• KSII Transactions on Internet and Information Systems (TIIS)
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• v.17 no.6
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• pp.1530-1544
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• 2023

Data monitoring is an important foundation of modern science. In most cases, the monitoring data is time-series data, which has high application value. The deep learning algorithm has a strong nonlinear fitting capability, which enables the recognition of time series by capturing anomalous information in time series. At present, the research of time series recognition based on deep learning is especially important for data monitoring. Deep learning algorithms require a large amount of data for training. However, abnormal sample is a small sample in time series, which means the number of abnormal time series can seriously affect the accuracy of recognition algorithm because of class imbalance. In order to increase the number of abnormal sample, a data augmentation method called GANBATS (GAN-based Bi-LSTM and Attention for Time Series) is proposed. In GANBATS, Bi-LSTM is introduced to extract the timing features and then transfer features to the generator network of GANBATS.GANBATS also modifies the discriminator network by adding an attention mechanism to achieve global attention for time series. At the end of discriminator, GANBATS is adding averagepooling layer, which merges temporal features to boost the operational efficiency. In this paper, four time series datasets and five data augmentation algorithms are used for comparison experiments. The generated data are measured by PRD(Percent Root Mean Square Difference) and DTW(Dynamic Time Warping). The experimental results show that GANBATS reduces up to 26.22 in PRD metric and 9.45 in DTW metric. In addition, this paper uses different algorithms to reconstruct the datasets and compare them by classification accuracy. The classification accuracy is improved by 6.44%-12.96% on four time series datasets.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.18 no.2
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• pp.149-156
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• 2018

Now RC cars have become a culture where everyone who wants to feel precise control and rushing instinct regardless of sex, young or old can participate. In addition, RC cars have attracted a lot of people because they can feel the feeling of driving while driving a car in a small, lightweight body. In line with these trends, various development companies are focusing on functional aspects such as driving and speed improvement for each environment and their sophistication. Of course, driving performance alone can bring a tremendous ripple effect, but what you can do with a RC car is only part replacement and motor modification. Therefore, we will develop RC car based on raspberry pie, control by application, add various functions through sensor recognition, and develop RC car that can travel through video information that can be obtained using web cam. As a small RC car, we carry out research that can combine the functions that can be used as a robot that moves at various construction sites and accident sites where people can not enter, and which can attract users' interest.

• Journal of Internet Computing and Services
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• v.7 no.5
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• pp.135-145
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• 2006

This paper presents a novel approach to real-time recognition of 3D environment and objects for intelligent robots. First. we establish the three fundamental principles that humans use for recognizing and interacting with the environment. These principles have led to the development of an integrated approach to real-time 3D recognition and modeling, as follows: 1) It starts with a rapid but approximate characterization of the geometric configuration of workspace by identifying global plane features. 2) It quickly recognizes known objects in environment and replaces them by their models in database based on 3D registration. 3) It models the geometric details on the fly adaptively to the need of the given task based on a multi-resolution octree representation. SIFT features with their 3D position data, referred to here as stereo-sis SIFT, are used extensively, together with point clouds, for fast extraction of global plane features, for fast recognition of objects, for fast registration of scenes, as well as for overcoming incomplete and noisy nature of point clouds. The experimental results show the feasibility of real-time and behavior-oriented 3D modeling of workspace for robotic manipulative tasks.

• Journal of The Korean Association of Information Education
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• v.21 no.3
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• pp.335-342
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• 2017

The artificial intelligence, robot technology, Internet of things, and life sciences that create added value while dramatically transforming human life have been highlighted in the fourth industrial revolution, the next industrial revolution. In order to adapt to the 4th industry, it is necessary to educate students to develop fusion thinking and computing thinking ability. Therefore, in this study, we developed a digital Yut Playing system based on physical computing, reflecting STEAM and decomposition, pattern recognition, abstraction, and algorithm design, which are components of computing thinking. By experiencing the developed system and applying it to education, it raised interest and interest in programming education and improved programming lesson for fusion thinking and computing thinking ability.

• International journal of advanced smart convergence
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• v.7 no.1
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• pp.1-6
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• 2018

In addition to the instability of energy import costs caused by the depletion of petroleum resources, which is a representative energy resource, and the strengthening of various regulations such as the convention on climate change, the plant for bio energy production, which is being watched as the next generation energy, and became subject of various complaints. In order to solve this problem, the bio-plant is underground and the ground is parked, making the convenience and accessibility of citizens more and more accessible. In this situation, the development of bioenergy production technology also increases the risk factor in bioenergy production process. Accordingly this paper explains method about apply the wide angle camera based AOA algorithm to the bio plant to prevent the accidents from spreading due to the lack of facilities and safety devices and the aging of the facilities and suggests a technique that can quickly identify the location and direction when it occurs.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.8 no.5
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• pp.1690-1710
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• 2014

In this paper, we propose the rapid implementation of a 3-dimensional (3D) facial reconstruction from a single frontal face image and introduce a design for its application on a mobile device. The proposed system can effectively reconstruct human faces in 3D using an approach robust to lighting conditions, and a fast method based on a Canonical Correlation Analysis (CCA) algorithm to estimate the depth. The reconstruction system is built by first creating 3D facial mapping from a personal identity vector of a face image. This mapping is then applied to real-world images captured with a built-in camera on a mobile device to form the corresponding 3D depth information. Finally, the facial texture from the face image is extracted and added to the reconstruction results. Experiments with an Android phone show that the implementation of this system as an Android application performs well. The advantage of the proposed method is an easy 3D reconstruction of almost all facial images captured in the real world with a fast computation. This has been clearly demonstrated in the Android application, which requires only a short time to reconstruct the 3D depth map.

• Journal of Internet of Things and Convergence
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• v.6 no.2
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• pp.31-36
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• 2020

The remarkable change in the automobile industry, which is a traditional industrial field, is now evolving into a form of moving toward autonomous functions rather than humans due to various convenience functions and automatic driving or autonomous driving technologies if the person was central when driving the car. This situation is expanding to various industries such as the aviation industry and the drone market, as well as the robot market. The drone market in the aviation industry is being used in various fields due to the unmanned nature of drone operation. Among them, military drones are secret and due to the specificity of technology, details are not disclosed, but as a collection of advanced technologies, they have played a key role in drone development. In this study, the current status of China and the European Union, including the United States, which are major competitors in the drone field, was investigated, and the technologies of major countries were compared and analyzed through the characteristics and operational specifications of the drones currently in operation.

• Fashion & Textile Research Journal
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• v.11 no.6
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• pp.867-877
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• 2009

These days, the fantastic in opposition to classic beauty becomes a genre of creative body expression. The purpose of this study was to analyze the expressive characteristics of body types and meanings in recent fantastic fashion illustration. The method of this study was to analyze recent documentaries, fashion books, internet web site and so forth. The results were as follows: In literatures, pictures and movies, the category of the fantastic body's expressive types were classified as dominant mutant based on SF, multi body or fragment body by disruption, heterogeneous compound based on myth, personified humanoid and non substance in supernatural boundary. The dominant mutant based on SF was expressed image morphing, composition of machine image with body and modern metamorphosis of classic SF body. It means propensity to post-feminism and reservation of meaning analysis based on human unconsciousness. The multi body or fragment body by disruption in fashion illustration was expressed distorted composition of same body pictures, replacement of different bodies, deconstruction and partial omission of body and composition of meaning or non meaning images. It means permanence of self and basic narcissism. The heterogeneous compound based on myth was expressed general composition or optical illusion of various and aggressive animal motive. It means reinterpretation of original myth, metaphor of basic femme fatale, pursuit of permanence and sign of primitive mind in unconsciousness. The personified humanoid was expressed real human body description of mannequin or ball joint doll and anthropomorphism of robot image. It means representative satisfaction and nostalgia of childhood. The non substance in supernatural boundary was expressed grotesque description of ghost, zombie, vampire, angel, fairy, using of symbolic red, black color and non body. It means human's basic desire about immortality and taboo. Through the result of these study, the expression of fantastic body in fashion illustration will expend expressive method and we will understand human and cultural codes of today.

• International journal of advanced smart convergence
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• v.7 no.1
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• pp.42-47
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• 2018

Recently, as the demand for limited resources continues to rise and problems of resource depletion rise worldwide, the importance of renewable energy is gradually increasing. In order to solve these problems, various methods such as energy conservation and alternative energy development have been suggested, and biogas, which can utilize the gas produced from biomass as fuel, is also receiving attention as the next generation of innovative renewable energy. New and renewable energy using biogas is an energy production method that is expected to be possible in large scale because it can supply energy with high efficiency in compliance with energy supply method of recycling conventional resources. In order to more efficiently produce and manage these biogas, a biogas plant has emerged. In recent years, a large number of biogas plants have been installed and operated in various locations. Organic wastes corresponding to biogas production resources in a biogas plant exist in a wide variety of types, and each of the incoming raw materials is processed in different processes. Because such a process is required, the case where the biogas plant process is inefficiently operated is continuously occurring, and the economic cost consumed for the operation of the biogas production relative to the generated biogas production is further increased. In order to solve such problems, various attempts such as process analysis and feedback based on the feedstock have been continued but it is a passive method and very limited to operate a medium/large scale biogas plant. In this paper, we propose "CNN-based production yield prediction algorithm for increasing process efficiency of biogas plant" for efficient operation of biogas plant process. Based on CNN-based production yield forecasting, which is one of the deep-leaning technologies, it enables mechanical analysis of the process operation process and provides a solution for optimal process operation due to process-related accumulated data analyzed by the automated process.

• Proceedings of the KSRS Conference
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• 2005.10a
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• pp.337-340
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• 2005

Context-awareness techniques in ubiquitous computing environment provide various services to users who need to get information via the analysis of collected information from sensors in a spatial area. Context-awareness has been increased in ubiquitous computing and is applied to many different applications such as disaster management system, intelligent robot system, transportation management system, shopping management system, and digital home service. Many researches have recently focused on services that provide the appropriate information, which are collected from Internet by different kinds of sensors, to users according to context of their surrounding environment. In this paper, we propose an abstraction model to manage the large-scale contextual information and their metadata which are collected from different kinds of in-situ sensors in a spatial area and are presented them on the web. This model is composed of the modules expressing functional elements of sensors using sensorML(Sensor Model Language) based on XML language and the modules managing contextual information, which is transmitted from the sensors.