Overview

Dataset statistics

Number of variables8
Number of observations101
Missing cells159
Missing cells (%)19.7%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory6.4 KiB
Average record size in memory65.3 B

Variable types

Text5
DateTime2
Boolean1

Dataset

Description산림과학기술정보서비스(FTIS) 시스템 연구과제 최종보고서에 대한 데이터로 국문보고서명, 연구책임자, 과제번호 등의 정보를 제공합니다.
Author산림청
URLhttps://www.data.go.kr/data/15091879/fileData.do

Alerts

보안여부 is highly imbalanced (71.6%)Imbalance
국문색인어 has 79 (78.2%) missing valuesMissing
영문색인어 has 80 (79.2%) missing valuesMissing
과제번호 has unique valuesUnique
국문보고서명 has unique valuesUnique

Reproduction

Analysis started2024-04-21 10:16:13.667081
Analysis finished2024-04-21 10:16:15.468357
Duration1.8 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

과제번호
Text

UNIQUE 

Distinct101
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size936.0 B
2024-04-21T19:16:16.446576image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length8
Median length8
Mean length8
Min length8

Characters and Unicode

Total characters808
Distinct characters12
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique101 ?
Unique (%)100.0%

Sample

1st rowPJ000088
2nd rowPJ000101
3rd rowPJ000121
4th rowPJ000116
5th rowPJ000010
ValueCountFrequency (%)
pj000088 1
 
1.0%
pj000243 1
 
1.0%
pj000057 1
 
1.0%
pj000054 1
 
1.0%
pj000065 1
 
1.0%
pj000059 1
 
1.0%
pj000095 1
 
1.0%
pj000091 1
 
1.0%
pj000118 1
 
1.0%
pj000115 1
 
1.0%
Other values (91) 91
90.1%
2024-04-21T19:16:17.987685image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 381
47.2%
P 101
 
12.5%
J 101
 
12.5%
2 44
 
5.4%
1 41
 
5.1%
5 29
 
3.6%
8 22
 
2.7%
4 20
 
2.5%
3 19
 
2.4%
6 18
 
2.2%
Other values (2) 32
 
4.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 606
75.0%
Uppercase Letter 202
 
25.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 381
62.9%
2 44
 
7.3%
1 41
 
6.8%
5 29
 
4.8%
8 22
 
3.6%
4 20
 
3.3%
3 19
 
3.1%
6 18
 
3.0%
7 18
 
3.0%
9 14
 
2.3%
Uppercase Letter
ValueCountFrequency (%)
P 101
50.0%
J 101
50.0%

Most occurring scripts

ValueCountFrequency (%)
Common 606
75.0%
Latin 202
 
25.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 381
62.9%
2 44
 
7.3%
1 41
 
6.8%
5 29
 
4.8%
8 22
 
3.6%
4 20
 
3.3%
3 19
 
3.1%
6 18
 
3.0%
7 18
 
3.0%
9 14
 
2.3%
Latin
ValueCountFrequency (%)
P 101
50.0%
J 101
50.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 808
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 381
47.2%
P 101
 
12.5%
J 101
 
12.5%
2 44
 
5.4%
1 41
 
5.1%
5 29
 
3.6%
8 22
 
2.7%
4 20
 
2.5%
3 19
 
2.4%
6 18
 
2.2%
Other values (2) 32
 
4.0%

제출일
Date

Distinct21
Distinct (%)20.8%
Missing0
Missing (%)0.0%
Memory size936.0 B
Minimum2017-07-04 00:00:00
Maximum2021-04-30 00:00:00
2024-04-21T19:16:18.368136image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T19:16:18.751242image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=21)

발행일
Date

Distinct16
Distinct (%)15.8%
Missing0
Missing (%)0.0%
Memory size936.0 B
Minimum2017-06-01 00:00:00
Maximum2021-04-30 00:00:00
2024-04-21T19:16:19.106797image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T19:16:19.480553image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=16)

연구책임자명
Text

Distinct90
Distinct (%)89.1%
Missing0
Missing (%)0.0%
Memory size936.0 B
2024-04-21T19:16:20.550909image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters303
Distinct characters81
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique81 ?
Unique (%)80.2%

Sample

1st row배*홍
2nd row유*열
3rd row송*선
4th row박*준
5th row김*용
ValueCountFrequency (%)
박*준 3
 
3.0%
김*현 3
 
3.0%
이*석 2
 
2.0%
이*환 2
 
2.0%
안*상 2
 
2.0%
이*희 2
 
2.0%
김*균 2
 
2.0%
최*랑 2
 
2.0%
이*우 2
 
2.0%
이*두 1
 
1.0%
Other values (80) 80
79.2%
2024-04-21T19:16:21.723428image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
* 101
33.3%
김 19
 
6.3%
이 18
 
5.9%
정 10
 
3.3%
박 7
 
2.3%
최 7
 
2.3%
현 6
 
2.0%
영 6
 
2.0%
환 5
 
1.7%
수 4
 
1.3%
Other values (71) 120
39.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 202
66.7%
Other Punctuation 101
33.3%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
김 19
 
9.4%
이 18
 
8.9%
정 10
 
5.0%
박 7
 
3.5%
최 7
 
3.5%
현 6
 
3.0%
영 6
 
3.0%
환 5
 
2.5%
수 4
 
2.0%
하 4
 
2.0%
Other values (70) 116
57.4%
Other Punctuation
ValueCountFrequency (%)
* 101
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 202
66.7%
Common 101
33.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
김 19
 
9.4%
이 18
 
8.9%
정 10
 
5.0%
박 7
 
3.5%
최 7
 
3.5%
현 6
 
3.0%
영 6
 
3.0%
환 5
 
2.5%
수 4
 
2.0%
하 4
 
2.0%
Other values (70) 116
57.4%
Common
ValueCountFrequency (%)
* 101
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 202
66.7%
ASCII 101
33.3%

Most frequent character per block

ASCII
ValueCountFrequency (%)
* 101
100.0%
Hangul
ValueCountFrequency (%)
김 19
 
9.4%
이 18
 
8.9%
정 10
 
5.0%
박 7
 
3.5%
최 7
 
3.5%
현 6
 
3.0%
영 6
 
3.0%
환 5
 
2.5%
수 4
 
2.0%
하 4
 
2.0%
Other values (70) 116
57.4%

국문보고서명
Text

UNIQUE 

Distinct101
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size936.0 B
2024-04-21T19:16:22.729352image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length86
Median length48
Mean length33.940594
Min length9

Characters and Unicode

Total characters3428
Distinct characters386
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

Unique101 ?
Unique (%)100.0%

Sample

1st row내생미생물을 이용한 산양삼 병원균 친환경 방제 기술 개발
2nd row산초유 효능 구명 및 산업화 기술개발
3rd row고산지역 내한성 차나무 육성을 통한 재배기술 개발
4th row흡음·난연·내진성 건축 목재-무기질 복합재 제조기술개발
5th row잣나무구과의 기능성 개별인정 연구 및 산업화
ValueCountFrequency (%)
개발 57
 
6.9%
및 48
 
5.8%
이용한 20
 
2.4%
위한 19
 
2.3%
연구 18
 
2.2%
활용한 11
 
1.3%
소재 11
 
1.3%
기능성 10
 
1.2%
기술 9
 
1.1%
산업화 8
 
1.0%
Other values (510) 620
74.6%
2024-04-21T19:16:24.024825image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
737
 
21.5%
개 83
 
2.4%
발 78
 
2.3%
산 73
 
2.1%
기 67
 
2.0%
한 67
 
2.0%
용 48
 
1.4%
및 48
 
1.4%
구 42
 
1.2%
을 42
 
1.2%
Other values (376) 2143
62.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 2549
74.4%
Space Separator 737
 
21.5%
Uppercase Letter 60
 
1.8%
Lowercase Letter 44
 
1.3%
Other Punctuation 15
 
0.4%
Open Punctuation 9
 
0.3%
Close Punctuation 9
 
0.3%
Decimal Number 3
 
0.1%
Dash Punctuation 2
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
개 83
 
3.3%
발 78
 
3.1%
산 73
 
2.9%
기 67
 
2.6%
한 67
 
2.6%
용 48
 
1.9%
및 48
 
1.9%
구 42
 
1.6%
을 42
 
1.6%
이 40
 
1.6%
Other values (337) 1961
76.9%
Uppercase Letter
ValueCountFrequency (%)
T 12
20.0%
I 10
16.7%
C 8
13.3%
D 7
11.7%
A 4
 
6.7%
F 3
 
5.0%
N 3
 
5.0%
L 3
 
5.0%
M 3
 
5.0%
E 2
 
3.3%
Other values (4) 5
8.3%
Lowercase Letter
ValueCountFrequency (%)
e 8
18.2%
r 7
15.9%
i 5
11.4%
o 5
11.4%
c 4
9.1%
t 3
 
6.8%
a 2
 
4.5%
n 2
 
4.5%
d 2
 
4.5%
m 2
 
4.5%
Other values (4) 4
9.1%
Other Punctuation
ValueCountFrequency (%)
· 9
60.0%
, 5
33.3%
/ 1
 
6.7%
Open Punctuation
ValueCountFrequency (%)
( 8
88.9%
[ 1
 
11.1%
Close Punctuation
ValueCountFrequency (%)
) 8
88.9%
] 1
 
11.1%
Decimal Number
ValueCountFrequency (%)
3 2
66.7%
4 1
33.3%
Space Separator
ValueCountFrequency (%)
737
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 2549
74.4%
Common 775
 
22.6%
Latin 104
 
3.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
개 83
 
3.3%
발 78
 
3.1%
산 73
 
2.9%
기 67
 
2.6%
한 67
 
2.6%
용 48
 
1.9%
및 48
 
1.9%
구 42
 
1.6%
을 42
 
1.6%
이 40
 
1.6%
Other values (337) 1961
76.9%
Latin
ValueCountFrequency (%)
T 12
 
11.5%
I 10
 
9.6%
e 8
 
7.7%
C 8
 
7.7%
r 7
 
6.7%
D 7
 
6.7%
i 5
 
4.8%
o 5
 
4.8%
A 4
 
3.8%
c 4
 
3.8%
Other values (18) 34
32.7%
Common
ValueCountFrequency (%)
737
95.1%
· 9
 
1.2%
( 8
 
1.0%
) 8
 
1.0%
, 5
 
0.6%
- 2
 
0.3%
3 2
 
0.3%
] 1
 
0.1%
[ 1
 
0.1%
/ 1
 
0.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 2547
74.3%
ASCII 870
 
25.4%
None 9
 
0.3%
Compat Jamo 2
 
0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
737
84.7%
T 12
 
1.4%
I 10
 
1.1%
e 8
 
0.9%
( 8
 
0.9%
C 8
 
0.9%
) 8
 
0.9%
r 7
 
0.8%
D 7
 
0.8%
i 5
 
0.6%
Other values (28) 60
 
6.9%
Hangul
ValueCountFrequency (%)
개 83
 
3.3%
발 78
 
3.1%
산 73
 
2.9%
기 67
 
2.6%
한 67
 
2.6%
용 48
 
1.9%
및 48
 
1.9%
구 42
 
1.6%
을 42
 
1.6%
이 40
 
1.6%
Other values (336) 1959
76.9%
None
ValueCountFrequency (%)
· 9
100.0%
Compat Jamo
ValueCountFrequency (%)
ㆍ 2
100.0%

국문색인어
Text

MISSING 

Distinct22
Distinct (%)100.0%
Missing79
Missing (%)78.2%
Memory size936.0 B
2024-04-21T19:16:25.162351image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length57
Median length36
Mean length33.636364
Min length23

Characters and Unicode

Total characters740
Distinct characters212
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

Unique22 ?
Unique (%)100.0%

Sample

1st row매실나무, 매실, 고혈압, 혈관질환, 혈관이완
2nd row자귀나무, 퇴행성관절염, 연골, 연골세포, 기능성 식품
3rd row기능성 미생물, 용균효소, 미국흰불나방, 친환경 방제, 환경보호
4th row수종별 치유인자, 산림시업 개발, 산림치유 보험화, 산림치유 의학적 효능, 산림건강증진 연계 정책
5th row생물권보전지역, 산림보호지역, 산림생물자원, 인문자원, 산림복원
ValueCountFrequency (%)
산림 3
 
2.1%
기능성 3
 
2.1%
필름 3
 
2.1%
개발 2
 
1.4%
리그닌 2
 
1.4%
수은 2
 
1.4%
개질 2
 
1.4%
헤미셀룰로오스 2
 
1.4%
측정 2
 
1.4%
산림치유 2
 
1.4%
Other values (120) 120
83.9%
2024-04-21T19:16:26.536944image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
122
 
16.5%
, 86
 
11.6%
산 25
 
3.4%
림 19
 
2.6%
생 11
 
1.5%
화 11
 
1.5%
물 10
 
1.4%
자 9
 
1.2%
스 9
 
1.2%
수 8
 
1.1%
Other values (202) 430
58.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 520
70.3%
Space Separator 122
 
16.5%
Other Punctuation 86
 
11.6%
Lowercase Letter 6
 
0.8%
Uppercase Letter 5
 
0.7%
Dash Punctuation 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
산 25
 
4.8%
림 19
 
3.7%
생 11
 
2.1%
화 11
 
2.1%
물 10
 
1.9%
자 9
 
1.7%
스 9
 
1.7%
수 8
 
1.5%
지 8
 
1.5%
유 8
 
1.5%
Other values (188) 402
77.3%
Lowercase Letter
ValueCountFrequency (%)
e 1
16.7%
s 1
16.7%
a 1
16.7%
n 1
16.7%
i 1
16.7%
k 1
16.7%
Uppercase Letter
ValueCountFrequency (%)
M 1
20.0%
P 1
20.0%
A 1
20.0%
T 1
20.0%
I 1
20.0%
Space Separator
ValueCountFrequency (%)
122
100.0%
Other Punctuation
ValueCountFrequency (%)
, 86
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 520
70.3%
Common 209
28.2%
Latin 11
 
1.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
산 25
 
4.8%
림 19
 
3.7%
생 11
 
2.1%
화 11
 
2.1%
물 10
 
1.9%
자 9
 
1.7%
스 9
 
1.7%
수 8
 
1.5%
지 8
 
1.5%
유 8
 
1.5%
Other values (188) 402
77.3%
Latin
ValueCountFrequency (%)
M 1
9.1%
e 1
9.1%
s 1
9.1%
a 1
9.1%
n 1
9.1%
i 1
9.1%
k 1
9.1%
P 1
9.1%
A 1
9.1%
T 1
9.1%
Common
ValueCountFrequency (%)
122
58.4%
, 86
41.1%
- 1
 
0.5%

Most occurring blocks

ValueCountFrequency (%)
Hangul 520
70.3%
ASCII 220
29.7%

Most frequent character per block

ASCII
ValueCountFrequency (%)
122
55.5%
, 86
39.1%
- 1
 
0.5%
M 1
 
0.5%
e 1
 
0.5%
s 1
 
0.5%
a 1
 
0.5%
n 1
 
0.5%
i 1
 
0.5%
k 1
 
0.5%
Other values (4) 4
 
1.8%
Hangul
ValueCountFrequency (%)
산 25
 
4.8%
림 19
 
3.7%
생 11
 
2.1%
화 11
 
2.1%
물 10
 
1.9%
자 9
 
1.7%
스 9
 
1.7%
수 8
 
1.5%
지 8
 
1.5%
유 8
 
1.5%
Other values (188) 402
77.3%

영문색인어
Text

MISSING 

Distinct21
Distinct (%)100.0%
Missing80
Missing (%)79.2%
Memory size936.0 B
2024-04-21T19:16:27.339185image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length136
Median length87
Mean length90.571429
Min length60

Characters and Unicode

Total characters1902
Distinct characters47
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique21 ?
Unique (%)100.0%

Sample

1st rowPrunus mume, korean plum, hypertension, vasorelaxant effect, cardiovascular disease
2nd rowAlbizia julibrissin, Osteoarthritis, Articular cartilage, Chondrocyte, Functional food
3rd rowPLS, Hyphantria cunea, microorganism, eco-friendly, bio-pesticide
4th rowTherapeutic Attributes by Species, Forest Working Plan, Insurance Policy, Clinical Effectiveness, Forest Therapy Health Promotion Policy
5th rowMAB, Forest reserve area, Forest bioresources, Humanity resources, Forest restoration
ValueCountFrequency (%)
forest 18
 
8.8%
wood 3
 
1.5%
film 3
 
1.5%
modification 3
 
1.5%
resource 2
 
1.0%
development 2
 
1.0%
species 2
 
1.0%
policy 2
 
1.0%
hemicellulose 2
 
1.0%
factor 2
 
1.0%
Other values (158) 165
80.9%
2024-04-21T19:16:28.408270image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
189
 
9.9%
e 176
 
9.3%
o 147
 
7.7%
i 144
 
7.6%
t 128
 
6.7%
r 114
 
6.0%
n 108
 
5.7%
s 98
 
5.2%
a 98
 
5.2%
, 83
 
4.4%
Other values (37) 617
32.4%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 1510
79.4%
Space Separator 189
 
9.9%
Uppercase Letter 109
 
5.7%
Other Punctuation 83
 
4.4%
Dash Punctuation 11
 
0.6%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e 176
11.7%
o 147
9.7%
i 144
9.5%
t 128
 
8.5%
r 114
 
7.5%
n 108
 
7.2%
s 98
 
6.5%
a 98
 
6.5%
c 77
 
5.1%
l 76
 
5.0%
Other values (15) 344
22.8%
Uppercase Letter
ValueCountFrequency (%)
F 13
11.9%
P 11
 
10.1%
A 9
 
8.3%
D 8
 
7.3%
T 7
 
6.4%
E 7
 
6.4%
C 7
 
6.4%
L 6
 
5.5%
S 6
 
5.5%
H 6
 
5.5%
Other values (9) 29
26.6%
Space Separator
ValueCountFrequency (%)
189
100.0%
Other Punctuation
ValueCountFrequency (%)
, 83
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 11
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 1619
85.1%
Common 283
 
14.9%

Most frequent character per script

Latin
ValueCountFrequency (%)
e 176
 
10.9%
o 147
 
9.1%
i 144
 
8.9%
t 128
 
7.9%
r 114
 
7.0%
n 108
 
6.7%
s 98
 
6.1%
a 98
 
6.1%
c 77
 
4.8%
l 76
 
4.7%
Other values (34) 453
28.0%
Common
ValueCountFrequency (%)
189
66.8%
, 83
29.3%
- 11
 
3.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1902
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
189
 
9.9%
e 176
 
9.3%
o 147
 
7.7%
i 144
 
7.6%
t 128
 
6.7%
r 114
 
6.0%
n 108
 
5.7%
s 98
 
5.2%
a 98
 
5.2%
, 83
 
4.4%
Other values (37) 617
32.4%

보안여부
Boolean

IMBALANCE 

Distinct2
Distinct (%)2.0%
Missing0
Missing (%)0.0%
Memory size229.0 B
True
96 
False
 
5
ValueCountFrequency (%)
True 96
95.0%
False 5
 
5.0%
2024-04-21T19:16:28.599967image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-04-21T19:16:28.709980image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
제출일발행일연구책임자명국문색인어영문색인어보안여부
제출일1.0000.9970.9681.0001.0000.000
발행일0.9971.0000.9751.0001.0000.000
연구책임자명0.9680.9751.0001.0001.0000.423
국문색인어1.0001.0001.0001.0001.0001.000
영문색인어1.0001.0001.0001.0001.0001.000
보안여부0.0000.0000.4231.0001.0001.000

Missing values

2024-04-21T19:16:14.630658image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-04-21T19:16:15.039754image/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.
2024-04-21T19:16:15.336915image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
The correlation heatmap measures nullity correlation: how strongly the presence or absence of one variable affects the presence of another.

Sample

과제번호제출일발행일연구책임자명국문보고서명국문색인어영문색인어보안여부
0PJ0000882017-07-042017-07-14배*홍내생미생물을 이용한 산양삼 병원균 친환경 방제 기술 개발<NA><NA>Y
1PJ0001012021-04-012021-04-01유*열산초유 효능 구명 및 산업화 기술개발<NA><NA>Y
2PJ0001212021-03-312021-03-31송*선고산지역 내한성 차나무 육성을 통한 재배기술 개발<NA><NA>Y
3PJ0001162021-03-312021-03-31박*준흡음·난연·내진성 건축 목재-무기질 복합재 제조기술개발<NA><NA>Y
4PJ0000102021-04-012021-04-01김*용잣나무구과의 기능성 개별인정 연구 및 산업화<NA><NA>Y
5PJ0002452021-04-222021-04-22정*헌시호 추출물을 활용한 DNA 상해 저감형 소재 개발<NA><NA>Y
6PJ0002372021-04-232021-04-23박*민캄보디아 경제수종의 생장 우수 가계 선발 및 GBS를 활용한 유전변이 연구<NA><NA>Y
7PJ0002502021-04-232021-04-23조*민매실나무를 이용한 혈관 기능 개선 기능성 소재 개발연구매실나무, 매실, 고혈압, 혈관질환, 혈관이완Prunus mume, korean plum, hypertension, vasorelaxant effect, cardiovascular diseaseY
8PJ0002392021-04-232021-04-23김*현자귀나무 추출물의 관절보호효능 기반 관절건강 기능성 원료소재 효용성 분석자귀나무, 퇴행성관절염, 연골, 연골세포, 기능성 식품Albizia julibrissin, Osteoarthritis, Articular cartilage, Chondrocyte, Functional foodY
9PJ0002572021-04-232021-04-23문*현기능성 미생물을 이용한 미국흰불나방 친환경 방제 기술 개발기능성 미생물, 용균효소, 미국흰불나방, 친환경 방제, 환경보호PLS, Hyphantria cunea, microorganism, eco-friendly, bio-pesticideY
과제번호제출일발행일연구책임자명국문보고서명국문색인어영문색인어보안여부
91PJ0000092021-04-012021-04-01여*명목재수종 실시간 분석을 위한 근적외선 분광분석 기술개발 및 기계화 연구<NA><NA>Y
92PJ0000082021-04-012021-04-01김*훈보급형 온열욕 겸용 숯가마 개발 및 치유효능 연구<NA><NA>Y
93PJ0000162021-04-012021-04-01이*명산국에센셜오일을 활용한 아토피피부염 개선 소재 및 화장품 개발<NA><NA>Y
94PJ0000122021-04-012021-04-01이*석산림곤충을 이용한 정서곤충자원 대량사육기술 개발 및 산업화<NA><NA>Y
95PJ0000032021-04-012021-04-01이*우산림치유시설에 적용가능한 감성과학 관점의 산림치유 이모션맵 개발 및 활용<NA><NA>Y
96PJ0000042021-04-012021-04-01최*환산림치유와 정보통신(ICT)의 융복합을 통한 맞춤형 건강관리 플랫폼 개발 및 상용화<NA><NA>Y
97PJ0000072021-04-012021-04-01조*길실용정원 확산을 위한 정원조성 기술개발 및 산업화 연구<NA><NA>Y
98PJ0000182021-04-012021-04-01정*경은행나무열매(가로수) 악취문제 해결을 위한 신기술 개발 및 산업화<NA><NA>Y
99PJ0000142021-04-012021-04-01정*철황칠나무 유래 기능성물질의 대량생산기술개발 및 산업화<NA><NA>Y
100PJ0000172021-04-012021-04-01예*수떫은감을 이용한 고부가 소재 및 제품 개발<NA><NA>Y