• Mass Spectrometry Letters
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• 제14권3호
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• pp.79-90
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• 2023

Natural goods, especially therapeutic plants, are abundant in the World. Because they have the ability to provide all humanity with countless advantages as a source of medicines, medicinal plants are presently receiving more attention than ever. These plants' therapeutic efficacy is based on bioactive phytochemical components that have clear physiological effects on the human body. The drying process is crucial for the preparation of plant materials prior to extraction since freshly harvested plant materials include active enzymes that create active components, intermediates, and metabolic processes. Many of the phytoconstituents may be extracted using the semi-polar solvent methanol. The goal of the current work is to use the GC-MS gas chromatography- mass spectrometry technology to identify the phytochemicals and review their biological activity. In methanol leaf extract, 5 phytocompounds were found in Ricinus communis, 5 phytocompounds in Pongamia pinnata, 12 phytocompounds in Datura metal, 7 phytocompounds in Azadirachta indica, 11 phytocompounds in Acalypha indica.

• Journal of Information Processing Systems
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• 제5권2호
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• pp.77-86
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• 2009

In this paper, we propose a framework for the real-time monitoring of wireless biosensors. This is a scalable platform that requires minimum human interaction during set-up and monitoring. Its main components include a biosensor, a smart gateway to automatically set up the body area network, a mechanism for delivering data to an Internet monitoring server, and automatic data collection, profiling and feature extraction from bio-potentials. Such a system could increase the quality of life and significantly lower healthcare costs for everyone in general, and for the elderly and those with disabilities in particular.

• International Journal of Internet, Broadcasting and Communication
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• 제12권4호
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• pp.83-92
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• 2020

A recent study to determine the fall is focused on analyzing fall motions using a recurrent neural network (RNN), and uses a deep learning approach to get good results for detecting human poses in 2D from a mono color image. In this paper, we investigated the improved detection method to estimate the position of the head and shoulder key points and the acceleration of position change using the skeletal key points information extracted using PoseNet from the image obtained from the 2D RGB low-cost camera, and to increase the accuracy of the fall judgment. In particular, we propose a fall detection method based on the characteristics of post-fall posture in the fall motion analysis method and on the velocity of human body skeleton key points change as well as the ratio change of body bounding box's width and height. The public data set was used to extract human skeletal features and to train deep learning, GRU, and as a result of an experiment to find a feature extraction method that can achieve high classification accuracy, the proposed method showed a 99.8% success rate in detecting falls more effectively than the conventional primitive skeletal data use method.

• 한국멀티미디어학회논문지
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• 제21권12호
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• pp.1473-1480
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• 2018

The extraction and recognition of human motion characteristics need to combine biometrics to determine and judge human behavior in the movement and distinguish individual identities. The so-called biometric technology, the specific operation is the use of the body's inherent biological characteristics of individual identity authentication, the most noteworthy feature is the invariance and uniqueness. In the past, the behavior recognition technology based on the single characteristic was too restrictive, in this paper, we proposed a mixed feature which combined global silhouette feature and local optical flow feature, and this combined representation was used for human action recognition. And we will use the KTH database to train and test the recognition system. Experiments have been very desirable results.

• 한국정보통신학회:학술대회논문집
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• 한국정보통신학회 2022년도 춘계학술대회
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• pp.413-415
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• 2022

인간의 관절은 인간의 신체를 구성하는 요소로 인간의 행동을 분석하는데 유용한 정보로 활용될 수 있기 때문에 관절 정보를 이용한 행동인식에 대한 많은 연구가 진행되었다. 하지만 각각의 독립적인 관절 정보만을 이용해서 시시각각 변화하는 인간의 행동을 인식하는 것은 매우 복잡한 문제이다. 따라서 학습에 사용할 부가적인 정보 추출 방법과 과거의 상태를 기반으로 현재 상태를 판단하는 고려하는 알고리즘이 필요하다. 본 논문에서는 연결된 관절들의 위치 관계와 각 관절의 위치가 시간의 흐름에 따라 변화하는 것을 고려한 행동 인식 기법을 제안한다. 사전 학습된 관절 추출 모델을 이용하여 각 관절의 위치 정보를 획득하고 연결된 관절 사이의 차 벡터를 이용하여 뼈대 정보를 추출한다. 그리고 두 가지 형태의 입력에 맞춰 간소화된 신경망을 구성하고 LSTM을 더하여 시·공간적 특징을 추출하도록 한다. 9개의 행동으로 구성된 데이터 셋을 이용하여 실험한 결과 각 관절 및 뼈대의 시·공간적 관계 특징을 고려하여 행동 인식 정확도를 측정하였을 때 단일 관절 정보만을 이용한 결과에 비해 뛰어난 성능을 보임을 확인하였다.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제11권11호
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• pp.5436-5458
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• 2017

Automatic Video Surveillance System (AVSS) has become important to computer vision researchers as crime has increased in the twenty-first century. As a new branch of AVSS, baggage detection has a wide area of security applications. Some of them are, detecting baggage in baggage restricted super shop, detecting unclaimed baggage in public space etc. However, in this paper, a detection & classification framework of baggage is proposed. Initially, background subtraction is performed instead of sliding window approach to speed up the system and HSI model is used to deal with different illumination conditions. Then, a model is introduced to overcome shadow effect. Then, occlusion of objects is detected using proposed mirroring algorithm to track individual objects. Extraction of rotational signal descriptor (SP-RSD-HOG) with support plane from Region of Interest (ROI) add rotation invariance nature in HOG. Finally, dynamic human body parameter setting approach enables the system to detect & classify single or multiple pieces of carried baggage even if some portions of human are absent. In baggage detection, a strong classifier is generated by boosting similarity measure based multi layer Support Vector Machine (SVM)s into HOG based SVM. This boosting technique has been used to deal with various texture patterns of baggage. Experimental results have discovered the system satisfactorily accurate and faster comparative to other alternatives.

• 한국산업정보학회:학술대회논문집
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• 한국산업정보학회 1999년도 춘계학술대회 발표논문집
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• pp.154-162
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• 1999

This paper introduces the research and development of automatic generation technology to develop the character agent. The R&D of this technology includes three major elements-body model generation, automatic motion generation and synthetic human generation. Main areas of application would be cyber space- 3D game, animation, virtual shopping, on line chatting, virtual education system, simulation and security system.

• 한국감성과학회:학술대회논문집
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• 한국감성과학회 2000년도 추계학술대회 논문집
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• pp.194-198
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• 2000

본 논문은 특별한 마커를 사용하지 않고 연속되는 영상들에서 사람의 2차원 움직임 정보를 추출하는 알고리즘을 제안한다. 사람의 움직임 정보 추출을 위해 색상, 움직임, 윤곽선, 그리고 사용자의 개인적인 특성을 반영하는 신체적인 특성 정보를 이용한다. 본 논문에서 제안하는 방법은 사람의 움직임 정보를 이용한 가상 캐릭터의 제어와 같은 마커를 사용하지 않는 다양한 HCI 응용분야에 사용될 수 있다.

• 한국약용작물학회지
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• 제18권3호
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• pp.157-167
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• 2010

We investigated a method to improve anticancer activities of Acer mono wood extracts by ultra high pressure extraction process. The A. mono was extracted by water at $40^{\circ}C$ and 300 MPa for 15 min (High Pressure Extraction, HPE). The extraction yield by ultra high pressure extraction process was 5.42%. The cytotoxicity on human normal lung cell (HEL299) of the extracts from HPE showed 21.54% lower than that from conventional water extraction at $100^{\circ}C$ in adding the maximum concentration of 1.0 mg/$m{\ell}$. Ultra high pressure extracts process for 15 minutes extracts (HPE15) showed more potent scavenging effect than the control, BHA. On SOD-like test, the HPE15 showed highest activity as 32.4% at 1.0 mg/$m{\ell}$ concentration. Human stomach adenocarcinoma, liver adenocarcinoma, breast adenocarcinoma and lung adenocarcinoma cell growth were inhibited up to about 67~79%, in adding 1.0 mg/$m{\ell}$ of extracts from HPE. HPE was 20~25% higher than conventional water extraction. It was interesting that, among several cancer cell lines (stomach adenocarcinoma, liver adenocarcinoma), the growth of digestive related cancer cells were most effectively inhibited as about 75~79%. On in vivo experiment using ICR mice, the variation of body weight of mice group treated A. mono wood extracts from HPE of 100 mg/kg/day concentration was very lower than control and other group. The survival times of group treated this extracts was 61.96% longer than that of the control group and this extracts showed the lower tumor weight, which were 10.49 g than positive control as 16.17 g. Based on these results, we could tell that the HPE wood extracts of A. mono had higher anticancer activity than conventional water extraction. The results of HPE showed obvious advantages in higher efficiency, shorter extraction time, at lower energy costs.

• 한국식품영양학회지
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• 제32권1호
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• pp.41-49
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• 2019

Carotene, xanthophyll, carotenoid anthocyan, phycopyrine, chlorophyll, and monascus pigments are used as natural coloring agents since they are more stable to human body than synthetic coloring agents. Among them, monascus pigments are a natural red pigment produced by the Monascus purpureus. For the development of edible paint using natural pigment, Monascus purpureus strain was cultured at a temperature of $35^{\circ}C$ for 15 days on a PDYA plate and liquid medium to produce a red pigment. In addition, a large amount of the red pigment was extracted from Hongkuk Koji in parallel with water extraction and ultrasonic wave extraction. At this time, the yield of ultrasonic extract was 2~4 times higher. Thus, Monascus purpureus strains, etc. were prepared by freeze-drying powder. In conclusion, natural paints made with red pigments have enabled the development of been edible paints that can be used as eco-friendly materials with good viscosity, enhanced spread ability and coloration.