• Journal of Internet Computing and Services
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• v.24 no.5
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• pp.17-27
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• 2023

Today, as AI (Artificial Intelligence) technology develops and its practicality increases, it is widely used in various application fields in real life. At this time, the AI model is basically learned based on various statistical properties of the learning data and then distributed to the system, but unexpected changes in the data in a rapidly changing data situation cause a decrease in the model's performance. In particular, as it becomes important to find drift signals of deployed models in order to respond to new and unknown attacks that are constantly created in the security field, the need for lifecycle management of the entire model is gradually emerging. In general, it can be detected through performance changes in the model's accuracy and error rate (loss), but there are limitations in the usage environment in that an actual label for the model prediction result is required, and the detection of the point where the actual drift occurs is uncertain. there is. This is because the model's error rate is greatly influenced by various external environmental factors, model selection and parameter settings, and new input data, so it is necessary to precisely determine when actual drift in the data occurs based only on the corresponding value. There are limits to this. Therefore, this paper proposes a method to detect when actual drift occurs through an Anomaly analysis technique based on XAI (eXplainable Artificial Intelligence). As a result of testing a classification model that detects DGA (Domain Generation Algorithm), anomaly scores were extracted through the SHAP(Shapley Additive exPlanations) Value of the data after distribution, and as a result, it was confirmed that efficient drift point detection was possible.

• Korean Chemical Engineering Research
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• v.62 no.3
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• pp.238-245
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• 2024

The lactate electrode can be utilized either as an electrode for lactate sensor to monitor the patient's health status, stress level, and athlete's fatigue in real time or lactate fuel cell. In this study, we fabricated a high-performance electrode composed of lactate oxidase, catalase, and mitochondria, and investigated the surface analysis and electrochemical properties of this electrode. Carbon paper modified with single-walled carbon nanotubes (CP-SWCNT) had significantly improved electrical conductivity compared to before modification. The electrode to which lactate oxidase, catalase, and mitochondria were attached (CP-SWCNT-LOx-Cat-Mito) produced a higher current than the electrode to which lactate oxidase and catalase were attached. The amount of reduction current produced by the bilirubin oxidase (BOD)-attached electrode (CP-SWCNT-BOD) was greatly affected by the presence or absence of oxygen in the electrolyte. The fuel cell composed of CP-SWCNT-LOx-Cat-Mito (anode) and CP-SWCNT-BOD (cathode) produced maximum power (29 ㎼/cm²) at a discharge current density of 133 ㎂/cm². From this study, we had proved that mitochondria is essential for improving lactate sensor and fuel cell performance.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.14 no.2
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• pp.828-834
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• 2013

In this paper, TMC (Tracker Motion Controller) as one of the many research methods for condensing efficiency improvements can be condensed into efficient solar system configuration to improve the power generation efficiency of the castle with Concentrated solar silicon and photovoltaic systems (CPV)experiments using PV systems. Microprocessor used on the solar system, tracing the development of solar altitude and latitude of each is calculated in real time. Also accept the value from the sensor, motor control and communication with the central control system by calculating the value of the current position of the sun, there is a growing burden on the applicability. Through the way the program is appropriate for solar power systems and sensors hybrid-type algorithm was implemented in the ARM core with built-in TMC, Concentrated CPV system compared to the existing PV systems, through the implementation of the TMC in the country's power generation efficiency compared and analyzed. Sensor method using existing experimental results Concentrated solar power systems to communicate the value of GPS location tracking method hybrid solar horizons in the coordinate system of the sun's azimuth and elevation angles calculated by the program in the calculations of astronomy through experimental resultslook clear day at high solar irradiation were shown to have a large difference. Stopped after a certain period of time, the sun appears in the blind spot of the sensor, the sensor error that can occur from climate change, however, do not have a cloudy and clear day solar radiation sensor does not keep track of the position of the sun, rather than the sensor of excellence could be found. It is expected that research is constantly needed for the system with ongoing research for development of solar cell efficiency increases to reduce the production cost of power generation, high efficiency condensing type according to the change of climate with the optimal development of the ability TMC.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.41 no.5
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• pp.361-366
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• 2017

As the recent development of computing architecture and application software technology, real world simulation, which is the ultimate destination of computer simulation, is emerging as a practical issue in several research sectors. In this paper, metal plate motion in a square shock tube for small time interval was calculated using a supercomputing-based fluid-structure-combustion multi-physics simulation tool called Illinois Rocstar, developed in a US national R amp; D program at the University of Illinois. Afterwards, the simulation results were compared with those from experiments. The coupled solvers for unsteady compressible fluid dynamics and for structural analysis were based on the finite volume structured grid system and the large deformation linear elastic model, respectively. In addition, a strong correlation between calculation and experiment was shown, probably because of the predictor-corrector time-integration scheme framework. In the future, additional validation studies and code improvements for higher accuracy will be conducted to obtain a reliable open-source software research tool.

• Korean Chemical Engineering Research
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• v.48 no.6
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• pp.757-762
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• 2010

Since the quality and performance of medicinal products are heavily dependent upon the size, shape and polymorphism of active pharmaceutical ingredients(APIs), their crystallization has been regarded as one of the most important pharmaceutical processes. In this study, NIR-based inline measurements were employed to monitor key attributes of API particles real-time during the crystallization process. Principal component analysis(PCA) method was selected to correlate inline NIR spectra while the well-known aspirin was studied as a model drug. According to our characterization results, the ratio of ethanol to acetone did not cause any change in polymorphism, but resulted in a significant difference in the nucleation time, crystal growth and crystal shape. These phenomenological changes were well correlated with the PCA's implications. It turned out that the NIR-based inline monitoring technology can be employed well in observing and predicting key quality attributes such as crystal size during pharmaceutical crystallization processes.

• Journal of Korean Society for Geospatial Information Science
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• v.22 no.1
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• pp.31-39
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• 2014

The trend of information service and its utilization has been gradually evolving due to the technological breakthrough in IT industries and the spread of smart phones. Especially regarding smart phones, a vast array of applications are being developed and employed for the purpose of providing real time information. Recently, numerous studies have been made and applied in regards to the efficient management and the supply of cadastral control point information. This research has developed and applied the NFC Cadastral Control Point, an advanced version of QR code Cadastral Control Point, which is installed and utilized in Dong-gu Ulsan, Korea, and an application that can utilize both the QR code and the NFC. In addition, this research continues on to analyzing the utility of the two methods that the survey use of a General Cadastral Control Point and the NFC Cadastral Control Point. Having implemented both methods, NFC Cadastral Control Point outweighed its counterpart in terms of the damage it gets from the outside influence and availability. Moreover, through developing Cadastral Control Point that could apply both the QR code Cadastral Control Point and NFC Cadastral Control Point, the research saw tremendous improvements compared to the survey method using the previously existing reference point performance. The results conveyed the fact that cadastral information application was time saving, convenient, and efficient in terms of finding information. Henceforth, with government's administration over Cadastral Control Point and with the development of more application for providing information, a nation-wide monitoring of Cadastral Control Point is considered possible and an efficient usage of information service is expected as well.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.30 no.6
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• pp.1115-1130
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• 2020

Modern vehicles are equipped with a number of ECUs(Electronic Control Units), and ECUs can control vehicles efficiently by communicating each other through CAN(Controller Area Network). However, CAN bus is known to be vulnerable to cyber attacks because of the lack of message authentication and message encryption, and access control. To find these security issues related to vehicle hacking, CAN Fuzzing methods, that analyze the vulnerabilities of ECUs, have been studied. In the existing CAN Fuzzing methods, fuzzing inputs are randomly generated without considering the structure of CAN messages transmitted by ECUs, which results in the non-negligible fuzzing time. In addition, the existing fuzzing solutions have limitations in how to monitor fuzzing results. To deal with the limitations of CAN Fuzzing, in this paper, we propose a Non-Random CAN Fuzzing, which consider the structure of CAN messages and systematically generates fuzzing input values that can cause malfunctions to ECUs. The proposed Non-Random CAN Fuzzing takes less time than the existing CAN Fuzzing solutions, so it can quickly find CAN messages related to malfunctions of ECUs that could be originated from SW implementation errors or CAN DBC(Database CAN) design errors. We evaluated the performance of Non-Random CAN Fuzzing by conducting an experiment in a real vehicle, and proved that the proposed method can find CAN messages related to malfunctions faster than the existing fuzzing solutions.

• Journal of the Institute of Convergence Signal Processing
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• v.22 no.4
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• pp.185-192
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• 2021

Various methods have been proposed to determine the defect detection of welding bead, and recently sensor data and image data inspection have been steadily announced. There are advantages that sensor data inspection is highly accurate, and two-dimensional-based image data inspection is able to determine the position of the welding bead. However, when analyzing only with sensor data, it is difficult to determine whether the welding has been performed at the correct position. On the other hand, the image data inspection does not have high accuracy due to noise and measurement errors. In this paper, we propose a method that can complement the shortcomings of each inspection method and increase its advantages to improve accuracy and speed up inspection by fusing sensor data inspection which are average current, average volt, and mixed gas data, and image data inspection methods and is implemented as software. In addition, it is intended to allow users to conveniently and intuitively analyze and grasp the results by performing analysis using a graphical user interface(GUI) and checking the data and inspection results used for the inspection. Sensor inspection is performed using the characteristics of each sensor data, and image data is inspected by applying a morphology geodesic active contour algorithm. The experimental results showed 98% accuracy, and when performing the inspection on the four image data, and sensor data the inspection time was about 1.9 seconds, indicating the performance of software that can be used as a real-time inspector in the welding process.

• Journal of Navigation and Port Research
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• v.46 no.6
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• pp.562-569
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• 2022

The alarm monitoring technology applied to existing operating ships manages data items such as temperature and pressure with AMS (Alarm Monitoring System) and provides an alarm to the crew should these sensing data exceed the normal level range. In addition, the maintenance of existing ships follows the Planned Maintenance System (PMS). whereby the sensing data measured from the equipment is monitored and if it surpasses the set range, maintenance is performed through an alarm, or the corresponding part is replaced in advance after being used for a certain period of time regardless of whether the target device has a malfunction or not. To secure the reliability and operational safety of ship engine operation, it is necessary to enable advanced diagnosis and prediction based on real-time condition monitoring data. To do so, comprehensive measurement of actual ship data, creation of a database, and implementation of a condition diagnosis monitoring system for condition-based predictive maintenance of auxiliary equipment and piping must take place. Furthermore, the system should enable management of auxiliary equipment and piping status information based on a responsive web, and be optimized for screen and resolution so that it can be accessed and used by various mobile devices such as smartphones as well as for viewing on a PC on board. This update cost is low, and the management method is easy. In this paper, we propose CBM (Condition Based Management) technology, for autonomous ships. This core technology is used to identify abnormal phenomena through state diagnosis and monitoring of pumps and purifiers among ship auxiliary equipment, and seawater and steam pipes among pipes. It is intended to provide performance diagnosis and failure prediction of ship auxiliary equipment and piping for convergence analysis, and to support preventive maintenance decision-making.

• The Transactions of the Korea Information Processing Society
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• v.13 no.6
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• pp.269-277
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• 2024

With the advancement of modern IT technologies, the operation of autonomous vehicles is becoming a reality, and route planning is essential for this. Generally, route planning involves proposing the shortest path to minimize travel distance and the quickest path to minimize travel time. However, the quality of these routes depends on the topological characteristics of the road network graph. If the connectivity structure of the road network is not rational, there are limits to the performance improvement that routing algorithms can achieve. Real drivers consider psychological factors such as the number of turns, surrounding environment, traffic congestion, and road quality when choosing routes, and they particularly prefer routes with fewer turns. This paper introduces a simple path algorithm that seeks routes with the fewest turns, in addition to the traditional shortest distance and quickest time routes, to evaluate the characteristics of road networks. Using this simple path algorithm, we compare and evaluate the connectivity characteristics of road networks in 20 major cities worldwide. By analyzing these road network characteristics, we can identify the strengths and weaknesses of urban road networks and develop more efficient and safer route planning algorithms. This paper comprehensively examines the quality of road networks and the efficiency of route planning by analyzing and comparing the road network characteristics of each city using the proposed simple path algorithm.