• Title/Summary/Keyword: profiling analysis

Search Result 742, Processing Time 0.028 seconds

Impurity Profiling Analysis of Illicit Methamphetamine Seized in Korea (우리나라에서 불법 유통되는 메스암페타민의 불순물 프로화일 분석)

  • Yoo, Young-Chan;Chung, Hee-Sun;Kim, Eun-Mi;Kim, Sun-Cheun;Kim, Seung-Whan
    • YAKHAK HOEJI
    • /
    • v.42 no.6
    • /
    • pp.627-633
    • /
    • 1998
  • Impurity profiling analysis of methamphetamine seized in Korea was investigated for the evidential and intelligent purpose. Samples were extracted with ethylacetate which contai ns internal standard of dioctylsebacate under basic condition and extracts were analyzed by GC-FID. Ephedrine, chloroephedrine & 1,2-dimethyl-3-phenylaziridine were identified impurities in illicit methamphetamine by GC-MS. These impurities revealed that most of abused methamphetamine in Korea were synthesized from ephedrine as a starting material. For the classification of samples. firstly, 24 impurity peaks were selected after inspection of every peak in 50 samples as the specific markers of impurities. Secondly, corresponding peak retention time and area ratio to the internal standard were calculated and database was created with values of 24 peaks by in-house program. Finally, cluster analysis was attempted with the resultant profiles using the STAR plot, which was based on the Euclidian distance for evaluating similarity among samples. A total of 76 samples were divided into 8 different groups within 90% statistical similarity and inter-batch samples showed similar impurity patterns by this procedure. In conclusion, the analysis of impurities is a suitable index for estimation the common or different origin of methamphetamine sample.

  • PDF

Static and Dynamic Analysis of Efficiency of Korean Regional Public Hospitals (지방의료원의 효율성에 대한 정태적 및 동태적 분석)

  • Kim, Jong-Ki;Jeon, Jinh-Wan
    • Korea Journal of Hospital Management
    • /
    • v.15 no.1
    • /
    • pp.27-48
    • /
    • 2010
  • The purpose of this paper is to analyze the efficiency change and its determinants of the regional public hospitals. We utilize 34 regional public hospital's panel data for 6 years from 2003 to 2008. We use DEA(Data Envelopment Analysis)-CCR, BCC model, DEA/Window model, and DEA Profiling. The empirical results show the following findings. First, technical efficiency shows that approximately 3.6% of inefficiency exists on the regional public hospitals and it reveals that the cause for technical inefficiency is due to scale inefficiency. Second, DEA/Window results show that the stable dissimilarity by standard deviation, LDP of CCR. Third, the results of partial efficiency by DEA Profiling show that increase efficiency depends on the number of beds, doctors, and nurses.

  • PDF

Profiling and Co-word Analysis of Teaching Korean as a Foreign Language Domain (프로파일링 분석과 동시출현단어 분석을 이용한 한국어교육학의 정체성 분석)

  • Kang, Beomil;Park, Ji-Hong
    • Journal of the Korean Society for information Management
    • /
    • v.30 no.4
    • /
    • pp.195-213
    • /
    • 2013
  • This study aims at establishing the identity of teaching Korean as a Foreign Language (KFL) domain by using journal profiling and co-word analysis in comparison with the relevant and adjacent domains. Firstly, by extracting and comparing topic terms, we calculate the similarity of academic journals of the three domains, KFL, teaching Korean as a Native Language (KNL), and Korean Linguistics (KL). The result shows that the journals of KFL form a distinct cluster from the others. The profiling analysis and co-word analysis are then conducted to visualize the relationship among all the three domains in order to uncover the characteristics of KFL. The findings show that KFL is more similar to KNL than to KL. Finally, the comparison of knowledge structures of these three domains based on the co-word analysis demonstrates the uniqueness of KFL as an independent domain in relation with the other relevant domains.

Domain Analysis of Reading Research in Korea using Author Profiling (저자 프로파일링 기법을 이용한 국내 독서 연구 영역 분석)

  • Kim, Pan-Jun
    • Journal of the Korean BIBLIA Society for library and Information Science
    • /
    • v.22 no.4
    • /
    • pp.21-44
    • /
    • 2011
  • This study aims to analyze research domains and trends of reading education in Korea and, suggest future research direction of this field. First, In order to identify the overview of research in terms of productivity, A basic analysis was performed based on 1,465 articles of domestic serials(1935~2011). Second, The analysis of intellectual structure using author profiling as a technique of text mining was performed based on 652 papers of domestic journals(2000~2011). Third, Depending on the results of these analysis, this study suggested the directions of future research of the field.

Designing SMS Phishing Profiling Model (스미싱 범죄 프로파일링 모델 설계)

  • Jeong, Youngho;Lee, Kukheon;Lee, Sangjin
    • Journal of the Korea Institute of Information Security & Cryptology
    • /
    • v.25 no.2
    • /
    • pp.293-302
    • /
    • 2015
  • With the attack information collected during SMS phishing investigation, this paper will propose SMS phishing profiling model applying criminal profiling. Law enforcement agencies have used signature analysis by apk file hash and analysis of C&C IP address inserted in the malware. However, recently law enforcement agencies are facing the challenges such as signature diversification or code obfuscation. In order to overcome these problems, this paper examined 169 criminal cases and found out that 89% of serial number in cert.rsa and 80% of permission file was reused in different cases. Therefore, the proposed SMS phishing profiling model is mainly based on signature serial number and permission file hash. In addition, this model complements the conventional file hash clustering method and uses code similarity verification to ensure reliability.

Advances in Plant Metabolomics (식물 대사체 연구의 진보)

  • Kim, Suk-Won;Chung, Hoe-Il;Liu, Jang-R.
    • Journal of Plant Biotechnology
    • /
    • v.33 no.3
    • /
    • pp.161-169
    • /
    • 2006
  • Plant metabolomics is a plant biology field for identifying all of the metabolites found in a certain plant cell, tissue, organ, or whole plant in a given time and conditions and for studying changes in metabolic profiling as time goes or conditions change. Metabolomics is one of the most recently developed omics for holistic approach to biology and is a kind of systems biology. For holistic approach, metabolomics frequently uses chemometrics or multivariate statistical analysis of metabolic profillings. In plant biology, metabolomics is useful to determine functions of genes often in combination with DHA microarrays by analyzing tagged mutants of the model plants Arabidopsis and rice. This review paper attempted to introduce basic concepts of metabolomics and practical uses of multivariate statistical analysis of metabolic profiling obtained by $^1$H HMR and Fourier transform infrared spectrometry.

Deep Learning Based User Safety Profiling Using User Feature Information Modeling (딥러닝 기반 사용자 특징 정보 모델링을 통한 사용자 안전 프로파일링)

  • Kim, Kye-Kyung
    • Journal of Software Assessment and Valuation
    • /
    • v.17 no.2
    • /
    • pp.143-150
    • /
    • 2021
  • There is a need for an artificial intelligent technology that can reduce various types of safety accidents by analyzing the risk factors that cause safety accidents in industrial site. In this paper, user safety profiling methods are proposed that can prevent safety accidents in advance by specifying and modeling user information data related to safety accidents. User information data is classified into normal and abnormal conditions through deep learning based artificial intelligence analysis. As a result of verifying user safety profiling technology using more than 10 types of industrial field data, 93.6% of user safety profiling accuracy was obtained.

Metabolic profiling study of ketoprofen-induced toxicity using 1H NMR spectroscopy coupled with multivariate analysis

  • Jung, Jee-Youn;Hwang, Geum-Sook
    • Journal of the Korean Magnetic Resonance Society
    • /
    • v.15 no.1
    • /
    • pp.54-68
    • /
    • 2011
  • $^1H$ nuclear magnetic resonance (NMR) spectroscopy of biological samples has been proven to be an effective and nondestructive approach to probe drug toxicity within an organism. In this study, ketoprofen toxicity was investigated using $^1H$-NMR spectroscopy coupled with multivariate statistical analysis. Histopathologic test of ketoprofen-induced acute gastrointestinal damage in rats demonstrated a significant dose-dependent effect. Furthermore, principal component analysis (PCA) derived from $^1H$-NMR spectra of urinary samples showed clear separation between the vehicle-treated control and ketoprofen-treated groups. Moreover, PCA derived from endogenous metabolite concentrations through targeted profiling revealed a dose-dependent metabolic shift between the vehicle-treated control, low-dose ketoprofen-treated (10 mg/kg body weight), and high-dose ketoprofen-treated (50 mg/kg) groups coinciding with their gastric damage scores after ketoprofen administration. The resultant metabolic profiles demonstrated that the ketoprofen-induced gastric damage exhibited energy metabolism perturbations that increased urinary levels of citrate, cis-aconitate, succinate, and phosphocreatine. In addition, ketoprofen administration induced an enhancement of xenobiotic activity in fatty oxidation, which caused increase levels of N-isovalerylglycine, adipate, phenylacetylglycine, dimethylamine, betaine, hippurate, 3-indoxylsulfate, N,N-dimethylglycine, trimethyl-N-oxide, and glycine. These findings demonstrate that $^1H$-NMR-based urinary metabolic profiling can be used for noninvasive and rapid way to diagnose adverse drug effects and is suitable for explaining the possible biological pathways perturbed by nonsteroidal anti-inflammatory drug toxicity.

Intellectual Structure and Infrastructure of Informetrics: Domain Analysis from 2001 to 2010 (계량정보학의 지적구조 분석 연구: 2001-2010년 연구영역 분석)

  • Lee, Jae-Yun;Choi, Sang-Hee
    • Journal of the Korean Society for information Management
    • /
    • v.28 no.2
    • /
    • pp.11-36
    • /
    • 2011
  • Since the 1990s, informetrics has grown in popularity among information scientists. Today it is a general discipline that comprises all kinds of metrics, including bibliometrics and scientometrics. To illustrate the dynamic progress of this field, this study aims to identify the structure and infrastructure of the informetrics literature using statistical and profiling methods. Informetrics literature was obtained from the Web of Knowledge for the years 2001-2010. The selected articles contain least one of these keywords: informetrics', bibliometrics', scientometrics', webometrics', and citation analysis.' Noteworthy publication patterns of major countries were identified by a statistical method. Intellectual structure analysis shows major research areas, authors, and journals.

Descriptor Profiling for Research Domain Analysis (연구영역분석을 위한 디스크립터 프로파일링에 관한 연구)

  • Kim, Pan-Jun;Lee, Jae-Yun
    • Journal of the Korean Society for information Management
    • /
    • v.24 no.4
    • /
    • pp.285-303
    • /
    • 2007
  • This study aims to explore a new technique making complementary linkage between controlled vocabularies and uncontrolled vocabularies for analyzing a research domain. Co-word analysis can be largely divided into two based on the types of vocabulary used: controlled and uncontrolled. In the case of using controlled vocabulary, data sparseness and indexer effect are inherent drawbacks. On the other case, word selection by the author's perspective and word ambiguity. To complement each other, we suggest a descriptor profiling that represents descriptors(controlled vocabulary) as the co-occurrence with words from the text(uncontrolled vocabulary). Applying the profiling to the domain of information science implies that this method can complement each other by reducing the inherent shortcoming of the controlled and uncontrolled vocabulary.