• KSII Transactions on Internet and Information Systems (TIIS)
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• v.11 no.10
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• pp.5023-5038
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• 2017

Big data is an emerging technology which deals with wide range of data sets with sizes beyond the ability to work with software tools which is commonly used for processing of data. When we consider a huge network, we have to process a large amount of network information generated, which consists of both normal and abnormal activity logs in large volume of multi-dimensional data. Intrusion Detection System (IDS) is required to monitor the network and to detect the malicious nodes and activities in the network. Massive amount of data makes it difficult to detect threats and attacks. Sequential Pattern mining may be used to identify the patterns of malicious activities which have been an emerging popular trend due to the consideration of quantities, profits and time orders of item. Here we propose a sequential pattern mining algorithm with fuzzy logic feature selection and fuzzy weighted support for huge volumes of network logs to be implemented in Apache Hadoop YARN, which solves the problem of speed and time constraints. Fuzzy logic feature selection selects important features from the feature set. Fuzzy weighted supports provide weights to the inputs and avoid multiple scans. In our simulation we use the attack log from NS-2 MANET environment and compare the proposed algorithm with the state-of-the-art sequential Pattern Mining algorithm, SPADE and Support Vector Machine with Hadoop environment.

• Archives of Pharmacal Research
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• v.28 no.6
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• pp.667-674
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• 2005

The leaves of Persimmon (Diospyros kaki L.) has long been used for tea in Korea since it was thought to be effective against hypertension. An anticoagulant fraction was purified through gel filtration G-100, hydrophobic, gel filtration G-150, and FPLC, Phenyl superpose column chromatographies. The purified fraction was homogenous and its Mr was estimated 10,000 Da by gel filtration and SDS-PAGE. The purified fraction was sensitive to treatment of subtilisin B, but not to heat and its activity was not changed after periodate oxidation, indicating that the activity was not due to carbohydrates. It delayed thrombin time (TT), activated partial thromboplastin time (APTT), and prothrombin time (PT) using human plasma. TT was more sensitive than APTT and PT, suggesting that the anticoagulant activity may be caused by a degradation or a defect of fibrin or thrombin. It did not cause the hydrolysis of fibrin after incubation. However, it inhibited thrombin-catalyzed fibrin formation with a competitive inhibition pattern. These results indicate that it may be an antithrombotic agent and that it is bound to fibrinogen binding sites of thrombin.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.14 no.4
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• pp.1543-1561
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• 2020

Taxonomy of human brain activity is a complicated rather challenging procedure. Due to its multifaceted aspects, including experiment design, stimuli selection and presentation of images other than feature extraction and selection techniques, foster its challenging nature. Although, researchers have focused various methods to create taxonomy of human brain activity, however use of multivariate pattern analysis (MVPA) for image recognition to catalog the human brain activities is scarce. Moreover, experiment design is a complex procedure and selection of image type, color and order is challenging too. Thus, this research bridge the gap by using MVPA to create taxonomy of human brain activity for different categories of images, both colored and gray scale. In this regard, experiment is conducted through EEG testing technique, with feature extraction, selection and classification approaches to collect data from prequalified criteria of 25 graduates of University Technology PETRONAS (UTP). These participants are shown both colored and gray scale images to record accuracy and reaction time. The results showed that colored images produces better end result in terms of accuracy and response time using wavelet transform, t-test and support vector machine. This research resulted that MVPA is a better approach for the analysis of EEG data as more useful information can be extracted from the brain using colored images. This research discusses a detail behavior of human brain based on the color and gray scale images for the specific and unique task. This research contributes to further improve the decoding of human brain with increased accuracy. Besides, such experiment settings can be implemented and contribute to other areas of medical, military, business, lie detection and many others.

• Advances in Traditional Medicine
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• v.6 no.3
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• pp.221-231
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• 2006

The aim of the present study is to investigate central nervous system (CNS) activity of the methanol extracts of leaves of Caesalpinia bonducella (MECB) and stem bark of Bauhinia racemosa (MEBR) (Caesalpinaceae) in Swiss albino mice and Wistar albino rats. General behavior, exploratory behavior, muscle relaxant activity and phenobarbitone sodium-induced sleeping time were studied. The results revealed that the methanol extracts of leaves of Caesalpinia bonducella at 100 - 200 mg/kg and stem bark of Bauhinia racemosa 100 - 200 mg/kg caused a significant reduction in the spontaneous activity (general behavioral profile), remarkable decrease in exploratory behavioral pattern (Y-maze and head dip test), a reduction in muscle relaxant activity (rotarod and traction tests), and also significantly potentiated phenobarbitone sodium-induced sleeping time. The results suggest that MECB and MEBR exhibit CNS depressant activity in tested animal models.

• Journal of KIISE:Software and Applications
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• v.41 no.8
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• pp.586-597
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• 2014

The next generation mobile computing technology is recently attracting attention that smartphone and wearable device imbedded with various sensors are being deployed in the world. Existing activity and posture recognition research can be divided into two different ways considering feature of one's movement. While activity recognition focuses on catching distinct pattern according to continuous movement, posture recognition focuses on sudden change of posture and body orientation. There is a lack of research constructing a system mixing two separate patterns which could be applied in real world. In this paper, we propose a method to use both smartphone and wearable device to recognize activity and posture in the same time. To use smartphone and wearable sensor data together, we designed a pre-processing method and constructed recognition model mixing signal vector magnitude and orientation pattern features of vertical and horizontal. We considered cycling, fast/slow walking and running activities, and postures such as standing, sitting, and laying down. We confirmed the performance and validity by experiment, and proved the feasibility in real world.

• Korean Journal of Animal Reproduction
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• v.22 no.3
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• pp.253-264
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• 1998

Porcine follicular oocyte, collected from antral follicles (2~5 mm in diameter) of gilt ovaries were matured in vitro porcine follicular fluid (pFF) with PMSG (pFF-PMSG) buffer with at 37$^{\circ}C$ under 5% CO2 in air their ability of maturation promoting factor (MPF), of GV and GVBD formation was examined followed during time after in vitro culture. Formation of second metaphase was observed in 57.6% and 71.2% of matured in with pFF-PMSG buffer to 45 and 50 hours after invitro. Porcine oocytes cultured in pFF-PMSG for various periods of up to 30 hours were stained with Hoechst-33342 and classified according to maturation before assaying. Histone H1 kinase (H1K) activity was assayed during meiotic maturation in porcine oocytes matured in pFF-PMSG buffer in vitro. In oocytes matured in pFF-PMSG, H1K activity was at the 30 hours after culture and increased about 15 fold than at the germinal vesicle stage with before at the cultured in vitro. This pattern is similar to those reported in non-mammalian species and su, pp.rts the concepts that H1K is ubiquitous in eukaryotes and controls the meiotic cell cycle in mammals. These results suggest that the maturation pFF-PMSG buffer used influences the fluctuation pattern of H1K activity and biological characteristics of porcine oocytes cultured in vitro.

• 한국생물공학회:학술대회논문집
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• 2005.10a
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• pp.827-831
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• 2005

Acupuncture and Low-frequency-wave stimulation at the Points (LI4, LI6, LI8 and LI11) on the large intestine meridian of hand resulted in same pattern about body temperature profiles with time. Upon 4Hz and 50Hz stimulation the temperature profiles on LI6 and LI11 were declined probably because of their relationship with Proprioceptive activity. Temperature different at the points was higher when the intensity of low-frequency-wave stimulation was stronger.

• Journal of Biomedical Engineering Research
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• v.16 no.2
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• pp.201-208
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• 1995

The information obtained from the analysis of respiratory muscle elecromyographic (EMG) activities provides a mean for studying muscular activity in relation to the ventilatory process. Thus, in order to comprehend the airflow pattern and its brain control, signal processing is required to characterize respiratory muscle activity. This paper presents a computerized method for the analysis of the electrical activity of the respiratory muscles of premature lambs, and focuses upon the automatic determination of respiratory timing points such as onset and cessation points of the burst activity. Based on experimental results, reliable timing points can be obtained using the proposed methodology.

• Korean Journal of Community Nutrition
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• v.22 no.6
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• pp.529-542
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• 2017

Objectives: The purpose of this study was to compare the physical activity level (PAL), the physical activity pattern and the energy expenditure in male and female elementary school soccer players using the accelerometer and the physical activity diary. Methods: Twenty-five (male 11, female 14) elementary school soccer players (9-12 years) participated in this study. During their daily activities, they wore an accelerometer for seven days (five weekdays and two weekend days) and completed the physical activity diary for three days (two weekdays and one weekend day). PAL was calculated by using the physical activity diary and three equations (Pate Preschool, Freedson Children, and Freedson) were used to calculate the intensity of physical activity and energy expenditure from the counts of accelerometer. Results: The average of physical activity by day of the week, CPM (Counts Per Minute) and METs (Metabolic Equivalents) were significantly higher in males ($723.3{\pm}149.2CPM$, $2.07{\pm}0.18METs$) compared to females ($505.6{\pm}119.9CPM$, $1.79{\pm}0.20METs$), but there was no significant difference in PAEE (Physical Activity Energy Expenditure) between the two groups (males: $15.5{\pm}9.1kcal/day$, females: $11.5{\pm}6.0kcal/day$). During weekdays, physical activity intensity was significantly higher in males compared to females at lunch time and training time than at other times. In both genders, the PAL was higher during weekdays (males 1.98, females 1.89) compared to weekend (males 1.62, females 1.61) (p<0.05). Conclusions: Our study observations suggest the necessity to develop an accelerometer equation for accurately evaluating the physical activity of elementary school athletes.

• Progress in Medical Physics
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• v.6 no.2
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• pp.103-109
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• 1995

Power spectral analysis of spontaneous heart rate fluctuations were assessed by use of autooic blocking agents and changes in posture. The total power spectral range of interest is divided amongst the various experiments so that each respiratory pattern contributes a spectral ratio of interval to respiration only over a group of frequencies for which the specific respiratory pattern has substantial, and roughly constant, spectral magnitudes. System hardware is consisted ECG preamplifier, respiratory fluctuation detect, interval time generator and IBC 486PC. High frequency fluctuation, at the respiratiory frequency, are decreased by standing and are mediated solely by the parasympathetic system. Power spectral analysis is a powerful nonivsve tool for quantitying autonomic nervous system activity.