• 스마트미디어저널
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• 제12권3호
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• pp.30-37
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• 2023

Alzheimer's disease (AD) symptoms are being treated by early diagnosis, where we can only slow the symptoms and research is still undergoing. In consideration, using T1-weighted images several classification models are proposed in Machine learning to identify AD. In this paper, we consider the improvised feature selection, to reduce the complexity by using wrapping techniques and Restricted Boltzmann Machine (RBM). This present work used the subcortical and cortical features of 278 subjects from the ADNI dataset to identify AD and sMRI. Multi-class classification is used for the experiment i.e., AD, EMCI, LMCI, HC. The proposed feature selection consists of Forward feature selection, Backward feature selection, and Combined PCA & RBM. Forward and backward feature selection methods use an iterative method starting being no features in the forward feature selection and backward feature selection with all features included in the technique. PCA is used to reduce the dimensions and RBM is used to select the best feature without interpreting the features. We have compared the three models with PCA to analysis. The following experiment shows that combined PCA &RBM, and backward feature selection give the best accuracy with respective classification model RF i.e., 88.65, 88.56% respectively.

• Journal of Communications and Networks
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• 제13권2호
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• pp.125-131
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• 2011

Rapid strides are being made to bring to reality the technology of wearable sensors for monitoring patients' physiological data.We study the problem of automatically detecting anomalies in themeasured blood glucose levels. The normal daily measurements of the patient are used to train a hidden Markov model (HMM). The structure of the HMM-its states and output symbols-are selected to accurately model the typical transitions in blood glucose levels throughout a 24-hour period. The learning of the HMM is done using historic data of normal measurements. The HMM can then be used to detect anomalies in blood glucose levels being measured, if the inferred likelihood of the observed data is low in the world described by the HMM. Our simulation results show that our technique is accurate in detecting anomalies in glucose levels and is robust (i.e., no false positives) in the presence of reasonable changes in the patient's daily routine.

• 반도체디스플레이기술학회지
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• 제19권2호
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• pp.96-99
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• 2020

According to brilliant development of smart devices, many related services are being devised. And, almost every service is designed to provide user-centric services based on personal information. In this situation, to prevent unintentional leakage of personal information is essential. Conventionally, ID and Password system is used for the user authentication. This is a convenient method, but it has a vulnerability that can cause problems due to information leakage. To overcome these problem, many methods related to face recognition is being researched. Through this paper, we investigated the trend of user authentication through biometrics and a representative model for face recognition techniques. One is DeepFace of FaceBook and another is FaceNet of Google. Each model is based on the concept of Deep Learning and Distance Metric Learning, respectively. And also, they are based on Convolutional Neural Network (CNN) model. In the future, further research is needed on the equipment configuration requirements for practical applications and ways to provide actual personalized services.

• 항공우주의학회지
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• 제30권3호
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• pp.100-107
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• 2020

Internet of Things (IoT) is a technology that communicates data between devices, which are things, using an embedded sensor connected through network backbone such as the internet. Here, data communication technology, sensor technology, and actuator (interface) technology are fused into IoT and it turns devices into smart things. As a result, vast sized data are being generated and that data is being processed into useful actions that can control the things that are devices to make our lives much fruitful. Nowadays, the IoT, early defined as Machine-to-Machine (M2M) connection, becomes a key technology powered by growing innovation of wireless communication trends in the internet connectivity through mobile networking. This paper gives an overview of Internet of Things and brief information about major technologies and its applications in various fields focusing aviation.

• 한국정보통신학회:학술대회논문집
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• 한국정보통신학회 2015년도 춘계학술대회
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• pp.595-597
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• 2015

최근, 전 세계 주요 국가에서 전략산업으로 육성되고 있는 사물인터넷(IoT : Internet of Things) 기술은 사물과 사물간의 소통이 가능한 상황인식 기반의 미래 인터넷 환경이다. 기존의 연구에는 사람이 직접 명령을 내려 디바이스를 제어하는 P2M(Person to Machine) 방식과 단순 센서 데이터를 통한 단일 디바이스 제어방식이 있다. 하지만, IoT의 일종인 Machine Socialization은 각각의 디바이스들이 디바이스 내부 기능정보를 이용하고, Device Manager를 통하여 전체적인 시나리오를 전개하는 M2M(Machine to Machine)방식의 디바이스 협업 시스템이다. 본 논문에서는 기존의 P2M의 시스템을 M2M의 시스템으로 변화시키기 위한 Machine Socialization의 시스템의 알고리즘을 제안한다.

• 한국산업융합학회 논문집
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• 제15권1호
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• pp.37-42
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• 2012

Trends in semiconductor equipment industry are to reduce the cost of producing semiconductor, semiconductor process development, facility development, and the minimum investment in terms of cost and quality. Semiconductor equipments are being considered to review and development is proceeding at the same time. In the first part of the semiconductor assembly process, in which the importance of die bonding process is emerging, a wide leadframe type die bonding machine is demanded for productivity. Die bonding machine was designed through experiments and by trial and error. It costs a lot of time and financial burden. The purpose of this study is to solve these problems by using the CAE tool 3G. By using finite element method, thermal analysis of die bonding machine to the various widths leadframe die bonder machine rail is performed for design.

• 한국해양공학회지
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• 제34권3호
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• pp.227-236
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• 2020

Underwater acoustics, which is the domain that addresses phenomena related to the generation, propagation, and reception of sound waves in water, has been applied mainly in the research on the use of sound navigation and ranging (SONAR) systems for underwater communication, target detection, investigation of marine resources and environment mapping, and measurement and analysis of sound sources in water. The main objective of remote sensing based on underwater acoustics is to indirectly acquire information on underwater targets of interest using acoustic data. Meanwhile, highly advanced data-driven machine-learning techniques are being used in various ways in the processes of acquiring information from acoustic data. The related theoretical background is introduced in the first part of this paper (Yang et al., 2020). This paper reviews machine-learning applications in passive SONAR signal-processing tasks including target detection/identification and localization.

• 한국실내디자인학회논문집
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• 제13권2호
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• pp.80-90
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• 2004

Scientism is a kind of paradigm since the birth of Modernism. Architectural design was also effected from scientism in the 1st Machine age, and being effected still In the End Machine age. But many architects in the 2nd Machine age express scientism in architectural design as a "science for kick" as SF. The design of Rem Koolhaas follows the line of Modernism which was effected from scientism in many ways. However he shows modified machine aesthetics as SF pataphysics mixed with literary imagination, and now shows new science paradigm in post-modern age. He expresses many new science theory like indeterminacy theory, chaos, catastrophe theory in his works. And those are expressed as indeterminate program that proceeds in non-linear way, rhizome in space, order out of chaos, topological metamorphosis as a catastrophe. This study analyzes the expression of scientism in architectural design of Rem Koolhaas since 1970s.nce 1970s.

• 경영과학
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• 제17권2호
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• pp.67-73
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• 2000

This paper describes a scheduling support system for a plant where the machine environment may be modeled as non-identical parallel machine lines (NPML). That is, there are a number of stages in series with various different-capability-machines at each stage. Arriving continuously are jobs with their specific due dates, processing times and candidate processing machines. We’ve developed a real-time scheduling module in conjunction with a supporting production information system which supplies necessary data to the module. This scheduling module is one of the 9 modules in this system, and is composed of both a scheduling interface and a production monitoring interface. This module allows users to generate many candidate schedules by selecting their business policies. The selective arguments which are available consist of allocation costs, batch sizes and machine selection intervals. They are now being implemented at a powder metallurgy plant.

• Tribology and Lubricants
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• 제19권6호
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• pp.335-341
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• 2003

Recently, the automotive industry is being developed rapidly. On this, a demand of high quality performance­test­machine is increased too. But it is progressive technology that must be combined hydraulic, mechanic and electronic technologies. To construct this system, the design of oil hydraulic circuit, interface skill between sensor and personal computer, data acquisition & display system and integrated control are very important skill. Moreover, reliable data is obtained with vacuum system and complex heat exchange system. Therefore, in this study, we designed a performance­test­machine by using above key technologies and we also made a integrated PC control system using personal computer which is more progressive and flexible method than PLC control.