• Journal of information and communication convergence engineering
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• 제19권1호
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• pp.29-35
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• 2021

While the population of pet dogs and pet-related markets are increasing, there is no convenient and reliable tool for pet health monitoring for pet owners/caregivers. In this paper, we propose a mobile platform-based pre-diagnosis system that pet owners can use for pre-diagnosis and obtaining information on coping strategies based on their observations of the pet dog's abnormal behavior. The proposed system constructs symptom-disease association databases for 100 frequently observed diseases under veterinarian guidance. Then, we apply the possibilistic fuzzy C-means algorithm to form the "probable disease" set and the "doubtable disease" set from the database. In the experiment, we found that the proposed system found almost all diseases correctly, with an average of 4.5 input symptoms and outputs 1.5 probable and one doubtable disease on average. The utility of this system is to alert the owner's attention to the pet dog's abnormal behavior and obtain an appropriate coping strategy before consult a veterinarian.

• 한국콘텐츠학회논문지
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• 제13권2호
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• pp.331-340
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• 2013

최근 의과대학과 의료서비스 산업에서 환자-의사 커뮤니케이션에 관한 논의가 활발히 이루어지고 있다. 환자-의사 커뮤니케이션이란 '진료면담'에서 환자와 의사간의 쌍방향 의사소통으로써, 환자와 의사 양자에게 모두 긍정적인 효과를 가져다주는 것으로 알려져 있다. 이 연구에서는 의사의 커뮤니케이션 스킬을 향상시켜 환자와 의사간의 의사소통을 원활히 할 수 있는 방안으로 코칭기법을 접목한 의사코칭 모델을 개발하였다. 모델 개발 방법은 문헌검토를 통해 초안을 개발하였고, 전문가 자문과 의사평가를 통해 수정 보완하였다. 연구 결과, 의사코칭 모델을 총 5단계로 구성하였다. 첫째, '관계 형성'으로 의사가 코칭에 대한 기대나 관심을 가지도록 한다. 둘째, '변화 주제 인식'으로 환자와의 커뮤니케이션에서 의사의 문제점과 장점을 파악하여 코칭의 방향을 설정한다. 셋째, '관점의 획득'으로 의사가 환자의 관점에서 생각할 수 있도록 유도한다. 넷째, '문제 해결 및 의사소통 역량 강화'로서 의사의 커뮤니케이션 스킬 개선사항을 세부항목으로 제시한다. 다섯째, '목표 설정 및 지원'으로 개선 사항 목표를 설정하고 장점을 유지 강화할 수 있는 실천 방안을 합의한다. 개발된 의사코칭 모델은 환자-의사 커뮤니케이션 개선을 위해 의사들을 대상으로 코칭기법을 처음으로 적용했다는데 가장 큰 의의가 있다. 향후 의료서비스 현장에서 활용될 경우, 의사들의 커뮤니케이션 스킬 향상과 환자 공감적 능력 향상에 효과가 있을 것으로 판단된다. 이를 통해 환자들의 진료만족도를 높이는데 기여할 것이다.

• 동의신경정신과학회지
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• 제24권1호
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• pp.131-144
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• 2013

Objectives : To provide information on the safety of ACM, we carried out a single oral dose-increasing toxicity and 4-weeks repeated oral dose determining test of ACM in beagle dogs. Methods : In a single oral dose-increasing toxicity test, beagles were treated with ACM orally increasing dose level (1,000, 2,000, 5,000 mg/㎏) at interval of 3 days. After administration, signs of toxicity were observed for two weeks. In 4-weeks repeated oral dose determinating test, beagles were treated with ACM with oral dose 500, 1,000, 2,000 mg/kg for 4 weeks. Mortality, clinical signs, body weight changes, food consumption, urinalysis, hematological and biochemical parameters, organ weights, necropsy findings, and histological findings were monitored during the study period. Results : In a single oral dose-increasing toxicity test, we found no mortality, abnormalities in clinical signs, body weight, and necropsy findings during the study period. In 4-weeks repeated oral dose determinating test, we found no mortality, abnormalities in clinical signs, body weight, food consumption, urinalysis, hematological and biological parameters, gross findings, organ weights, necropsy findings, and histopathological findings in any of the beagles tested. Conclusions : The results obtained in these studies suggest that maximum tolerated dose (MTD) of ACM in male and female beagle dogs was supposed to be over 5,000 mg/kg. For the future studies of toxicity, it is advisable that high dose and low dose are set at 2000 mg/kg and 500 mg/kg, respectively.

• Elastomers and Composites
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• 제56권4호
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• pp.209-216
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• 2021

In this study, we observed the mechanical properties, thermal stability, and low temperature sealing performance of fluorosilicone elastic composites. When the blend ratio of Phenyl vinyl methyl silicone (PVMQ) was increased, the tensile strength, modulus at 100%, and compression set were decreased. The thermal stability of fluorosilicone elastic composites showed a similar tendency. These were caused by poorer green strength of PVMQ than Fluorosilicone rubber (FVMQ). The change in the tensile strength and elongation at -40℃ showed a decreasing tendency with increasing PVMQ blend ratio. By increasing the PVMQ blend ratio, low-temperature performance was improved. The Dynamic mechanical analysis (DMA) results showed that T_g was decreased and low-temperature performance was improved with increasing PVMQ blend ratio. However tanδ was decreased becaused of the poor green strength and elasticity of PVMQ. From a hysteresis loss at -40℃, the hysteresis loss value was increased and fluorosilicone elastic composites showed the decreasing tendency of elasticity with increasing PVMQ blend ratio. From the TR test, TR10 was decreased with increasing PVMQ blend ratio. FS-4 (45% PVMQ blended composites) showed a TR10 of -68.0℃ that was 5℃ lower than that of FS-1 (100% FVMQ). The gas leakage temperature was decreased with increasing PVMQ blend ratio. The gas leakage temperature of FS-4 was -69.2℃ that was 5℃ lower than that of FS-1. Caused by the polymer chain started to transfer from a glassy state to a rubbery state and had a mobility of chain under T_g, the gas leakage temperature showed a lower value than T_g. The sealing performance at low temperature was dominated by T_g that directly affected the mobility of the polymer chain.

• International journal of advanced smart convergence
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• 제8권4호
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• pp.75-81
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• 2019

Though recent advancement of deep learning methods have provided satisfactory results from large data domain, somehow yield poor performance on few-shot classification tasks. In order to train a model with strong performance, i.e. deep convolutional neural network, it depends heavily on huge dataset and the labeled classes of the dataset can be extremely humongous. The cost of human annotation and scarcity of the data among the classes have drastically limited the capability of current image classification model. On the contrary, humans are excellent in terms of learning or recognizing new unseen classes with merely small set of labeled examples. Few-shot learning aims to train a classification model with limited labeled samples to recognize new classes that have neverseen during training process. In this paper, we increase the backbone depth of the embedding network in orderto learn the variation between the intra-class. By increasing the network depth of the embedding module, we are able to achieve competitive performance due to the minimized intra-class variation.

• 전기학회논문지
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• 제56권7호
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• pp.1324-1330
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• 2007

In this paper, we propose pattern recognition algorithm for activities of daily living by adopting extreme learning machine based on single layer feedforward networks(SLFNs) to the signal from bidirectional accelerometer. For activity classification, 20 persons are participated and we acquire 6, types of signals at standing, walking, running, sitting, lying, and falling. Then, we design input vector using reduced model for ELM input. In ELM classification results, we can find accuracy change by increasing the number of hidden neurons. As a result, we find the accuracy is increased by increasing the number of hidden neuron. ELM is able to classify more than 80 % accuracy for experimental data set when the number of hidden is more than 20.

• International Journal of Safety
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• 제2권1호
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• pp.7-11
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• 2003

Structure of the counterflow nonpremixed flames were investigated by using Fire Dynamics Simulator(FDS) and OPPDIF to evaluate FDS for simulations of the diffusion flame. FDS, employed a mixture fraction formulation, were applied to the diluted axisymmetric methane-air nonpremixed counterflow flames. Fuel concentration in the mixture of methane and nitrogen was considered as a numerical parameter in the range from 20% to 100% increasing by 10% by volume at the global strain rates of $a_g = 20S^{-l} and 80S^{-1}$ respectively. In all the computations, the gravity was set to zero since OPPDIF is not able to compute the buoyancy effects. It was shown by the axisymmetric simulation of the flames with FDS that increasing fuel concentration increases the flame thickness and decreases the flame radius. The centerline temperature and axial velocity, and the peek flame temperature showed good agreement between the both methods.

• 한국경영과학회지
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• 제16권2호
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• pp.118-127
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• 1991

In this paper, criteria and algorithms for the optimal service rate in a closed queueing network have been established. The objective is to minimize total cost. It is shown that system throughput is increasing concave over the service rate of a node and cycle time is increasing convex over the set of service times with a single calss of cubsomers. This enables developing an algorithm using a steepest descent method when the cost function for service rate is convex. The efficiency of the algorithm rests on the fact that the steepest descent direction is readily obtained at each iteration from the MVA algorithm. Several numerical examples are presented. The major application of this research is optimization of facility capacity in a manufacturing system.

• 한국정보처리학회:학술대회논문집
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• 한국정보처리학회 2007년도 춘계학술발표대회
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• pp.1167-1170
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• 2007

This paper introduces a data storage transport protocol internet Advanced Technology Attachment (iATA) for ATA storage devices that can be accessed over (TCP/IP) networks. As the access speed of Advanced Technology Attachment (ATA) type storage is increasing, the importance of sharing the ATA type storages over internet is also increasing. We are proposing a protocol in which we have implemented the basic ATA command set to access the ATA type remote storage devices over the TCP/IP networks.In this paper, we give basic details of the protocol and discuss the existing storage protocols which are mainly used for accessing block storage like internet Small Computer System Interface (iSCSI) Hyper Small Computer System Interface (HyperSCSI) and ATA over Ethernet (AoE).

• 한국세라믹학회지
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• 제44권8호
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• pp.412-418
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• 2007

The atomic scale details of the melting of solid argon were monitored with the aid of molecular dynamics simulations. The potential energy distribution is substantially disturbed by an increase in the interatomic distance and the random of set distance from the lattice points, with increasing temperature. The potential energy barriers between the lattice points decrease in magnitude with the temperature. Eventually, at the melting point, these barriers can be overcome by atoms that are excited with the entropy gain acquired when the atoms obtain rotational freedom in their atomic motion, and the rotational freedom leads to the collapse of the crystal structure. Furthermore, it was found that the surface of crystals plays an important role in the melting process: the surface eliminates the barrier for the nucleation of the liquid phase and facilitates the melting process. Moreover, the atomic structure of the surface varies with increasing temperature, first via surface roughening and then, before the bulk melts, via surface melting.