• Title/Summary/Keyword: classification activity

Search Result 724, Processing Time 0.025 seconds

Free Play Activities in the Curricula of Childcare Centers and Teachers' Perceptions of Play (보육과정에서의 자유놀이 현황과 교사의 놀이인식)

  • Rim, Hyo-Shin;Rha, Jong-Hay
    • Journal of the Korean Home Economics Association
    • /
    • v.49 no.2
    • /
    • pp.27-36
    • /
    • 2011
  • This study dealt with free play activities in the curricula of childcare centers in Daejeon area. 29 teachers from 21 day care centers were interviewed individually to obtain an understanding of teachers perceptions and conflicting views about play activity in the context of different day care curricula. The data were analysed qualitatively, using categorization and key word classification, frequency analyses and chi-squared tests. The results were as follows: (1) play-oriented curricula included sufficient play time and planned play activities in terms of the children's development. Children's freedom in play, optimum intercession by teachers, and interrelating activities between activity areas were included. In mixed curricula, children's freedoms were limited in many cases, and interrelating play between activity areas was hardly found. Formal lesson-oriented curricula resulted unplanned play activities and teachers' passive intercession of play. (2) Most teachers believed that play activities were more important to a child's development than formal lessons.

Molecular Vibration-Activity Relationship in the Agonism of Adenosine Receptors

  • Chee, Hyun Keun;Oh, S. June
    • Genomics & Informatics
    • /
    • v.11 no.4
    • /
    • pp.282-288
    • /
    • 2013
  • The molecular vibration-activity relationship in the receptor-ligand interaction of adenosine receptors was investigated by structure similarity, molecular vibration, and hierarchical clustering in a dataset of 46 ligands of adenosine receptors. The resulting dendrogram was compared with those of another kind of fingerprint or descriptor. The dendrogram result produced by corralled intensity of molecular vibrational frequency outperformed four other analyses in the current study of adenosine receptor agonism and antagonism. The tree that was produced by clustering analysis of molecular vibration patterns showed its potential for the functional classification of adenosine receptor ligands.

Frequent Pattern Bayesian Classification for ECG Pattern Diagnosis (심전도 패턴 판별을 위한 빈발 패턴 베이지안 분류)

  • Noh, Gi-Yeong;Kim, Wuon-Shik;Lee, Hun-Gyu;Lee, Sang-Tae;Ryu, Keun-Ho
    • The KIPS Transactions:PartD
    • /
    • v.11D no.5
    • /
    • pp.1031-1040
    • /
    • 2004
  • Electrocardiogram being the recording of the heart's electrical activity provides valuable clinical information about heart's status. Many re-searches have been pursued for heart disease diagnosis using ECG so far. However, electrocardio-graph uses foreign diagnosis algorithm due to inaccuracy of diagnosis results for a heart disease. This paper suggests ECG data collection, data preprocessing and heart disease pattern classification using data mining. This classification technique is the FB(Frequent pattern Bayesian) classifier and is a combination of two data mining problems, naive bayesian and frequent pattern mining. FB uses Product Approximation construction that uses the discovered frequent patterns. Therefore, this method overcomes weakness of naive bayesian which makes the assumption of class conditional independence.

Research on Malware Classification with Network Activity for Classification and Attack Prediction of Attack Groups (공격그룹 분류 및 예측을 위한 네트워크 행위기반 악성코드 분류에 관한 연구)

  • Lim, Hyo-young;Kim, Wan-ju;Noh, Hong-jun;Lim, Jae-sung
    • The Journal of Korean Institute of Communications and Information Sciences
    • /
    • v.42 no.1
    • /
    • pp.193-204
    • /
    • 2017
  • The security of Internet systems critically depends on the capability to keep anti-virus (AV) software up-to-date and maintain high detection accuracy against new malware. However, malware variants evolve so quickly they cannot be detected by conventional signature-based detection. In this paper, we proposed a malware classification method based on sequence patterns generated from the network flow of malware samples. We evaluated our method with 766 malware samples and obtained a classification accuracy of approximately 40.4%. In this study, malicious codes were classified only by network behavior of malicious codes, excluding codes and other characteristics. Therefore, this study is expected to be further developed in the future. Also, we can predict the attack groups and additional attacks can be prevented.

A Study on Identifying Nursing Activities and Standard Nursing Practice Time for Developing a Neonatal Patient Classification System in Neonatal Intensive Care Unit (신생아중환자 분류도구 개발을 위한 간호활동 규명 및 표준간호시간 조사연구)

  • Ko, Bum Ja;Yu, Mi;Kang, Jin Sun;Kim, Dong Yeon;Bog, Jeong Hee;Jang, Eun Kyung;Park, Sun Ja;Oh, Sun Ja;Choi, Yun Jin
    • Journal of Korean Clinical Nursing Research
    • /
    • v.18 no.2
    • /
    • pp.251-263
    • /
    • 2012
  • Purpose: It was necessary for developing a neonatal classification system based on nursing needs and direct care time. This study was, thus, aimed at identifying nursing activities and measuring the standard nursing practice time for developing a neonatal patient classification system in Neonatal Intensive Care Unit (NICU). Methods: The study was taken place in 8 general hospitals located in Seoul and Kyungi province, South Korea from Dec, 2009 to Jan, 2010. By using 'the modified Workload Management System for critical care Nurses' (WMSN), nursing categories, activities, standard time, and task frequencies were measured with direct observation. The data were analyzed by using descriptive statistics. Results: Neonatal nursing activities were categorized into 8 areas: vital signs (manual), monitoring, activity of daily living (ADL), feeding, medication, treatment and procedure, respiratory therapy, and education-emotional support. The most frequent and time-consuming area was an ADL, unlike that of adult patients. Conclusion: The findings of the study provide a foundation for developing a neonatal patient classification system in NICU. Further research is warranted to verify the reliability and validity of the instrument.

What Characteristics Do Preservice Teachers Show During Trilobite Classification Activities? (예비교사들은 삼엽충 분류활동 중에 어떤 특성을 보이는가?)

  • Lim, Sungman
    • Journal of the Korean Society of Earth Science Education
    • /
    • v.12 no.1
    • /
    • pp.40-53
    • /
    • 2019
  • This study was to analyze the inquiry characteristics of preservice teachers as they classify trilobites. For the study, 70 preservice teachers attending teacher training university participated. The classification tasks used in the study were 9 photos of trilobite fossils. The preservice teachers' inquiry activity was to classify the evolutionary processes of trilobites after observing trilobite fossils by group and then to construct a phylogenetic tree. The results of the study are as follows. First, preservice teachers observed the external features of the trilobites and constructed systematic classification results based on their observed contents. Second, preservice teachers classified trilobites using various classification criteria. Third, the phylogenetic tree of preservice teachers and the phylogenetic tree of scientists were very similar. The preservice teachers constructed a sphylogenetic tree based on the observation and inference of the change from a simple form to a complex form, which is a general evolution process of the trilobite fossil claimed by scientists. These results suggest that group-based inquiry activities with sufficient time are very effective and that the experience of inquiry activities is very important for preservice teachers.

A Genetic Algorithm-based Classifier Ensemble Optimization for Activity Recognition in Smart Homes

  • Fatima, Iram;Fahim, Muhammad;Lee, Young-Koo;Lee, Sungyoung
    • KSII Transactions on Internet and Information Systems (TIIS)
    • /
    • v.7 no.11
    • /
    • pp.2853-2873
    • /
    • 2013
  • Over the last few years, one of the most common purposes of smart homes is to provide human centric services in the domain of u-healthcare by analyzing inhabitants' daily living. Currently, the major challenges in activity recognition include the reliability of prediction of each classifier as they differ according to smart homes characteristics. Smart homes indicate variation in terms of performed activities, deployed sensors, environment settings, and inhabitants' characteristics. It is not possible that one classifier always performs better than all the other classifiers for every possible situation. This observation has motivated towards combining multiple classifiers to take advantage of their complementary performance for high accuracy. Therefore, in this paper, a method for activity recognition is proposed by optimizing the output of multiple classifiers with Genetic Algorithm (GA). Our proposed method combines the measurement level output of different classifiers for each activity class to make up the ensemble. For the evaluation of the proposed method, experiments are performed on three real datasets from CASAS smart home. The results show that our method systematically outperforms single classifier and traditional multiclass models. The significant improvement is achieved from 0.82 to 0.90 in the F-measures of recognized activities as compare to existing methods.

Isolation and Characterization of an Anti-listerial Bacteriocin from Leuconostoc lactis SD501

  • Hwang, In-Chan;Oh, Ju Kyoung;Kim, Sang Hoon;Oh, Sejong;Kang, Dae-Kyung
    • Food Science of Animal Resources
    • /
    • v.38 no.5
    • /
    • pp.1008-1018
    • /
    • 2018
  • Although bacteriocins with anti-listerial activity have been isolated from a wide variety of lactic acid bacteria, little is known about those from Leuconostoc lactis, a heterofermentative bacterium that produces diacetyl and exopolysaccharides in dairy foods. In this study, an anti-listerial bacteriocin was isolated from Leuc. lactis SD501 and characterized. It was particularly potent against Listeria monocytogenes and also inhibited Enterococcus faecalis. Anti-listerial activity reached a maximum during the early stationary phase and then decreased gradually. The anti-listerial substance was sensitive to proteinase K and ${\alpha}$-chymotrypsin, confirming its proteinaceous nature. Its activity remained stable at pH values ranging from 1 to 10. In addition, it was strongly resistant to high temperatures, retaining its activity even after incubation for 15 min at $121^{\circ}C$. The apparent molecular mass of the partially purified anti-listerial bacteriocin was approximately 7 kDa. The characteristics of the SD501 bacteriocin, including its small molecular size (<10 kDa), strong anti-listerial activity, wide pH stability and good thermostability, indicate its classification as a Class IIa bacteriocin.

Classification of Daily Routine Types in Child Care Center and Teacher Behaviors Based on Daily Routine Types (어린이집 유아반의 일과 유형분류 및 일과 유형별 교사행동에 관한 연구)

  • Kwon, Yeon Hee;Choi, Mock Wha;Park, Chan Hwa
    • Korean Journal of Human Ecology
    • /
    • v.21 no.5
    • /
    • pp.837-848
    • /
    • 2012
  • This study evaluated the types of daily routines that occurred in child care centers based on four general categorizations: time spent on indoor free choice activities, outdoor activities, group activities and special activities. In addition, resulting child care teacher behaviors were examined based on daily routine types. A total 23 classes' activity times and teacher behaviors were observed. The collected data were analyzed using descriptive statistics, hierarchical cluster, and Mann-Whitney U. Results indicated that there were 2 principle daily routine, 'indoor/outdoor activity time oriented' and 'group activity time oriented'. Analysis showed that teachers who belonged to the 'indoor/outdoor activity time oriented' type showed more positive affect, positive guidance, neural guidance, and less non-involved behavior. Results suggest the importance of time spent on free choice activities in the context of daily routine for quality childcare.

Development of the Activity Posture Classifier for Ubiquitous Health Care (유비쿼터스 헬스케어를 위한 활동상태 분류기 개발)

  • Kim, Se-Jin;Chung, Wan-Young;Jeong, Do-Un
    • Proceedings of the Korean Institute of Information and Commucation Sciences Conference
    • /
    • 2007.06a
    • /
    • pp.703-706
    • /
    • 2007
  • The real-time monitoring about the activity of the human provides useful information about the activity quantity and an ability. This study developed a system for human physical activity assessment in ambulatory monitoring using portable sensing device combining a tri-axial accelerometer and wireless sensor node. This real-time system is able to identify several postures, posture transitions and movements with classification algorithm. In addition, this system also features fall detection capability. The results of the assessment for evaluating the performance of the system show high identification accuracy.

  • PDF