• Radiation Oncology Journal
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• v.28 no.3
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• pp.155-165
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• 2010

Purpose: In order to evaluate the positional uncertainty of internal organs during radiation therapy for treatment of liver cancer, we measured differences in inter- and intra-fractional variation of the tumor position and tidal amplitude using 4-dimentional computed radiograph (DCT) images and gated orthogonal setup kilovolt (KV) images taken on every treatment using the on board imaging (OBI) and real time position management (RPM) system. Materials and Methods: Twenty consecutive patients who underwent 3-dimensional (3D) conformal radiation therapy for treatment of liver cancer participated in this study. All patients received a 4DCT simulation with an RT16 scanner and an RPM system. Lipiodol, which was updated near the target volume after transarterial chemoembolization or diaphragm was chosen as a surrogate for the evaluation of the position difference of internal organs. Two reference orthogonal (anterior and lateral) digital reconstructed radiograph (DRR) images were generated using CT image sets of 0% and 50% into the respiratory phases. The maximum tidal amplitude of the surrogate was measured from 3D conformal treatment planning. After setting the patient up with laser markings on the skin, orthogonal gated setup images at 50% into the respiratory phase were acquired at each treatment session with OBI and registered on reference DRR images by setting each beam center. Online inter-fractional variation was determined with the surrogate. After adjusting the patient setup error, orthogonal setup images at 0% and 50% into the respiratory phases were obtained and tidal amplitude of the surrogate was measured. Measured tidal amplitude was compared with data from 4DCT. For evaluation of intra-fractional variation, an orthogonal gated setup image at 50% into the respiratory phase was promptly acquired after treatment and compared with the same image taken just before treatment. In addition, a statistical analysis for the quantitative evaluation was performed. Results: Medians of inter-fractional variation for twenty patients were 0.00 cm (range, -0.50 to 0.90 cm), 0.00 cm (range, -2.40 to 1.60 cm), and 0.00 cm (range, -1.10 to 0.50 cm) in the X (transaxial), Y (superior-inferior), and Z (anterior-posterior) directions, respectively. Significant inter-fractional variations over 0.5 cm were observed in four patients. Min addition, the median tidal amplitude differences between 4DCTs and the gated orthogonal setup images were -0.05 cm (range, -0.83 to 0.60 cm), -0.15 cm (range, -2.58 to 1.18 cm), and -0.02 cm (range, -1.37 to 0.59 cm) in the X, Y, and Z directions, respectively. Large differences of over 1 cm were detected in 3 patients in the Y direction, while differences of more than 0.5 but less than 1 cm were observed in 5 patients in Y and Z directions. Median intra-fractional variation was 0.00 cm (range, -0.30 to 0.40 cm), -0.03 cm (range, -1.14 to 0.50 cm), 0.05 cm (range, -0.30 to 0.50 cm) in the X, Y, and Z directions, respectively. Significant intra-fractional variation of over 1 cm was observed in 2 patients in Y direction. Conclusion: Gated setup images provided a clear image quality for the detection of organ motion without a motion artifact. Significant intra- and inter-fractional variation and tidal amplitude differences between 4DCT and gated setup images were detected in some patients during the radiation treatment period, and therefore, should be considered when setting up the target margin. Monitoring of positional uncertainty and its adaptive feedback system can enhance the accuracy of treatments.

• Journal of Intelligence and Information Systems
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• v.25 no.1
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• pp.163-177
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• 2019

As smartphones are getting widely used, human activity recognition (HAR) tasks for recognizing personal activities of smartphone users with multimodal data have been actively studied recently. The research area is expanding from the recognition of the simple body movement of an individual user to the recognition of low-level behavior and high-level behavior. However, HAR tasks for recognizing interaction behavior with other people, such as whether the user is accompanying or communicating with someone else, have gotten less attention so far. And previous research for recognizing interaction behavior has usually depended on audio, Bluetooth, and Wi-Fi sensors, which are vulnerable to privacy issues and require much time to collect enough data. Whereas physical sensors including accelerometer, magnetic field and gyroscope sensors are less vulnerable to privacy issues and can collect a large amount of data within a short time. In this paper, a method for detecting accompanying status based on deep learning model by only using multimodal physical sensor data, such as an accelerometer, magnetic field and gyroscope, was proposed. The accompanying status was defined as a redefinition of a part of the user interaction behavior, including whether the user is accompanying with an acquaintance at a close distance and the user is actively communicating with the acquaintance. A framework based on convolutional neural networks (CNN) and long short-term memory (LSTM) recurrent networks for classifying accompanying and conversation was proposed. First, a data preprocessing method which consists of time synchronization of multimodal data from different physical sensors, data normalization and sequence data generation was introduced. We applied the nearest interpolation to synchronize the time of collected data from different sensors. Normalization was performed for each x, y, z axis value of the sensor data, and the sequence data was generated according to the sliding window method. Then, the sequence data became the input for CNN, where feature maps representing local dependencies of the original sequence are extracted. The CNN consisted of 3 convolutional layers and did not have a pooling layer to maintain the temporal information of the sequence data. Next, LSTM recurrent networks received the feature maps, learned long-term dependencies from them and extracted features. The LSTM recurrent networks consisted of two layers, each with 128 cells. Finally, the extracted features were used for classification by softmax classifier. The loss function of the model was cross entropy function and the weights of the model were randomly initialized on a normal distribution with an average of 0 and a standard deviation of 0.1. The model was trained using adaptive moment estimation (ADAM) optimization algorithm and the mini batch size was set to 128. We applied dropout to input values of the LSTM recurrent networks to prevent overfitting. The initial learning rate was set to 0.001, and it decreased exponentially by 0.99 at the end of each epoch training. An Android smartphone application was developed and released to collect data. We collected smartphone data for a total of 18 subjects. Using the data, the model classified accompanying and conversation by 98.74% and 98.83% accuracy each. Both the F1 score and accuracy of the model were higher than the F1 score and accuracy of the majority vote classifier, support vector machine, and deep recurrent neural network. In the future research, we will focus on more rigorous multimodal sensor data synchronization methods that minimize the time stamp differences. In addition, we will further study transfer learning method that enables transfer of trained models tailored to the training data to the evaluation data that follows a different distribution. It is expected that a model capable of exhibiting robust recognition performance against changes in data that is not considered in the model learning stage will be obtained.

• Journal of Intelligence and Information Systems
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• v.27 no.4
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• pp.1-22
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• 2021

Aspect Based Sentiment Analysis (ABSA), which analyzes sentiment based on aspects that appear in the text, is drawing attention because it can be used in various business industries. ABSA is a study that analyzes sentiment by aspects for multiple aspects that a text has. It is being studied in various forms depending on the purpose, such as analyzing all targets or just aspects and sentiments. Here, the aspect refers to the property of a target, and the target refers to the text that causes the sentiment. For example, for restaurant reviews, you could set the aspect into food taste, food price, quality of service, mood of the restaurant, etc. Also, if there is a review that says, "The pasta was delicious, but the salad was not," the words "steak" and "salad," which are directly mentioned in the sentence, become the "target." So far, in ABSA, most studies have analyzed sentiment only based on aspects or targets. However, even with the same aspects or targets, sentiment analysis may be inaccurate. Instances would be when aspects or sentiment are divided or when sentiment exists without a target. For example, sentences like, "Pizza and the salad were good, but the steak was disappointing." Although the aspect of this sentence is limited to "food," conflicting sentiments coexist. In addition, in the case of sentences such as "Shrimp was delicious, but the price was extravagant," although the target here is "shrimp," there are opposite sentiments coexisting that are dependent on the aspect. Finally, in sentences like "The food arrived too late and is cold now." there is no target (NULL), but it transmits a negative sentiment toward the aspect "service." Like this, failure to consider both aspects and targets - when sentiment or aspect is divided or when sentiment exists without a target - creates a dual dependency problem. To address this problem, this research analyzes sentiment by considering both aspects and targets (Target-Aspect-Sentiment Detection, hereby TASD). This study detected the limitations of existing research in the field of TASD: local contexts are not fully captured, and the number of epochs and batch size dramatically lowers the F1-score. The current model excels in spotting overall context and relations between each word. However, it struggles with phrases in the local context and is relatively slow when learning. Therefore, this study tries to improve the model's performance. To achieve the objective of this research, we additionally used auxiliary loss in aspect-sentiment classification by constructing CNN(Convolutional Neural Network) layers parallel to existing models. If existing models have analyzed aspect-sentiment through BERT encoding, Pooler, and Linear layers, this research added CNN layer-adaptive average pooling to existing models, and learning was progressed by adding additional loss values for aspect-sentiment to existing loss. In other words, when learning, the auxiliary loss, computed through CNN layers, allowed the local context to be captured more fitted. After learning, the model is designed to do aspect-sentiment analysis through the existing method. To evaluate the performance of this model, two datasets, SemEval-2015 task 12 and SemEval-2016 task 5, were used and the f1-score increased compared to the existing models. When the batch was 8 and epoch was 5, the difference was largest between the F1-score of existing models and this study with 29 and 45, respectively. Even when batch and epoch were adjusted, the F1-scores were higher than the existing models. It can be said that even when the batch and epoch numbers were small, they can be learned effectively compared to the existing models. Therefore, it can be useful in situations where resources are limited. Through this study, aspect-based sentiments can be more accurately analyzed. Through various uses in business, such as development or establishing marketing strategies, both consumers and sellers will be able to make efficient decisions. In addition, it is believed that the model can be fully learned and utilized by small businesses, those that do not have much data, given that they use a pre-training model and recorded a relatively high F1-score even with limited resources.

• Journal of Wetlands Research
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• v.18 no.4
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• pp.474-480
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• 2016

In this study, formation background of biodiversity and its changes in the process of geologic history, and effects of climate change on biodiversity and human were discussed and the alternatives to reduce the effects of climate change were suggested. Biodiversity is 'the variety of life' and refers collectively to variation at all levels of biological organization. That is, biodiversity encompasses the genes, species and ecosystems and their interactions. It provides the basis for ecosystems and the services on which all people fundamentally depend. Nevertheless, today, biodiversity is increasingly threatened, usually as the result of human activity. Diverse organisms on earth, which are estimated as 10 to 30 million species, are the result of adaptation and evolution to various environments through long history of four billion years since the birth of life. Countlessly many organisms composing biodiversity have specific characteristics, respectively and are interrelated with each other through diverse relationship. Environment of the earth, on which we live, has also created for long years through extensive relationship and interaction of those organisms. We mankind also live through interrelationship with the other organisms as an organism. The man cannot lives without the other organisms around him. Even though so, human beings accelerate mean extinction rate about 1,000 times compared with that of the past for recent several years. We have to conserve biodiversity for plentiful life of our future generation and are responsible for sustainable use of biodiversity. Korea has achieved faster economic growth than any other countries in the world. On the other hand, Korea had hold originally rich biodiversity as it is not only a peninsula country stretched lengthily from north to south but also three sides are surrounded by sea. But they disappeared increasingly in the process of fast economic growth. Korean people have created specific Korean culture by coexistence with nature through a long history of agriculture, forestry, and fishery. But in recent years, the relationship between Korean and nature became far in the processes of introduction of western culture and development of science and technology and specific natural feature born from harmonious combination between nature and culture disappears more and more. Population of Korea is expected to be reduced as contrasted with world population growing continuously. At this time, we need to restore biodiversity damaged in the processes of rapid population growth and economic development in concert with recovery of natural ecosystem due to population decrease. There were grand extinction events of five times since the birth of life on the earth. Modern extinction is very rapid and human activity is major causal factor. In these respects, it is distinguished from the past one. Climate change is real. Biodiversity is very vulnerable to climate change. If organisms did not find a survival method such as 'adaptation through evolution', 'movement to the other place where they can exist', and so on in the changed environment, they would extinct. In this respect, if climate change is continued, biodiversity should be damaged greatly. Furthermore, climate change would also influence on human life and socio-economic environment through change of biodiversity. Therefore, we need to grasp the effects that climate change influences on biodiversity more actively and further to prepare the alternatives to reduce the damage. Change of phenology, change of distribution range including vegetation shift, disharmony of interaction among organisms, reduction of reproduction and growth rates due to odd food chain, degradation of coral reef, and so on are emerged as the effects of climate change on biodiversity. Expansion of infectious disease, reduction of food production, change of cultivation range of crops, change of fishing ground and time, and so on appear as the effects on human. To solve climate change problem, first of all, we need to mitigate climate change by reducing discharge of warming gases. But even though we now stop discharge of warming gases, climate change is expected to be continued for the time being. In this respect, preparing adaptive strategy of climate change can be more realistic. Continuous monitoring to observe the effects of climate change on biodiversity and establishment of monitoring system have to be preceded over all others. Insurance of diverse ecological spaces where biodiversity can establish, assisted migration, and establishment of horizontal network from south to north and vertical one from lowland to upland ecological networks could be recommended as the alternatives to aid adaptation of biodiversity to the changing climate.

• Food preservation and processing industry
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• v.8 no.2
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• pp.6-12
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• 2009

면역반응은 외부 감염원으로부터 신체를 보호하고 외부감염원을 제거하고자 하는 주요항상성 유지기전의 하나이다. 이들 반응은 골수에서 생성되고 비장, 흉선 및 임파절 등에서 성숙되는 면역세포들에 의해 매개된다. 보통 태어나면서부터 얻어진 선천성 면역반응을 매개하는 대식세포, 수지상 세포 등과, 오랜기간 동안 감염된 다양한 면역원에 대한 경험을 토대로 얻어진 획득성 면역을 담당하는 T 임파구 등이 대표적인 면역세포로 알려져 있다. 다양한 면역질환이 최근 주요 사망률의 원인이 되고 있다. 최근, 암, 당뇨 및 뇌혈관질환 등이 생체에서 발생되는 급 만성염증에 의해 발생된다고 보고됨에 따라 면역세포 매개성 염증질환에 대한 치료제 개발을 서두르고 있다. 또한 암환자의 급격한 증가는 암발생의 주요 방어기전인 면역력 증강에 대한 요구들을 가중시키고 있다. 예로부터 사용되어 오던 고려인삼과 홍삼은 기를 보호하고 원기를 회복하는 명약으로 알려진 대표적인 우리나라 천연생약이다. 특별히, 홍삼은 단백질과 핵산의 합성을 촉진시키고, 조혈작용, 간기능 회복, 혈당강하, 운동수행 능력증대, 기억력 개선, 항피로작용 및 면역력 증대에 매우 효과가 좋은 것으로 보고되고 있다. 홍삼에 관한 많은 연구에 비해, 현재까지 홍삼이 면역력 증강에 미치는 효과에 대한 분자적 수준에서의 연구는 매우 미미한 것으로 확인되어져 있다. 홍삼의 투여는 NK 세포나 대식세포의 활성이 증가하고 항암제의 암세포 사멸을 증가시키는 것으로 확인되어졌다. 현재까지 알려진 주요 면역증강 성분은 산성다당류로 보고되었다. 또 한편으로 일부 진세노사이드류에서 항염증 효능이 확인되어졌으며, 이를 통해 피부염증 반응과 관절염에 대한 치료 효과가 있는 것으로 추측되고 있다 [본 연구는 KT&G 연구출연금 (2009-2010) 지원을 받아 이루어졌기에 이에 감사드린다]. 면역반응은 외부 감염물질의 침입으로 유도된 질병환경을 제거하고 수복하는 중요한 생체적 방어작용의 하나이다. 이들 과정은 체내로 유입된 미생물이나 미세화학물질들과 같은 독성물질을 소거하거나 파괴하는 것을 주요 역할로 한다. 외부로 부터 인체에 들어온 이물질에 대한 방어기전은 현재 두 가지 종류의 면역반응으로 구분해서 설명한다. 즉, 선천성 면역 반응 (innate immunity)과 후천성 면역 반응 (adaptive immunity)이 그것이다. 선천성 면역반응은 1) 피부나 점막의 표면과 같은 해부학적인 보호벽 구조와 2) 체온과 낮은 pH 및 chemical mediator (리소자임, collectin류) 등과 같은 생리적 방어구조, 3) phagocyte류 (대식세포, 수지상세포 및 호중구 등)에 의한 phagocytic/endocytic 방어, 그리고 4) 마지막으로 염증반응을 통한 감염에 저항하는 면역반응 등으로 구분된다. 후천성 면역반응은 획득성면역이라고도 불리고 특이성, 다양성, 기억 및 자기/비자기의 인식이라는 네 가지의 특징을 가지고 있으며, 외부 유입물질을 제거하는 반응에 따라 체액성 면역 반응 (humoral immune response)과 세포성 면역반응 (cell-mediated immune response)으로 구분된다. 체액성 면역은 침입한 항원의 구조 특이적으로 생성된 B cell 유래 항체와의 반응과 간이나 대식세포 등에서 합성되어 분비된 혈청내 보체 등에 의해 매개되는 반응으로 구성되어 있다. 세포성 면역반응은 T helper cell (CD4+), cytotoxic T cell (CD8+), B cell 및antigen presenting cell 중개를 통한 세포간 상호 작용에 의해 발생되는 면역반응이다. 선천성 면역반응의 하나인 염증은 우리 몸에서 가장 빈번히 발생되고 있는 방어작용의 하나이다. 예를 들면 감기에 걸렸을 경우, 환자의 편도선내 대식세포나 수지상세포류는 감염된 바이러스 단독 혹은 동시에 감염된 박테리아를 상대로 다양한 염증성 반응을 유도하게 된다. 또한, 상처가 생겼을 경우에도 감염원을 통해 유입된 병원성 세균과 주위조직내 선천성 면역담당 세포들 간의 면역학적 전투가 발생되게 된다. 이들 과정을 통해, 주위 세포나 조직이 손상되면, 즉각적으로 이들 면역세포들 (주로 phagocytes류)은 신속하게 손상을 극소화하고 더 나가서 손상된 부위를 원상으로 회복시키려는 일련의 염증반응을 유도하게 된다. 이들 반응은 우리가 흔히 알고 있는 발적 (redness), 부종 (swelling), 발열 (heat), 통증 (pain) 등의 증상으로 나타나게 된다. 즉, 손상된 부위 주변에 존재하는 모세혈관에 흐르는 혈류의 양이 증가하면서 혈관의 직경이 늘어나게 되고, 이로 인한 조직의 홍반과, 부어 오른 혈관에 의해 발열과 부종이 초래되는 것이다. 확장된 모세혈관의 투과성 증가는 체액과 세포들이 혈관에서 조직으로 이동하게 하는 원동력이 되고, 이를 통해 축적된 삼출물들은 단백질의 농도를 높여, 최종적으로 혈관에 존재하는 체액들이 조직으로 더 많이 이동되도록 유도하여 부종을 형성시킨다. 마지막으로 혈관 내 존재하는 면역세포들은 혈판 내벽에 점착되고 (margination), 혈관벽의 간극을 넓히는 역할을 하는 히스타민 (histamine)이나 일산화질소(nitric oxide : NO), 프로스타그린딘 (prostagladins : PGE2) 및 류코트리엔 (leukotriens) 등과 같은 chemical mediator의 도움으로 인해 혈관벽 사이로 삼출하게 되어 (extravasation), 손상된 부위로 이동하여 직접적인 외부 침입 물질의 파괴나 다른 면역세포들을 모으기 위한 cytokine (tumor necrosis factor [TNF]-$\alpha$, interleukin [IL]-1, IL-6 등) 혹은 chemokine (MIP-l, IL-8, MCP-l등)의 분비 등을 수행함으로써 염증반응을 매개하게 된다. 염증과정시 발생되는 여러 mediator 중 PGE2나 NO 및 TNF-$\alpha$ 등은 실험적 평가가 용이하여 이들 mediator 자체나 생성관련효소 (cyclooxygenase [COX] 및 nitric oxide synthase [NOS] 등)들은 현재항염증 치료제의 개발 연구시 주요 표적으로 연구되고 있다. 염증 반응은 지속기간에 따라 크게 급성염증과 만성염증으로 나뉘며, 삼출물의 종류에 따라서는 장액성, 섬유소성, 화농성 및 출혈성 염증 등으로 구분된다. 급성 염증 (acute inflammation)반응은 수일 내지 수주간 지속되는 일반적인 염증반응이라고 볼 수 있다. 국소반응은 기본징후인 발열과 발적, 부종, 통증 및 기능 상실이 특징적이며, 현미경적 소견으로는 혈관성 변화와 삼출물 형성이 주 작용이므로 일명 삼출성 염증이라고 한다. 만성 염증 (chronic inflammation)은, 급성 염증으로부터 이행되거나 만성으로 시작된다. 염증지속 기간은 보통 4주 이상 장기화 된다. 보통 염증의 경우에는 염증 생성 cytokine인 Th1 cytokine (IL-2, interferone [IFN]-$\gamma$ 및 TNF-$\alpha$ 등)의 생성 후, 거의 즉각적으로 항 염증성 cytokine인 Th2 cytokine(IL-4, IL-6, IL-10 및 transforming growth factor [TGF]-$\beta$ 등)이 생성되어 정상반응으로 회복된다. 그러나, 어떤 원인에서든 면역세포에 의한 염증원 제거 반응이 문제가 되면, 만성염증으로 진행된다. 이 반응에 주로 작용을 하는 염증세포로는 단핵구와 대식세포, 림프구, 형질세포 등이 있다. 암은 전세계적으로 사망률 1위의 원인이 되는 면역질환의 하나이다. 산화적 스트레스나 자외선 조사 혹은 암유발 물질들에 의해 염색체내 protooncogene, tumor-suppressor gene 혹은 DNA repairing gene의 일부 DNA의 돌연변이 혹은 결손 등이 발행되면 정상세포는 암화과정을 시작하게 된다. 양성세포 수준에서 약 5에서 10여년 후 악성수준의 암세포가 생성되게 되면 이들 세포는 새로운 환경을 찾아 전이하게 되는데 이를 통해 암환자들은 다양한 장기에 동인 오리진의 암세포들이 생성한 종양들을 가지게 된다. 이들 종양세포는 정상 장기의 기능을 손상시켜며 결국 생명을 잃게 만든다. 이들 염색체 수준에서의 돌연변이 유래 암세포는 거의 대부분이 체내 면역시스템에 의해 사멸되는 것으로 알려져 있다. 그러나 계속되는 스트레스나 암유발 물질의 노출은 체내 면역체계를 파괴하면서 최후의 방어선을 무너뜨리면서 암발생에 무방비 상태를 만들게 된다. 이런 이유로 체내 면역시스템의 정상적 가동 및 증강을 유도하게 하는 전략이 암예방시 매우 중요한 표적으로 인식되면서 다양한 형태의 면역증강 물질 개발을 시도하고 있다. 인삼은 두릅나무과의 여러해살이 풀로써, 오랜동안 한방 및 민간에서 원기를 회복시키고, 각종 질병을 치료할 수단으로 사용되고 있는 대표적인 전통생약이다. 예로부터 불로(不老), 장생(長生), 익기(益氣), 경신(經身)의 명약으로 구전되어졌는데, 이는 약 2천년 전 중국의 신농본초경(神農本草經)에서 "인삼은 오장(五腸)을 보하고, 정신을 안정시키고, 혼백을 고정하며 경계를 멈추게 하고, 외부로부터 침입하는 병사를 제거하여주며, 눈을 밝게 하고 마음을 열어 더욱 지혜롭게 하고 오랫동안 복용하면 몸이 가벼워지고 장수한다" 라고 기술되어있는 데에서 유래한 것이다. 다양한 연구를 통해 우리나라에서 생산되는 고려인삼 (Panax ginseng)이 효능 면에서 가장 탁월한 것으로 알려져 있으며 특별이 고려인삼으로부터 제조된 고려홍삼은 전세계적으로도 그 효능이 우수한 것으로 보고되어 있다. 대부분의 홍삼 약효는 dammarane계열의 triterpenoid인 ginsenosides라고 불리는 인삼 saponin에 의해 기인된 것으로 알려져 있다. 이들 화합물군의 기본 골격에 따라, protopanaxadiol (PD)계 (22종) 및 protopanaxatriol (PT)계 (10종)으로 구분되고 있다 (표 1). 실험적 접근을 통해 인삼의 약리작용 이해를 위한 다양한 노력들이 경주되고 있으나, 여전히 많은 부분에서 충분히 이해되고 있지 않다. 그러나, 현재까지 연구된 인삼의 약리작용 관련 연구들은 심혈관, 당뇨, 항암 및 항스트레스 등과 같은 분야에서 인삼효능이 우수한 것으로 보고하고 있다. 그러나 면역조절 및 염증현상과 관련된 최근 연구결과들은 많지 않으나, 향후 다양하게 연구될 효능부분으로 인식되고 있다.