min length2

Characters and Unicode

Total characters13764
Distinct characters169
Distinct categories6 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique30 ?
Unique (%)2.5%

Sample

1st row한국지질자원연구원
2nd row한국해양과학기술원
3rd row한국해양과학기술원
4th row한국해양과학기술원
5th row한국해양과학기술원
ValueCountFrequency (%)
한국해양과학기술원 543
28.9%
부설 211
 
11.2%
산학협력단 203
 
10.8%
서울대학교 146
 
7.8%
사)한국선급 137
 
7.3%
선박해양플랜트연구소 133
 
7.1%
극지연구소 80
 
4.3%
전남대학교산학협력단 27
 
1.4%
여수산학협력본부 27
 
1.4%
한국지질자원연구원 25
 
1.3%
Other values (84) 345
18.4%
2023-12-12T14:07:31.403228image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
학 1188
 
8.6%
국 804
 
5.8%
한 797
 
5.8%
해 714
 
5.2%
양 708
 
5.1%
원 702
 
5.1%
686
 
5.0%
기 624
 
4.5%
술 611
 
4.4%
과 579
 
4.2%
Other values (159) 6351
46.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 12662
92.0%
Space Separator 686
 
5.0%
Open Punctuation 196
 
1.4%
Close Punctuation 196
 
1.4%
Decimal Number 12
 
0.1%
Uppercase Letter 12
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
학 1188
 
9.4%
국 804
 
6.3%
한 797
 
6.3%
해 714
 
5.6%
양 708
 
5.6%
원 702
 
5.5%
기 624
 
4.9%
술 611
 
4.8%
과 579
 
4.6%
산 367
 
2.9%
Other values (149) 5568
44.0%
Uppercase Letter
ValueCountFrequency (%)
E 4
33.3%
C 2
16.7%
T 2
16.7%
Y 2
16.7%
D 2
16.7%
Decimal Number
ValueCountFrequency (%)
1 6
50.0%
2 6
50.0%
Space Separator
ValueCountFrequency (%)
686
100.0%
Open Punctuation
ValueCountFrequency (%)
( 196
100.0%
Close Punctuation
ValueCountFrequency (%)
) 196
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 12662
92.0%
Common 1090
 
7.9%
Latin 12
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
학 1188
 
9.4%
국 804
 
6.3%
한 797
 
6.3%
해 714
 
5.6%
양 708
 
5.6%
원 702
 
5.5%
기 624
 
4.9%
술 611
 
4.8%
과 579
 
4.6%
산 367
 
2.9%
Other values (149) 5568
44.0%
Common
ValueCountFrequency (%)
686
62.9%
( 196
 
18.0%
) 196
 
18.0%
1 6
 
0.6%
2 6
 
0.6%
Latin
ValueCountFrequency (%)
E 4
33.3%
C 2
16.7%
T 2
16.7%
Y 2
16.7%
D 2
16.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 12662
92.0%
ASCII 1102
 
8.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
학 1188
 
9.4%
국 804
 
6.3%
한 797
 
6.3%
해 714
 
5.6%
양 708
 
5.6%
원 702
 
5.5%
기 624
 
4.9%
술 611
 
4.8%
과 579
 
4.6%
산 367
 
2.9%
Other values (149) 5568
44.0%
ASCII
ValueCountFrequency (%)
686
62.3%
( 196
 
17.8%
) 196
 
17.8%
1 6
 
0.5%
2 6
 
0.5%
E 4
 
0.4%
C 2
 
0.2%
T 2
 
0.2%
Y 2
 
0.2%
D 2
 
0.2%

수행기관 과제번호
Text

Distinct367
Distinct (%)30.8%
Missing0
Missing (%)0.0%
Memory size9.4 KiB
2023-12-12T14:07:31.679010image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length11
Median length10
Mean length10.154492
Min length10

Characters and Unicode

Total characters12094
Distinct characters11
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique170 ?
Unique (%)14.3%

Sample

1st row20180016-2
2nd row20180447-5
3rd row20180447-5
4th row20180447-2
5th row20180447-2
ValueCountFrequency (%)
20210427-2 55
 
4.6%
20160400-2 41
 
3.4%
20170305-2 27
 
2.3%
20200615-30 23
 
1.9%
20220526-2 23
 
1.9%
20210607-2 22
 
1.8%
20170411-2 22
 
1.8%
20220357-2 21
 
1.8%
20160254-2 18
 
1.5%
20210605-2 18
 
1.5%
Other values (357) 921
77.3%
2023-12-12T14:07:32.152938image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2 3253
26.9%
0 2944
24.3%
1 1327
11.0%
- 1191
 
9.8%
6 699
 
5.8%
4 615
 
5.1%
5 609
 
5.0%
3 536
 
4.4%
7 337
 
2.8%
9 298
 
2.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 10903
90.2%
Dash Punctuation 1191
 
9.8%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 3253
29.8%
0 2944
27.0%
1 1327
12.2%
6 699
 
6.4%
4 615
 
5.6%
5 609
 
5.6%
3 536
 
4.9%
7 337
 
3.1%
9 298
 
2.7%
8 285
 
2.6%
Dash Punctuation
ValueCountFrequency (%)
- 1191
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 12094
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
2 3253
26.9%
0 2944
24.3%
1 1327
11.0%
- 1191
 
9.8%
6 699
 
5.8%
4 615
 
5.1%
5 609
 
5.0%
3 536
 
4.4%
7 337
 
2.8%
9 298
 
2.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 12094
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2 3253
26.9%
0 2944
24.3%
1 1327
11.0%
- 1191
 
9.8%
6 699
 
5.8%
4 615
 
5.1%
5 609
 
5.0%
3 536
 
4.4%
7 337
 
2.8%
9 298
 
2.5%

과제구분
Categorical

Distinct4
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size9.4 KiB
세부
699 
공동
382 
위탁
102 
협동
 
8

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row세부
2nd row위탁
3rd row위탁
4th row세부
5th row세부

Common Values

ValueCountFrequency (%)
세부 699
58.7%
공동 382
32.1%
위탁 102
 
8.6%
협동 8
 
0.7%

Length

2023-12-12T14:07:32.400895image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T14:07:32.512205image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
세부 699
58.7%
공동 382
32.1%
위탁 102
 
8.6%
협동 8
 
0.7%

과제명
Text

Distinct329
Distinct (%)27.6%
Missing0
Missing (%)0.0%
Memory size9.4 KiB
2023-12-12T14:07:32.920123image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length71
Median length48
Mean length25.896725
Min length6

Characters and Unicode

Total characters30843
Distinct characters459
Distinct categories11 ?
Distinct scripts3 ?
Distinct blocks5 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique145 ?
Unique (%)12.2%

Sample

1st row동해남부 해저활성단층 연구 및 해저지진 발생 가능성 평가
2nd row비정형격자 해양예측시스템 구축 및 해양 요소 예측정확도 향상을 위한 딥러닝 기술 개발
3rd row비정형격자 해양예측시스템 구축 및 해양 요소 예측정확도 향상을 위한 딥러닝 기술 개발
4th row해양수치모델링과 지능정보기술을 활용한 해양예측 정확도 향상 연구
5th row해양수치모델링과 지능정보기술을 활용한 해양예측 정확도 향상 연구
ValueCountFrequency (%)
및 454
 
6.3%
개발 437
 
6.1%
기술개발 208
 
2.9%
기반 204
 
2.8%
연구 155
 
2.2%
기술 115
 
1.6%
해양 98
 
1.4%
스마트 85
 
1.2%
구축 76
 
1.1%
과학기술 55
 
0.8%
Other values (1082) 5315
73.8%
2023-12-12T14:07:33.606237image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
6139
 
19.9%
기 1174
 
3.8%
해 987
 
3.2%
발 886
 
2.9%
개 803
 
2.6%
술 588
 
1.9%
양 503
 
1.6%
및 454
 
1.5%
구 357
 
1.2%
이 329
 
1.1%
Other values (449) 18623
60.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 23518
76.3%
Space Separator 6139
 
19.9%
Uppercase Letter 479
 
1.6%
Other Punctuation 164
 
0.5%
Lowercase Letter 142
 
0.5%
Dash Punctuation 134
 
0.4%
Decimal Number 126
 
0.4%
Close Punctuation 69
 
0.2%
Open Punctuation 69
 
0.2%
Letter Number 2
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
기 1174
 
5.0%
해 987
 
4.2%
발 886
 
3.8%
개 803
 
3.4%
술 588
 
2.5%
양 503
 
2.1%
및 454
 
1.9%
구 357
 
1.5%
이 329
 
1.4%
스 327
 
1.4%
Other values (384) 17110
72.8%
Uppercase Letter
ValueCountFrequency (%)
S 57
11.9%
N 52
10.9%
I 45
 
9.4%
M 38
 
7.9%
H 35
 
7.3%
T 29
 
6.1%
G 26
 
5.4%
C 25
 
5.2%
W 24
 
5.0%
P 22
 
4.6%
Other values (12) 126
26.3%
Lowercase Letter
ValueCountFrequency (%)
o 23
16.2%
i 14
 
9.9%
t 12
 
8.5%
r 12
 
8.5%
e 10
 
7.0%
s 8
 
5.6%
n 7
 
4.9%
p 7
 
4.9%
h 6
 
4.2%
m 6
 
4.2%
Other values (11) 37
26.1%
Decimal Number
ValueCountFrequency (%)
1 38
30.2%
2 25
19.8%
0 22
17.5%
3 17
13.5%
7 6
 
4.8%
4 6
 
4.8%
5 5
 
4.0%
8 3
 
2.4%
6 2
 
1.6%
9 2
 
1.6%
Other Punctuation
ValueCountFrequency (%)
, 94
57.3%
· 44
26.8%
/ 13
 
7.9%
？ 9
 
5.5%
. 2
 
1.2%
: 2
 
1.2%
Space Separator
ValueCountFrequency (%)
6139
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 134
100.0%
Close Punctuation
ValueCountFrequency (%)
) 69
100.0%
Open Punctuation
ValueCountFrequency (%)
( 69
100.0%
Letter Number
ValueCountFrequency (%)
Ⅱ 2
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 23518
76.3%
Common 6702
 
21.7%
Latin 623
 
2.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
기 1174
 
5.0%
해 987
 
4.2%
발 886
 
3.8%
개 803
 
3.4%
술 588
 
2.5%
양 503
 
2.1%
및 454
 
1.9%
구 357
 
1.5%
이 329
 
1.4%
스 327
 
1.4%
Other values (384) 17110
72.8%
Latin
ValueCountFrequency (%)
S 57
 
9.1%
N 52
 
8.3%
I 45
 
7.2%
M 38
 
6.1%
H 35
 
5.6%
T 29
 
4.7%
G 26
 
4.2%
C 25
 
4.0%
W 24
 
3.9%
o 23
 
3.7%
Other values (34) 269
43.2%
Common
ValueCountFrequency (%)
6139
91.6%
- 134
 
2.0%
, 94
 
1.4%
) 69
 
1.0%
( 69
 
1.0%
· 44
 
0.7%
1 38
 
0.6%
2 25
 
0.4%
0 22
 
0.3%
3 17
 
0.3%
Other values (11) 51
 
0.8%

Most occurring blocks

ValueCountFrequency (%)
Hangul 23516
76.2%
ASCII 7270
 
23.6%
None 53
 
0.2%
Number Forms 2
 
< 0.1%
Compat Jamo 2
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
6139
84.4%
- 134
 
1.8%
, 94
 
1.3%
) 69
 
0.9%
( 69
 
0.9%
S 57
 
0.8%
N 52
 
0.7%
I 45
 
0.6%
1 38
 
0.5%
M 38
 
0.5%
Other values (52) 535
 
7.4%
Hangul
ValueCountFrequency (%)
기 1174
 
5.0%
해 987
 
4.2%
발 886
 
3.8%
개 803
 
3.4%
술 588
 
2.5%
양 503
 
2.1%
및 454
 
1.9%
구 357
 
1.5%
이 329
 
1.4%
스 327
 
1.4%
Other values (383) 17108
72.8%
None
ValueCountFrequency (%)
· 44
83.0%
？ 9
 
17.0%
Number Forms
ValueCountFrequency (%)
Ⅱ 2
100.0%
Compat Jamo
ValueCountFrequency (%)
ㆍ 2
100.0%

논문명
Text

Distinct1092
Distinct (%)91.7%
Missing0
Missing (%)0.0%
Memory size9.4 KiB
2023-12-12T14:07:34.022700image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length237
Median length148
Mean length96.905122
Min length15

Characters and Unicode

Total characters115414
Distinct characters549
Distinct categories15 ?
Distinct scripts4 ?
Distinct blocks5 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1010 ?
Unique (%)84.8%

Sample

1st rowDistribution and Characteristics of Sandy Sediments along the Northeastern Continental Shelf of Korea In the East Sea
2nd rowMethod for Detection of Meteotsunami Propagation in the Yellow Sea: Reported Cases
3rd rowPerformance Comparisons on Parallel Optimization of Atmospheric and Ocean Numerical Circulation Models Using KISTI Supercomputer Nurion System
4th rowCharacteristics of High Swell-like Waves on East Coast of Korea Observed by Direct Measurements and Reanalysis Data Sets
5th rowFuture Changes in Significant Wave Heights in the East/Japan Sea
ValueCountFrequency (%)
of 910
 
5.4%
the 598
 
3.6%
and 526
 
3.1%
in 501
 
3.0%
on 232
 
1.4%
a 224
 
1.3%
for 202
 
1.2%
sea 170
 
1.0%
using 135
 
0.8%
from 130
 
0.8%
Other values (5184) 13073
78.3%
2023-12-12T14:07:34.642531image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
15646
 
13.6%
e 9077
 
7.9%
a 7701
 
6.7%
i 7669
 
6.6%
n 7123
 
6.2%
o 6852
 
5.9%
t 6715
 
5.8%
r 5527
 
4.8%
s 4801
 
4.2%
l 3636
 
3.2%
Other values (539) 40667
35.2%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 82451
71.4%
Space Separator 15646
 
13.6%
Other Letter 7612
 
6.6%
Uppercase Letter 7554
 
6.5%
Dash Punctuation 688
 
0.6%
Decimal Number 613
 
0.5%
Other Punctuation 551
 
0.5%
Close Punctuation 143
 
0.1%
Open Punctuation 142
 
0.1%
Final Punctuation 6
 
< 0.1%
Other values (5) 8
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
한 230
 
3.0%
의 175
 
2.3%
연 136
 
1.8%
해 136
 
1.8%
기 135
 
1.8%
에 133
 
1.7%
이 131
 
1.7%
구 127
 
1.7%
선 118
 
1.6%
을 115
 
1.5%
Other values (445) 6176
81.1%
Lowercase Letter
ValueCountFrequency (%)
e 9077
11.0%
a 7701
 
9.3%
i 7669
 
9.3%
n 7123
 
8.6%
o 6852
 
8.3%
t 6715
 
8.1%
r 5527
 
6.7%
s 4801
 
5.8%
l 3636
 
4.4%
c 3581
 
4.3%
Other values (20) 19769
24.0%
Uppercase Letter
ValueCountFrequency (%)
S 979
13.0%
A 651
 
8.6%
C 610
 
8.1%
E 512
 
6.8%
P 471
 
6.2%
I 422
 
5.6%
M 415
 
5.5%
D 403
 
5.3%
T 333
 
4.4%
O 326
 
4.3%
Other values (18) 2432
32.2%
Other Punctuation
ValueCountFrequency (%)
, 216
39.2%
: 129
23.4%
. 59
 
10.7%
/ 42
 
7.6%
？ 30
 
5.4%
; 26
 
4.7%
& 25
 
4.5%
· 9
 
1.6%
¡ 5
 
0.9%
# 3
 
0.5%
Other values (4) 7
 
1.3%
Decimal Number
ValueCountFrequency (%)
2 144
23.5%
1 129
21.0%
0 110
17.9%
3 61
10.0%
9 52
 
8.5%
4 28
 
4.6%
8 25
 
4.1%
7 24
 
3.9%
5 21
 
3.4%
6 19
 
3.1%
Close Punctuation
ValueCountFrequency (%)
) 141
98.6%
] 2
 
1.4%
Open Punctuation
ValueCountFrequency (%)
( 140
98.6%
[ 2
 
1.4%
Space Separator
ValueCountFrequency (%)
15646
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 688
100.0%
Final Punctuation
ValueCountFrequency (%)
’ 6
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 4
100.0%
Control
ValueCountFrequency (%)
1
100.0%
Letter Number
ValueCountFrequency (%)
Ⅰ 1
100.0%
Format
ValueCountFrequency (%)
­ 1
100.0%
Math Symbol
ValueCountFrequency (%)
+ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 89995
78.0%
Common 17796
 
15.4%
Hangul 7612
 
6.6%
Greek 11
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
한 230
 
3.0%
의 175
 
2.3%
연 136
 
1.8%
해 136
 
1.8%
기 135
 
1.8%
에 133
 
1.7%
이 131
 
1.7%
구 127
 
1.7%
선 118
 
1.6%
을 115
 
1.5%
Other values (445) 6176
81.1%
Latin
ValueCountFrequency (%)
e 9077
 
10.1%
a 7701
 
8.6%
i 7669
 
8.5%
n 7123
 
7.9%
o 6852
 
7.6%
t 6715
 
7.5%
r 5527
 
6.1%
s 4801
 
5.3%
l 3636
 
4.0%
c 3581
 
4.0%
Other values (44) 27313
30.3%
Common
ValueCountFrequency (%)
15646
87.9%
- 688
 
3.9%
, 216
 
1.2%
2 144
 
0.8%
) 141
 
0.8%
( 140
 
0.8%
: 129
 
0.7%
1 129
 
0.7%
0 110
 
0.6%
3 61
 
0.3%
Other values (25) 392
 
2.2%
Greek
ValueCountFrequency (%)
β 7
63.6%
Δ 1
 
9.1%
δ 1
 
9.1%
α 1
 
9.1%
κ 1
 
9.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 107734
93.3%
Hangul 7612
 
6.6%
None 61
 
0.1%
Punctuation 6
 
< 0.1%
Number Forms 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
15646
14.5%
e 9077
 
8.4%
a 7701
 
7.1%
i 7669
 
7.1%
n 7123
 
6.6%
o 6852
 
6.4%
t 6715
 
6.2%
r 5527
 
5.1%
s 4801
 
4.5%
l 3636
 
3.4%
Other values (72) 32987
30.6%
Hangul
ValueCountFrequency (%)
한 230
 
3.0%
의 175
 
2.3%
연 136
 
1.8%
해 136
 
1.8%
기 135
 
1.8%
에 133
 
1.7%
이 131
 
1.7%
구 127
 
1.7%
선 118
 
1.6%
을 115
 
1.5%
Other values (445) 6176
81.1%
None
ValueCountFrequency (%)
？ 30
49.2%
· 9
 
14.8%
β 7
 
11.5%
¡ 5
 
8.2%
Æ 5
 
8.2%
Δ 1
 
1.6%
δ 1
 
1.6%
α 1
 
1.6%
κ 1
 
1.6%
­ 1
 
1.6%
Punctuation
ValueCountFrequency (%)
’ 6
100.0%
Number Forms
ValueCountFrequency (%)
Ⅰ 1
100.0%

논문(학술지)구분
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct5
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size9.4 KiB
국외학술지
859 
국내학술지
263 
국내기타논문집
 
63
국외기타논문집
 
5
국내학술대회논문집
 
1

Length

Max length9
Median length5
Mean length5.1175483
Min length5

Unique

Unique1 ?
Unique (%)0.1%

Sample

1st row국외학술지
2nd row국외학술지
3rd row국외학술지
4th row국외학술지
5th row국외학술지

Common Values

ValueCountFrequency (%)
국외학술지 859
72.1%
국내학술지 263
 
22.1%
국내기타논문집 63
 
5.3%
국외기타논문집 5
 
0.4%
국내학술대회논문집 1
 
0.1%

Length

2023-12-12T14:07:34.888629image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T14:07:35.030952image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
국외학술지 859
72.1%
국내학술지 263
 
22.1%
국내기타논문집 63
 
5.3%
국외기타논문집 5
 
0.4%
국내학술대회논문집 1
 
0.1%

과학기술논문색인지수(SCI(E))구분
Categorical

HIGH CORRELATION 

Distinct2
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size9.4 KiB
SCI
860 
비SCI
331 

Length

Max length4
Median length3
Mean length3.2779177
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowSCI
2nd rowSCI
3rd rowSCI
4th rowSCI
5th rowSCI

Common Values

ValueCountFrequency (%)
SCI 860
72.2%
비SCI 331
 
27.8%

Length

2023-12-12T14:07:35.160814image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T14:07:35.271533image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
sci 860
72.2%
비sci 331
 
27.8%

개제일
Date

Distinct466
Distinct (%)39.1%
Missing0
Missing (%)0.0%
Memory size9.4 KiB
Minimum2020-01-01 00:00:00
Maximum2023-10-01 00:00:00
2023-12-12T14:07:35.396447image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:07:35.582390image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

상태
Categorical

CONSTANT 

Distinct1
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size9.4 KiB
승인(확정)
1191 

Length

Max length6
Median length6
Mean length6
Min length6

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row승인(확정)
2nd row승인(확정)
3rd row승인(확정)
4th row승인(확정)
5th row승인(확정)

Common Values

ValueCountFrequency (%)
승인(확정) 1191
100.0%

Length

2023-12-12T14:07:35.759466image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T14:07:35.879986image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
승인(확정 1191
100.0%

활용구분
Categorical

Distinct2
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size9.4 KiB
조사분석
1040 
연구개발결과 활용보고
151 

Length

Max length11
Median length4
Mean length4.8874895
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row조사분석
2nd row연구개발결과 활용보고
3rd row조사분석
4th row조사분석
5th row조사분석

Common Values

ValueCountFrequency (%)
조사분석 1040
87.3%
연구개발결과 활용보고 151
 
12.7%

Length

2023-12-12T14:07:36.032121image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T14:07:36.178696image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
조사분석 1040
77.5%
연구개발결과 151
 
11.3%
활용보고 151
 
11.3%

학술지명
Text

Distinct585
Distinct (%)49.1%
Missing0
Missing (%)0.0%
Memory size9.4 KiB
2023-12-12T14:07:36.535371image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length148
Median length78
Mean length24.36356
Min length2

Characters and Unicode

Total characters29017
Distinct characters236
Distinct categories11 ?
Distinct scripts4 ?
Distinct blocks5 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique403 ?
Unique (%)33.8%

Sample

1st rowJournal of Coastal Research
2nd rowJournal of Coastal Research
3rd rowApplied Sciences_basel(MDPI)
4th rowJournal of Coastal Research
5th rowJournal of Coastal Research
ValueCountFrequency (%)
of 323
 
8.3%
journal 262
 
6.7%
marine 217
 
5.6%
science 215
 
5.5%
and 180
 
4.6%
in 98
 
2.5%
the 95
 
2.4%
frontiers 87
 
2.2%
engineering 87
 
2.2%
research 74
 
1.9%
Other values (589) 2253
57.9%
2023-12-12T14:07:37.193404image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2764
 
9.5%
e 2467
 
8.5%
n 2359
 
8.1%
i 1844
 
6.4%
o 1837
 
6.3%
a 1635
 
5.6%
r 1564
 
5.4%
c 1163
 
4.0%
t 1089
 
3.8%
l 1024
 
3.5%
Other values (226) 11271
38.8%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 19410
66.9%
Uppercase Letter 3319
 
11.4%
Other Letter 3109
 
10.7%
Space Separator 2764
 
9.5%
Decimal Number 223
 
0.8%
Other Punctuation 113
 
0.4%
Math Symbol 23
 
0.1%
Close Punctuation 20
 
0.1%
Open Punctuation 20
 
0.1%
Dash Punctuation 15
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
학 319
 
10.3%
회 314
 
10.1%
한 204
 
6.6%
지 191
 
6.1%
국 183
 
5.9%
해 134
 
4.3%
양 104
 
3.3%
술 102
 
3.3%
대 77
 
2.5%
경 62
 
2.0%
Other values (150) 1419
45.6%
Lowercase Letter
ValueCountFrequency (%)
e 2467
12.7%
n 2359
12.2%
i 1844
9.5%
o 1837
9.5%
a 1635
8.4%
r 1564
8.1%
c 1163
 
6.0%
t 1089
 
5.6%
l 1024
 
5.3%
s 973
 
5.0%
Other values (16) 3455
17.8%
Uppercase Letter
ValueCountFrequency (%)
S 424
12.8%
E 375
11.3%
M 332
 
10.0%
J 250
 
7.5%
A 219
 
6.6%
R 197
 
5.9%
I 191
 
5.8%
C 164
 
4.9%
O 151
 
4.5%
T 143
 
4.3%
Other values (16) 873
26.3%
Decimal Number
ValueCountFrequency (%)
2 152
68.2%
0 50
 
22.4%
1 9
 
4.0%
7 5
 
2.2%
3 4
 
1.8%
9 1
 
0.4%
8 1
 
0.4%
6 1
 
0.4%
Other Punctuation
ValueCountFrequency (%)
& 33
29.2%
: 27
23.9%
, 20
17.7%
. 19
16.8%
· 7
 
6.2%
？ 5
 
4.4%
# 1
 
0.9%
; 1
 
0.9%
Close Punctuation
ValueCountFrequency (%)
) 18
90.0%
] 2
 
10.0%
Open Punctuation
ValueCountFrequency (%)
( 18
90.0%
[ 2
 
10.0%
Space Separator
ValueCountFrequency (%)
2764
100.0%
Math Symbol
ValueCountFrequency (%)
= 23
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 15
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 22729
78.3%
Common 3179
 
11.0%
Hangul 3093
 
10.7%
Han 16
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
학 319
 
10.3%
회 314
 
10.2%
한 204
 
6.6%
지 191
 
6.2%
국 183
 
5.9%
해 134
 
4.3%
양 104
 
3.4%
술 102
 
3.3%
대 77
 
2.5%
경 62
 
2.0%
Other values (142) 1403
45.4%
Latin
ValueCountFrequency (%)
e 2467
 
10.9%
n 2359
 
10.4%
i 1844
 
8.1%
o 1837
 
8.1%
a 1635
 
7.2%
r 1564
 
6.9%
c 1163
 
5.1%
t 1089
 
4.8%
l 1024
 
4.5%
s 973
 
4.3%
Other values (42) 6774
29.8%
Common
ValueCountFrequency (%)
2764
86.9%
2 152
 
4.8%
0 50
 
1.6%
& 33
 
1.0%
: 27
 
0.8%
= 23
 
0.7%
, 20
 
0.6%
. 19
 
0.6%
) 18
 
0.6%
( 18
 
0.6%
Other values (14) 55
 
1.7%
Han
ValueCountFrequency (%)
水 2
12.5%
敎 2
12.5%
洋 2
12.5%
硏 2
12.5%
海 2
12.5%
究 2
12.5%
育 2
12.5%
産 2
12.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 25896
89.2%
Hangul 3089
 
10.6%
CJK 16
 
0.1%
None 12
 
< 0.1%
Compat Jamo 4
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2764
 
10.7%
e 2467
 
9.5%
n 2359
 
9.1%
i 1844
 
7.1%
o 1837
 
7.1%
a 1635
 
6.3%
r 1564
 
6.0%
c 1163
 
4.5%
t 1089
 
4.2%
l 1024
 
4.0%
Other values (64) 8150
31.5%
Hangul
ValueCountFrequency (%)
학 319
 
10.3%
회 314
 
10.2%
한 204
 
6.6%
지 191
 
6.2%
국 183
 
5.9%
해 134
 
4.3%
양 104
 
3.4%
술 102
 
3.3%
대 77
 
2.5%
경 62
 
2.0%
Other values (141) 1399
45.3%
None
ValueCountFrequency (%)
· 7
58.3%
？ 5
41.7%
Compat Jamo
ValueCountFrequency (%)
ㆍ 4
100.0%
CJK
ValueCountFrequency (%)
水 2
12.5%
敎 2
12.5%
洋 2
12.5%
硏 2
12.5%
海 2
12.5%
究 2
12.5%
育 2
12.5%
産 2
12.5%

국제표준도서번호(ISBN)_국제표준연속간행물번호(ISSN)
Text

Distinct415
Distinct (%)34.8%
Missing0
Missing (%)0.0%
Memory size9.4 KiB
2023-12-12T14:07:37.549495image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length9
Median length9
Mean length9
Min length9

Characters and Unicode

Total characters10719
Distinct characters13
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique260 ?
Unique (%)21.8%

Sample

1st row0749-0208
2nd row0749-0208
3rd row2076-3417
4th row1551-5036
5th row1551-5036
ValueCountFrequency (%)
2296-7745 70
 
5.9%
0000-0000 64
 
5.4%
2077-1312 49
 
4.1%
2288-0089 30
 
2.5%
2076-3417 27
 
2.3%
1229-3431 24
 
2.0%
0048-9697 23
 
1.9%
2072-4292 22
 
1.8%
2045-2322 21
 
1.8%
0025-326x 21
 
1.8%
Other values (403) 840
70.5%
2023-12-12T14:07:38.094361image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 1610
15.0%
2 1590
14.8%
- 1191
11.1%
1 1026
9.6%
7 955
8.9%
3 801
7.5%
9 759
7.1%
4 748
7.0%
6 670
6.3%
5 656
6.1%
Other values (3) 713
6.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 9470
88.3%
Dash Punctuation 1191
 
11.1%
Uppercase Letter 54
 
0.5%
Lowercase Letter 4
 
< 0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 1610
17.0%
2 1590
16.8%
1 1026
10.8%
7 955
10.1%
3 801
8.5%
9 759
8.0%
4 748
7.9%
6 670
7.1%
5 656
6.9%
8 655
6.9%
Dash Punctuation
ValueCountFrequency (%)
- 1191
100.0%
Uppercase Letter
ValueCountFrequency (%)
X 54
100.0%
Lowercase Letter
ValueCountFrequency (%)
x 4
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 10661
99.5%
Latin 58
 
0.5%

Most frequent character per script

Common
ValueCountFrequency (%)
0 1610
15.1%
2 1590
14.9%
- 1191
11.2%
1 1026
9.6%
7 955
9.0%
3 801
7.5%
9 759
7.1%
4 748
7.0%
6 670
6.3%
5 656
6.2%
Latin
ValueCountFrequency (%)
X 54
93.1%
x 4
 
6.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 10719
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 1610
15.0%
2 1590
14.8%
- 1191
11.1%
1 1026
9.6%
7 955
8.9%
3 801
7.5%
9 759
7.1%
4 748
7.0%
6 670
6.3%
5 656
6.1%
Other values (3) 713
6.7%

주저자
Text

Distinct970
Distinct (%)81.4%
Missing0
Missing (%)0.0%
Memory size9.4 KiB
2023-12-12T14:07:38.541698image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length91
Median length41
Mean length9.3073048
Min length1

Characters and Unicode

Total characters11085
Distinct characters254
Distinct categories9 ?
Distinct scripts3 ?
Distinct blocks4 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique816 ?
Unique (%)68.5%

Sample

1st rowSo-Ra Kim
2nd rowMyung-Seok Kim
3rd rowLim, Chaewook
4th rowKi-Young Heo
5th rowChan Joo Jang
ValueCountFrequency (%)
kim 110
 
5.1%
lee 83
 
3.8%
park 25
 
1.2%
jung 23
 
1.1%
seo 22
 
1.0%
choi 20
 
0.9%
shin 18
 
0.8%
yoon 16
 
0.7%
young 15
 
0.7%
hwang 15
 
0.7%
Other values (1162) 1813
83.9%
2023-12-12T14:07:39.193817image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
991
 
8.9%
n 976
 
8.8%
o 758
 
6.8%
e 677
 
6.1%
a 631
 
5.7%
i 473
 
4.3%
u 464
 
4.2%
g 420
 
3.8%
h 335
 
3.0%
J 229
 
2.1%
Other values (244) 5131
46.3%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 5997
54.1%
Uppercase Letter 1831
 
16.5%
Other Letter 1677
 
15.1%
Space Separator 991
 
8.9%
Other Punctuation 409
 
3.7%
Dash Punctuation 177
 
1.6%
Close Punctuation 1
 
< 0.1%
Open Punctuation 1
 
< 0.1%
Final Punctuation 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
김 112
 
6.7%
이 81
 
4.8%
박 52
 
3.1%
정 49
 
2.9%
영 42
 
2.5%
현 41
 
2.4%
진 39
 
2.3%
호 34
 
2.0%
수 30
 
1.8%
상 28
 
1.7%
Other values (181) 1169
69.7%
Lowercase Letter
ValueCountFrequency (%)
n 976
16.3%
o 758
12.6%
e 677
11.3%
a 631
10.5%
i 473
7.9%
u 464
7.7%
g 420
7.0%
h 335
 
5.6%
m 222
 
3.7%
y 204
 
3.4%
Other values (16) 837
14.0%
Uppercase Letter
ValueCountFrequency (%)
J 229
12.5%
S 207
11.3%
K 192
10.5%
H 184
 
10.0%
Y 136
 
7.4%
L 116
 
6.3%
C 113
 
6.2%
M 76
 
4.2%
D 61
 
3.3%
A 57
 
3.1%
Other values (16) 460
25.1%
Other Punctuation
ValueCountFrequency (%)
, 215
52.6%
; 139
34.0%
. 52
 
12.7%
？ 1
 
0.2%
/ 1
 
0.2%
* 1
 
0.2%
Space Separator
ValueCountFrequency (%)
991
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 177
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1
100.0%
Final Punctuation
ValueCountFrequency (%)
’ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 7828
70.6%
Hangul 1677
 
15.1%
Common 1580
 
14.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
김 112
 
6.7%
이 81
 
4.8%
박 52
 
3.1%
정 49
 
2.9%
영 42
 
2.5%
현 41
 
2.4%
진 39
 
2.3%
호 34
 
2.0%
수 30
 
1.8%
상 28
 
1.7%
Other values (181) 1169
69.7%
Latin
ValueCountFrequency (%)
n 976
 
12.5%
o 758
 
9.7%
e 677
 
8.6%
a 631
 
8.1%
i 473
 
6.0%
u 464
 
5.9%
g 420
 
5.4%
h 335
 
4.3%
J 229
 
2.9%
m 222
 
2.8%
Other values (42) 2643
33.8%
Common
ValueCountFrequency (%)
991
62.7%
, 215
 
13.6%
- 177
 
11.2%
; 139
 
8.8%
. 52
 
3.3%
？ 1
 
0.1%
/ 1
 
0.1%
) 1
 
0.1%
( 1
 
0.1%
’ 1
 
0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 9406
84.9%
Hangul 1677
 
15.1%
None 1
 
< 0.1%
Punctuation 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
991
 
10.5%
n 976
 
10.4%
o 758
 
8.1%
e 677
 
7.2%
a 631
 
6.7%
i 473
 
5.0%
u 464
 
4.9%
g 420
 
4.5%
h 335
 
3.6%
J 229
 
2.4%
Other values (51) 3452
36.7%
Hangul
ValueCountFrequency (%)
김 112
 
6.7%
이 81
 
4.8%
박 52
 
3.1%
정 49
 
2.9%
영 42
 
2.5%
현 41
 
2.4%
진 39
 
2.3%
호 34
 
2.0%
수 30
 
1.8%
상 28
 
1.7%
Other values (181) 1169
69.7%
None
ValueCountFrequency (%)
？ 1
100.0%
Punctuation
ValueCountFrequency (%)
’ 1
100.0%

연구책임자 포함여부
Boolean

Distinct2
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size1.3 KiB
True
660 
False
531 
ValueCountFrequency (%)
True 660
55.4%
False 531
44.6%
2023-12-12T14:07:39.364976image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Interactions

2023-12-12T14:07:27.165201image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:07:26.926959image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:07:27.279692image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:07:27.046070image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T14:07:39.466084image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
성과년도예산년도과제접수번호사업명주관연구기관과제구분논문(학술지)구분과학기술논문색인지수(SCI(E))구분활용구분연구책임자 포함여부
성과년도1.0000.9560.4030.8830.5750.4210.1110.2030.2490.104
예산년도0.9561.0000.4180.8220.6200.3080.1170.1930.1460.127
과제접수번호0.4030.4181.0000.8900.7290.2490.2410.1600.0950.078
사업명0.8830.8220.8901.0000.9940.7040.6700.6630.5540.503
주관연구기관0.5750.6200.7290.9941.0000.7430.6620.6180.5610.325
과제구분0.4210.3080.2490.7040.7431.0000.1710.3330.2700.395
논문(학술지)구분0.1110.1170.2410.6700.6620.1711.0000.7550.0860.040
과학기술논문색인지수(SCI(E))구분0.2030.1930.1600.6630.6180.3330.7551.0000.1200.103
활용구분0.2490.1460.0950.5540.5610.2700.0860.1201.0000.083
연구책임자 포함여부0.1040.1270.0780.5030.3250.3950.0400.1030.0831.000
2023-12-12T14:07:39.967705image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연구책임자 포함여부성과년도과제구분논문(학술지)구분활용구분과학기술논문색인지수(SCI(E))구분
연구책임자 포함여부1.0000.0690.2650.0480.0530.066
성과년도0.0691.0000.1740.0900.1650.135
과제구분0.2650.1741.0000.1400.1790.222
논문(학술지)구분0.0480.0900.1401.0000.1050.889
활용구분0.0530.1650.1790.1051.0000.077
과학기술논문색인지수(SCI(E))구분0.0660.1350.2220.8890.0771.000
2023-12-12T14:07:40.132597image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
예산년도과제접수번호성과년도과제구분논문(학술지)구분과학기술논문색인지수(SCI(E))구분활용구분연구책임자 포함여부
예산년도1.0000.5530.8620.2080.0740.1370.1020.090
과제접수번호0.5531.0000.3510.2080.0880.1930.1140.136
성과년도0.8620.3511.0000.1740.0900.1350.1650.069
과제구분0.2080.2080.1741.0000.1400.2220.1790.265
논문(학술지)구분0.0740.0880.0900.1401.0000.8890.1050.048
과학기술논문색인지수(SCI(E))구분0.1370.1930.1350.2220.8891.0000.0770.066
활용구분0.1020.1140.1650.1790.1050.0771.0000.053
연구책임자 포함여부0.0900.1360.0690.2650.0480.0660.0531.000

Missing values

2023-12-12T14:07:27.492910image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T14:07:27.828232image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.

Sample

성과년도예산년도과제접수번호사업명과제명(총괄)주관연구기관수행기관 과제번호과제구분과제명논문명논문(학술지)구분과학기술논문색인지수(SCI(E))구분개제일상태활용구분학술지명국제표준도서번호(ISBN)_국제표준연속간행물번호(ISSN)주저자연구책임자 포함여부
02020202020180016해양과학조사 및 예보기술개발동해남부 해저활성단층 연구 및 해저지진 발생 가능성 평가한국지질자원연구원20180016-2세부동해남부 해저활성단층 연구 및 해저지진 발생 가능성 평가Distribution and Characteristics of Sandy Sediments along the Northeastern Continental Shelf of Korea In the East Sea국외학술지SCI2020-06-17승인(확정)조사분석Journal of Coastal Research0749-0208So-Ra KimN
12020202020180447해양과학조사 및 예보기술개발해양수치모델링과 지능정보기술을 활용한 해양예측 정확도 향상 연구한국해양과학기술원20180447-5위탁비정형격자 해양예측시스템 구축 및 해양 요소 예측정확도 향상을 위한 딥러닝 기술 개발Method for Detection of Meteotsunami Propagation in the Yellow Sea: Reported Cases국외학술지SCI2020-06-17승인(확정)연구개발결과 활용보고Journal of Coastal Research0749-0208Myung-Seok KimY
22020202020180447해양과학조사 및 예보기술개발해양수치모델링과 지능정보기술을 활용한 해양예측 정확도 향상 연구한국해양과학기술원20180447-5위탁비정형격자 해양예측시스템 구축 및 해양 요소 예측정확도 향상을 위한 딥러닝 기술 개발Performance Comparisons on Parallel Optimization of Atmospheric and Ocean Numerical Circulation Models Using KISTI Supercomputer Nurion System국외학술지SCI2020-04-21승인(확정)조사분석Applied Sciences_basel(MDPI)2076-3417Lim, ChaewookN
32020202020180447해양과학조사 및 예보기술개발해양수치모델링과 지능정보기술을 활용한 해양예측 정확도 향상 연구한국해양과학기술원20180447-2세부해양수치모델링과 지능정보기술을 활용한 해양예측 정확도 향상 연구Characteristics of High Swell-like Waves on East Coast of Korea Observed by Direct Measurements and Reanalysis Data Sets국외학술지SCI2020-05-26승인(확정)조사분석Journal of Coastal Research1551-5036Ki-Young HeoN
42020202020180447해양과학조사 및 예보기술개발해양수치모델링과 지능정보기술을 활용한 해양예측 정확도 향상 연구한국해양과학기술원20180447-2세부해양수치모델링과 지능정보기술을 활용한 해양예측 정확도 향상 연구Future Changes in Significant Wave Heights in the East/Japan Sea국외학술지SCI2020-05-26승인(확정)조사분석Journal of Coastal Research1551-5036Chan Joo JangN
52020202020180447해양과학조사 및 예보기술개발해양수치모델링과 지능정보기술을 활용한 해양예측 정확도 향상 연구한국해양과학기술원20180447-2세부해양수치모델링과 지능정보기술을 활용한 해양예측 정확도 향상 연구Hindcasting of Search and Rescue Cases using the Trajectory Model based on KOOS (Korea Operational Oceanographic System)국외학술지SCI2020-05-26승인(확정)조사분석Journal of Coastal Research1551-5036Jung-Woon ChoiN
62020202020180447해양과학조사 및 예보기술개발해양수치모델링과 지능정보기술을 활용한 해양예측 정확도 향상 연구한국해양과학기술원20180447-2세부해양수치모델링과 지능정보기술을 활용한 해양예측 정확도 향상 연구Simulation of Storm Surge due to the Changes of Typhoon Moving Speed in the South Coast of Korean Peninsula국외학술지SCI2020-05-26승인(확정)조사분석Journal of Coastal Research1551-5036Yeong-Yeon KwonN
72020202020180447해양과학조사 및 예보기술개발해양수치모델링과 지능정보기술을 활용한 해양예측 정확도 향상 연구한국해양과학기술원20180447-2세부해양수치모델링과 지능정보기술을 활용한 해양예측 정확도 향상 연구Three dimensional numerical modeling using a multi-level nesting system for identifying a Water layer suitable for scallop farming in Tongyeong, Korea국외학술지SCI2020-05-06승인(확정)조사분석Aquacultural Engineering0144-8609Yeon S. ChangN
82020202020180447해양과학조사 및 예보기술개발해양수치모델링과 지능정보기술을 활용한 해양예측 정확도 향상 연구한국해양과학기술원20180447-2세부해양수치모델링과 지능정보기술을 활용한 해양예측 정확도 향상 연구고해상도 파랑후측에서 나타난 동해 파랑기후의 40년 선형추세국내학술대회논문집비SCI2020-04-30승인(확정)조사분석한국연안방재학회지2288-7903김기호N
92020201920180456해양과학조사 및 예보기술개발다종위성 기반 해양 현안대응 실용화 기술 개발한국해양과학기술원20180456-2세부다종위성 기반 해양 현안대응 실용화 기술 개발Sea Fog Identification From GOCI Images Using CNN Transfer Learning Models국외학술지SCI2020-02-11승인(확정)조사분석Electronics2079-9292Ho-Kun Jeon(전호군)N
성과년도예산년도과제접수번호사업명과제명(총괄)주관연구기관수행기관 과제번호과제구분과제명논문명논문(학술지)구분과학기술논문색인지수(SCI(E))구분개제일상태활용구분학술지명국제표준도서번호(ISBN)_국제표준연속간행물번호(ISSN)주저자연구책임자 포함여부
11812023202320220534해양유해물질 오염원 추적기법 개발해양유해물질오염원추적기법 개발충남대학교산학협력단20220534-2세부해양유해물질오염원추적기법 개발Characterization of microalgal toxicants in the sediments from an industrial area: Application of advanced effect-directed analysis with multiple endpoint bioassays국외학술지SCI2023-03-01승인(확정)조사분석Environment International1873-6750Seong-Ah AnY
11822023202320220534해양유해물질 오염원 추적기법 개발해양유해물질오염원추적기법 개발충남대학교산학협력단20220534-2세부해양유해물질오염원추적기법 개발Historical trends of traditional, emerging, and halogenated polycyclic aromatic hydrocarbons recorded in core sediments from the coastal areas of the Yellow and Bohai seas국외학술지SCI2023-08-01승인(확정)조사분석Environment International1873-6750Seo Joon YoonY
11832023202320220534해양유해물질 오염원 추적기법 개발해양유해물질오염원추적기법 개발충남대학교산학협력단20220534-2세부해양유해물질오염원추적기법 개발해양환경에서 유기물 오염 관리 지표로서 총유기탄소(TOC)의 적용 가능성 연구국내학술지비SCI2023-02-25승인(확정)조사분석Journal of the Korean Society for Marine Environment & Energy2288-0089Junsik WooY
11842023202320220534해양유해물질 오염원 추적기법 개발해양유해물질오염원추적기법 개발충남대학교산학협력단20220534-2세부해양유해물질오염원추적기법 개발Isotopic investigation of sources and processes affecting gaseous and particulate bound mercury in the east coast, South Korea affecting gaseous and particulate bound mercury in the east coast, South Korea국외학술지SCI2023-05-20승인(확정)조사분석Science of the Total Environment1879-1026Hoin LeeY
11852023202320220534해양유해물질 오염원 추적기법 개발해양유해물질오염원추적기법 개발충남대학교산학협력단20220534-2세부해양유해물질오염원추적기법 개발Spatial distribution and temporal trends of cyclic and linear siloxanes in sediment from semi-enclosed and industrialized bays of Korea, in 2013 and 2021국외학술지SCI2023-04-19승인(확정)조사분석Frontiers in Marine science2296-7745Wenming ChenY
11862023202320220534해양유해물질 오염원 추적기법 개발해양유해물질오염원추적기법 개발충남대학교산학협력단20220534-2세부해양유해물질오염원추적기법 개발Determination and comparison of freely dissolved PAHs using different types of passive samplers in freshwater국외학술지SCI2023-09-20승인(확정)조사분석Science of the Total Environment1879-1026Na Yeong KimY
11872023202320220534해양유해물질 오염원 추적기법 개발해양유해물질오염원추적기법 개발충남대학교산학협력단20220534-2세부해양유해물질오염원추적기법 개발Trace element characterization and source identification of particulate matter of different sizes in Hanoi, Vietnam국외학술지SCI2023-03-01승인(확정)조사분석Urban Climate2212-0955Quang Tran VuongY
11882023202320220534해양유해물질 오염원 추적기법 개발해양유해물질오염원추적기법 개발충남대학교산학협력단20220534-2세부해양유해물질오염원추적기법 개발인공지능 모델을 활용한 실시간 수질 평가지수 예측국내학술지비SCI2023-02-25승인(확정)조사분석Journal of the Korean Society for Marine Environment & Energy2288-0089Soobin KimN
11892023202320220534해양유해물질 오염원 추적기법 개발해양유해물질오염원추적기법 개발충남대학교산학협력단20220534-2세부해양유해물질오염원추적기법 개발Chemical characterization of sub-micron aerosols over the East Sea (Sea of Japan)국외학술지SCI2023-01-15승인(확정)조사분석Science of The Total Environment1879-1026Andrew LohY
11902023202320220567해양레저장비 및 안전기술 개발해양레저선박 표준 제작기술 및 수중레저활동 안전지원 로봇 개발한국로봇융합연구원20220567-2세부해양레저선박 표준 제작기술 및 수중레저활동 안전지원 로봇 개발An Experimental Study on Trajectory Tracking Control of Torpedo-like AUVs Using Coupled Error Dynamics국외학술지SCI2023-06-30승인(확정)조사분석Journal of Marine Science and Engineering2077-1312Gun Rae ChoN

Duplicate rows

Most frequently occurring

성과년도예산년도과제접수번호사업명과제명(총괄)주관연구기관수행기관 과제번호과제구분과제명논문명논문(학술지)구분과학기술논문색인지수(SCI(E))구분개제일상태활용구분학술지명국제표준도서번호(ISBN)_국제표준연속간행물번호(ISSN)주저자연구책임자 포함여부# duplicates
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