• The Transactions of the Korea Information Processing Society
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• v.6 no.3
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• pp.699-709
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• 1999

This paper is aimed at defining items of analysis using SNMP MIB-II for the purpose of managing the Internet based network running on TCP/IP protocol, and then utilize these items, in conjunction with various Web technology and JAVA to design and implement a Web based interface of a management system to analyze the performance and status of the Internet. Among the required items in order to accomplish this task are utilization, interface packet transmission rate, I/O traffic ratio, and so on. Based on these items, the actual analysis is carried out by the Web interface according to the type of analysis. For instance, the interface executes the function of real-time analysis, collection processing, elementary analysis and detailed analysis. The demand of the user is fed into the Web interface which carried out a real-time analysis with the client system which in turn will eventually produce the results of the analysis. In order words, the interface acts as a mediator server for the analysis system. Furthermore, a protocol for exchange of data and messages between the server and the analysis system, the MATP protocol, was also designed. Finally, the results obtained through the system presented in this paper were displayed on screen according to the type of analysis. The system realized in this paper uses We technology and is independent of platform and allows the user to determine the performance of Internet at his/her own host according to the selected items of analysis.

• Journal of the Korea Society of Computer and Information
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• v.11 no.3
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• pp.31-39
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• 2006

This paper presents a novel approach to real-time recognition of 3D environment and objects for various applications such as intelligent robots, intelligent vehicles, intelligent buildings,..etc. 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 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.

• Journal of Convergence for Information Technology
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• v.11 no.9
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• pp.138-144
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• 2021

In the electronic component assembly business, when product defects occur, it is important to track incoming raw material defects or work defects, and it is important to improve suppliers or work sites according to the results. The core task of the smart factory is to build an integrated data hub to process storage, management, and analysis in real time, and to manage cluster processes, energy, environment, and safety. In order to improve reliability through accurate analysis and collection of production data by real-time monitoring of production site management for electronic parts-related small and medium-sized enterprises (SMEs), the establishment of a smart factory is essential. This paper was developed to be utilized in the construction by defining the system configuration method, smart factory-related technology and application cases, considering the characteristics of SMEs related to electronic components that want to introduce a smart factory.

• International Journal of Computer Science & Network Security
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• v.21 no.8
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• pp.288-296
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• 2021

Automated face recognition in a runtime environment is gaining more and more important in the fields of surveillance and urban security. This is a difficult task keeping in mind the constantly volatile image landscape with varying features and attributes. For a system to be beneficial in industrial settings, it is pertinent that its efficiency isn't compromised when running on roads, intersections, and busy streets. However, recognition in such uncontrolled circumstances is a major problem in real-life applications. In this paper, the main problem of face recognition in which full face is not visible (Occlusion). This is a common occurrence as any person can change his features by wearing a scarf, sunglass or by merely growing a mustache or beard. Such types of discrepancies in facial appearance are frequently stumbled upon in an uncontrolled circumstance and possibly will be a reason to the security systems which are based upon face recognition. These types of variations are very common in a real-life environment. It has been analyzed that it has been studied less in literature but now researchers have a major focus on this type of variation. Existing state-of-the-art techniques suffer from several limitations. Most significant amongst them are low level of usability and poor response time in case of any calamity. In this paper, an improved face recognition system is developed to solve the problem of occlusion known as FRS-OCC. To build the FRS-OCC system, the color and texture features are used and then an incremental learning algorithm (Learn++) to select more informative features. Afterward, the trained stack-based autoencoder (SAE) deep learning algorithm is used to recognize a human face. Overall, the FRS-OCC system is used to introduce such algorithms which enhance the response time to guarantee a benchmark quality of service in any situation. To test and evaluate the performance of the proposed FRS-OCC system, the AR face dataset is utilized. On average, the FRS-OCC system is outperformed and achieved SE of 98.82%, SP of 98.49%, AC of 98.76% and AUC of 0.9995 compared to other state-of-the-art methods. The obtained results indicate that the FRS-OCC system can be used in any surveillance application.

• Journal of The Korean Society of Integrative Medicine
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• v.9 no.1
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• pp.41-48
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• 2021

Purpose : The purpose of this study is to find out if it helps to improve static balance ability and weight bearing rate for chronic stroke patients with poor balance in clinical intervention through a method of correcting movement errors while performing a task by vibrotactile bio-feedback providing pressure information. Methods : Fifteen chronic stroke patients (12 male and 3 female) were participated in this study. To examine the effects of vibrotactile bio-feedback and general standing without bio-feedback on static balance ability and weight distribution symmetric index in all subjects randomized with R Studio. The static balance ability and weight distribution symmetric index of the participants was evaluated using a force plate. A paired t-test was used for comparison of each conditions. Statistical significance was set at α=0.05. Results : The comparisons of static balance ability and weight distribution symmetric index in chronic stroke patients after two different condition are as follows. In the static balance ability and weight distribution symmetric index, the vibrotactile feedback providing pressure information showed a significant difference compared to none feedback (p<.001). Conclusion : The vibrotactile bio-feedback providing pressure information in real time can support an improve in static balance ability, uniform weight bearing rehabilitation in chronic stroke patients. In the future, it is hoped that a follow-up study that provides a better direction of intervention compared to various feedback interventions commonly used in clinical practice.

• Journal of Platform Technology
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• v.11 no.6
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• pp.79-88
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• 2023

Recently, industrial accidents have continued to increase due to the industrialization, and worker safety management is recognized as essential to reduce losses due to hazardous factors at work places. To manage the safety of workers, it is required to apply customized safety management artificial intelligence technology that takes into account the characteristics of industrial sites, and a service for real-time risk detection and response to workers depending on the situation based on safety accident types and risk analysis for each task and process. The proposed safety management service consists of worker devices to acquire sensor data, edge devices to collect from IoT-based sensors, and a voice chatbot to support workers' disaster response. The voice chatbot plays a major role in interacting with workers at disaster sites to respond to risks. This paper focuses on real-time risk response using an IoT-based system and voice chatbot on a server for work safety according to the worker's situation. A Scenario-based voice chatbot is used to process responses at the edge level to provide safety management services.

• The Transactions of the Korean Institute of Electrical Engineers A
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• v.53 no.1
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• pp.22-30
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• 2004

As an information-oriented society comes, many people use PC and depend on database that network server has. However, the online data can be missed when a blackout happens and also a power failure effects on standard of judgment on Power Quality. Thus, it is reason of a trend using interruption-free live-line work when a trouble happens to power system. However, the 83％ among the number of people who receive an electric shock experience when a laborer is doing interruption-free live-line works. In interruption-free method, the education and the training problem has been issued. However, we have a few instructors for that training. Furthermore, the trainees have short training period, just 4 weeks. In this paper, to develope the method that has no restriction of a time and place and reduce the wasteful materials, immersion type virtual reality(or environment) technology is used. The users of a 3D immersion type VR training system can interact with the system by doing same action in the real safe environment. Thus, it can be valuable to apply this training system to a dangerous work like as "Interruption-free live-line work exchanging COS(Cut-Out-Switch)". In this program, the user works with a instruction on the window and speaker and can't work other tasks until each part of the task completed. The workers using this system can use their hands and viewpoint movement as he is in a real environment but the trainee can't use all parts and senses of a real body with the current VR technology. Despite of this weak point, when we consider the trends of improvement in electrical devices and communication technology, we can say that 3D graphic VR application has a high potentiality.

• The Transactions of the Korea Information Processing Society
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• v.4 no.11
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• pp.2874-2890
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• 1997

This paper describes a methodology for translation of concurrent software expressed in operating system (OS) calls to Ada. Concurrency is expressed in some legacy software by OS calls that perform concurrent process/task control. Examples considered in this paper are calls in programs in C to Unix and calls in programs in CMS-2 to the Executive Service Routines of ATES or SDEX-20 other software re/reverse engineering research has focused on translating the OS calls in a legacy software to calls to another OS. In this approach, the understanding of software has required knowledge of the underlying OS, which is usually very complicated and informally documented. The research in this paper has focused on translating the OS calls in a legacy software into the equivalent protocols using the Ada facilities. In translation to Ada, these calls are represented by Ada equivalent code that follow the scheme of a message-based kernel oriented architecture. To facilitate translation, it utilizes templates placed in library for data structures, tasks, procedures, and messages. This methodology is a new approach to modeling OS in Ada in software re/reverse engineering. There is no need of knowledge of the underlying OS for software understanding in this approach, since the dependency on the OS in the legacy software is removed. It is portable and interoperable on Ada run-time environments. This approach can handle the OS calls in different legacy software systems.

• Journal of Korea Water Resources Association
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• v.45 no.8
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• pp.839-851
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• 2012

When we evaluate the water supply capacity of a river basin, it is a common practice to gradually increase the water demand and check if the water demands are met. This practice is not only used in the simulation approach, but also in the optimization approach. However, this trial and error approach is a tedious task. Hence, we propose a two-phase method. In the first phase, by assuming that the decision maker has complete information on inflow data, we use a goal programming model that can generate the maximum water supply capacity at one time. In the second phase, we simulate the real-time operation for the critical period by utilizing the water supply capacity given by the goal programming model under the condition that there is no foresight of inflow. We applied the two-phase method to the Geum-River basin, where multi-purpose weirs were newly constructed. By comparing the results of the goal programming model with those of the real-time simulation model we could comprehend and estimate the effect of perfect inflow data on the water supply capacity.

• The Journal of the Acoustical Society of Korea
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• v.42 no.2
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• pp.102-111
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• 2023

Automatic Music Transcription (AMT) is a task that detects and recognizes musical note events from a given audio recording. In this paper, we focus on reducing the latency of real-time AMT systems on piano music. Although neural AMT models have been adapted for real-time piano transcription, they suffer from high latency, which hinders their usefulness in interactive scenarios. To tackle this issue, we explore several techniques for reducing the intrinsic latency of a neural network for piano transcription, including reducing window and hop sizes of Fast Fourier Transformation (FFT), modifying convolutional layer's kernel size, and shifting the label in the time-axis to train the model to predict onset earlier. Our experiments demonstrate that combining these approaches can lower latency while maintaining high transcription accuracy. Specifically, our modified model achieved note F1 scores of 92.67 % and 90.51 % with latencies of 96 ms and 64 ms, respectively, compared to the baseline model's note F1 score of 93.43 % with a latency of 160 ms. This methodology has potential for training AMT models for various interactive scenarios, including providing real-time feedback for piano education.