• 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.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.15 no.5
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• pp.1060-1065
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• 2011

In this paper, the proposed method is recognized the hands using color information with input image of the camera. It controls the mouse pointer using recognized hands. In addition, specific commands with the mouse pointer is designed to perform. Most users felt uncomfortable since existing interaction multimedia systems depend on a particular external input devices such as pens and mouse However, the proposed method is to compensate for these shortcomings by hand without the external input devices. In experimental methods, hand areas and backgrounds are separated using color information obtaining image from camera. And coordinates of the mouse pointer is determined using coordinates of the center of a separate hand. The mouse pointer is located in pre-filled area using these coordinates, and the robot will move and execute with the command. In experimental results, the recognition of the proposed method is more accurate but is still sensitive to the change of color of light.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.39 no.4
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• pp.531-540
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• 2019

Existing dozer productivity computation models use different input variables, formulas, productivity correction factors, and experimental data source. This paper presents a method that characterizes the productivity outputs obtained by the PLS model and the Caterpillar model that are accepted as industry standards. The method identifies the input variables to be collected from the site, the performance charts to be referenced, and the formulas and implements them in a single computational tool. This study verifies that the PLS model may replace the manual computational process of Caterpillar model by eliminating reliance on graphics manipulation. Replacing the Caterpillar model with the PLS model and implementing the process as a function contributes to assess the productivity of a dozer timely by encouraging to utilize real-time information collected directly from the site. This study allows researchers and practitioners to effectively deal with the values of productivity correction factors collected from the job site and to control the productivity. The practicality and effectiveness of the method have been validated by applying to a project case.

• The Journal of the Korea institute of electronic communication sciences
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• v.18 no.5
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• pp.981-988
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• 2023

As the usage of unmanned aerial vehicles expands, the development and the demand of related technologies are increasing. As the frequency of operation increases and the convenience of operation is emphasized, the importance of related autonomous flight technology is also highlighted. Establishing a path plan to reach the destination in autonomous flight of an unmanned aerial vehicle is important in guidance and control, and a technology for automatically generating path plan is required in order to maximize the effect of unmanned aerial vehicle. In this study, the optimization research of path planning using rapid-exploring random tree method was performed for increasing the effectiveness of autonomous operation. The path planning optimization method considering the characteristics of the unmanned aerial vehicle is proposed. In order to achieve indexes such as optimal distance, shortest time, and passage of mission points, the path planning was optimized in consideration of the mission goals and dynamic characteristics of the unmanned aerial vehicle. The proposed methods confirmed their applicability to the generation of path planning for unmanned aerial vehicles through performance verification for obstacle situations.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.24 no.2
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• pp.295-310
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• 2014

DCS (Distributed Control System), the main control system of power plants, is an automated system for enhancing operational efficiency by monitoring, tuning and real-time operation. DCS is becoming more intelligent and open systems as Information technology are evolving. In addition, there are a large amount of investment to enable proactive facility management, maintenance and risk management through the predictive diagnostics. However, new upcoming weaponized malware, such as Stuxnet designed for disrupting industrial control system(ICS), become new threat to the main control system of the power plant. Even though these systems are not connected with any other outside network. The main control systems used in the power plant usually have been used for more than 10 years. Also, this system requires the extremely high availability (rapid recovery and low failure frequency). Therefore, installing updates including security patches is not easy. Even more, in some cases, installing security updates can break the warranty by the vendor's policy. If DCS is exposed a potential vulnerability, serious concerns are to be expected. In this paper, we conduct the penetration test by using NESSUS, a general-purpose vulnerability scanner under the simulated environment configured with the Ovation version 1.5. From this result, we suggest a log analysis method to detect the security infringement and react the incident effectively.

• Journal of the Korean Institute of Intelligent Systems
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• v.25 no.2
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• pp.174-179
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• 2015

Failure Mode and Effects Analysis (FMEA) has been used by Dynamic Positioning (DP) system for risk and reliability analysis. However, there are limitations associated with its implementation in offshore project. 1) since the failure data measured from the SCADA system is missing or unreliable, assessments of Severity, Occurrence, Detection are based on expert's knowledge; 2) it is not easy for experts to precisely evaluate the three risk factors. The risk factors are often expressed in a linguistic way. 3) the relative importance among three risk factors are rarely even considered. To solve these problems and improve the effectiveness of the traditional FMEA, we suggest a Fuzzy-FMEA method for risk and failure mode analysis in Dynamic Positioning System of offshore. The information gathered from DP FMEA report and DP FMEA Proving Trials is expressed using fuzzy linguistic terms. The proposed method is applied to an offshore Dynamic Positioning system, and the results are compared with traditional FMEA.

• JSTS:Journal of Semiconductor Technology and Science
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• v.11 no.3
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• pp.135-145
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• 2011

Accurate process characterization and optimization are the first step for a successful advanced process control (APC), and they should be followed by continuous monitoring and control in order to run manufacturing processes most efficiently. In this paper, process characterization and recipe optimization methods with multiple outputs are presented in high density plasma-chemical vapor deposition (HDP-CVD) silicon dioxide deposition process. Five controllable process variables of Top $SiH_4$, Bottom $SiH_4$, $O_2$, Top RF Power, and Bottom RF Power, and two responses of interest, such as deposition rate and uniformity, are simultaneously considered employing both statistical response surface methodology (RSM) and neural networks (NNs) based genetic algorithm (GA). Statistically, two phases of experimental design was performed, and the established statistical models were optimized using performance index (PI). Artificial intelligently, NN process model with two outputs were established, and recipe synthesis was performed employing GA. Statistical RSM offers minimum numbers of experiment to build regression models and response surface models, but the analysis of the data need to satisfy underlying assumption and statistical data analysis capability. NN based-GA does not require any underlying assumption for data modeling; however, the selection of the input data for the model establishment is important for accurate model construction. Both statistical and artificial intelligent methods suggest competitive characterization and optimization results in HDP-CVD $SiO_2$ deposition process, and the NN based-GA method showed 26% uniformity improvement with 36% less $SiH_4$ gas usage yielding 20.8 ${\AA}/sec$ deposition rate.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.20 no.6
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• pp.1136-1141
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• 2016

IoT technology has been used as a core technology of convergence service that needs intelligent information processing, and the importance is largely emerging now. And internal network construction thru IoT interaction device can connect with IoT device effectively, provide diverse services by connection with open platform. Especially, beacon that is based on low electric power bluetooth device is receiving attention as one of core technology of IoT. Beacon technology is utilized widly in various fields of industry, and there are lot of demands in the specific environment and conditions beyond the basic function. On this thesis, the authors are proposing the beacon device that utilized acceleration sensor and hole sensor. this beacon device can control the target on specific situation thru sensing of moving target. For the more, we will expect to apply to the various type of factory environments like detachable installation, optimized management using sensor.

• Journal of Institute of Control, Robotics and Systems
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• v.11 no.12
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• pp.1011-1019
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• 2005

In this paper, Ubiquitous Home Mess-Cleanup Robot(UHMR), which has a practical function of the automatic mess-cleanup, is developed. The vacuum-cleaner had made the burden of house chore lighten but the operation labour of a vacuum-cleaner had been so severe. Recently, the cleaning robot was producted to perfectly solve the cleaning labour of a house but it also was not successful because it still had a problem of mess-cleaning, which was the clean-up of big trash and the arrangement of newspapers, clothes, etc. The cleaning robot is to just vacuum dust and small trash but has no function to arrange and take away before the automatic vacuum-cleaning. For this reason, the market for the cleaning robot is not yet built up. So, we need a design method and technological algorithm of new automatic machine to solve the problem of mess-cleanup in house. It needs functions of agile automatic navigation, novel manipulation system for mess-cleanup. The automatic navigation system has to be controlled for the full scanning of living room, to recognize the absolute position and orientation of tile self, the precise tracking of the desired path, and to distinguish the mess object to clean-up from obstacle object to just avoid. The manipulate,, which is not needed in the vacuum-cleaning robot, must have the functions, how to distinguish big trash to clean from mess objects to arrange, how to grasp in according to the form of mess objects, how to move to the destination in according to mess objects and arrange them. We use the RFID system to solve the problems in this paper and propose the reading algorithm of RFID tags installed in indoor objects and environments. Then, it should be an intelligent system so that the mess cleaning task can be autonomously performed in a wide variety of situations and environments. It needs to also has the entertainment functions for the good communication between the human and UHMR. Finally, the good performance of the designed UHMR is confirmed through the results of the mess clean-up and arrangement.

• Journal of Institute of Control, Robotics and Systems
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• v.14 no.1
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• pp.21-26
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• 2008

It was already realized at a current technological level of home network systems that the systems recognizes a user's simple order and carry out the order in the ubiquitous computing environment. However home is not a simple environment consisting into a large number of family members, so various order and situation would be needed accordingly. From now on we need to reach the technological level to infer that how is the user's behavior patterns and what kinds of service is the fittest to user who belong to the ubiquitous computing environment by using the result of the context interpreter. In this regards, active inferred-model needs to be suggested upgrading user's command into one step more higher level than the simple one adapting diversified feature. This study would like to suggest this active model recognizing context, which is user's environmental information applying basic network and inferring Context-based Service that user wants through the recognized result This study proposes a new method that can infer the user's desire in ubiquitous computing environment. First of all, we define a context as user's information of ubiquitous computing environment situation that user belongs to and we classify the context into 4W1H(Where, Who, When, What) formats. We construct Bayesian network and put the factor of context use as Bayesian network nodes. As a result, we can infer the user's behavior pattern and most proper service for user in the intelligent space from the probabilistic result of Bayesian network.