• Information Systems Review
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• v.5 no.2
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• pp.203-217
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• 2003

Constraint Programming and Optimization have developed in different fields to solve common problems in real world. In particular, constraint propagation and linear Programming are their own fundamental and complementary techniques with the potential for integration to benefit each other. This intersection has evoked the efforts to combine both for a solution method to combinatorial optimization problems. Attempts to combine them have mainly focused on incorporating either technique into the framework of the other with traditional models left intact. This paper argues that integrating both techniques into an old modeling fame loses advantages from another and the integration should be molded in a new framework to be able to exploit advantages from both. The paper propose a declarative modeling framework in which the structure of the constraints indicates how constraint programming and optimization solvers can interact to solve problems.

• Proceedings of the Korea Information Processing Society Conference
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• 2014.04a
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• pp.904-907
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• 2014

In this work we present a robust and fast approach to estimate 3D vehicle pose that can provide results under a specific traffic surveillance conditions. Such limitations are expressed by single fixed CCTV camera that is located relatively high above the ground, its pitch axes is parallel to the reference plane and the camera focus assumed to be known. The benefit of our framework that it does not require prior training, camera calibration and does not heavily rely on 3D model shape as most common technics do. Also it deals with a bad shape condition of the objects as we focused on low resolution surveillance scenes. Pose estimation task is presented as PnP problem to solve it we use well known "POSIT" algorithm [1]. In order to use this algorithm at least 4 non coplanar point's correspondence is required. To find such we propose a set of techniques based on model and scene geometry. Our framework can be applied in real time video sequence. Results for estimated vehicle pose are shown in real image scene.

• Journal of Korea Multimedia Society
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• v.22 no.1
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• pp.1-9
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• 2019

Single image rain removal is a typical inverse problem which decomposes the image into a background scene and a rain streak. Recent works have witnessed a substantial progress on the task due to the development of convolutional neural network (CNN). However, existing CNN-based approaches train the network with synthetically generated training examples. These data tend to make the network bias to the synthetic scenes. In this paper, we present an unsupervised framework for removing rain streaks from real-world rainy images. We focus on the natural phenomena that static rainy scenes capture a common background but different rain streak. From this observation, we train siamese network with the real rain image pairs, which outputs identical backgrounds from the pairs. To train our network, a real rainy dataset is constructed via web-crawling. We show that our unsupervised framework outperforms the recent CNN-based approaches, which are trained by supervised manner. Experimental results demonstrate that the effectiveness of our framework on both synthetic and real-world datasets, showing improved performance over previous approaches.

• International Journal of Computer Science & Network Security
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• v.22 no.11
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• pp.121-126
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• 2022

The number of vehicles has increased exponentially over the past 20 years due to technological advancements. It is becoming almost impossible to manually control and manage the traffic in a city like Karachi. Without license plate recognition, traffic management is impossible. The Framework for License Plate Detection & Recognition to overcome these issues is proposed. License Plate Detection & Recognition is primarily performed in two steps. The first step is to accurately detect the license plate in the given image, and the second step is to successfully read and recognize each character of that license plate. Some of the most common algorithms used in the past are based on colour, texture, edge-detection and template matching. Nowadays, many researchers are proposing methods based on deep learning. This research proposes a framework for License Plate Detection & Recognition using a custom YOLOv5 Object Detector, image segmentation techniques, and Tesseract's optical character recognition OCR. The accuracy of this framework is 0.89.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2022.05a
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• pp.203-205
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• 2022

As digital transformation and remote work environment advanced by Covid-19 become more common, the scale of leakage damage to industrial secrets and personal information caused by information leakage attacks is increasing. Recently, advanced and persistent information leakage attacks have become a serious security threat because they do not quickly leak large amounts of information, but continuously leak small amounts of information over a long period of time. In this study, we propose a framework for detecting advanced and persistent information leakage attacks based on traffic characteristics. The proposed method can effectively detect advanced and persistent information leakage attacks using traffic patterns, packet sizes, and metadata, even if the payload is encrypted.

• KIPS Transactions on Computer and Communication Systems
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• v.12 no.11
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• pp.329-336
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• 2023

This paper analyzes the Personal Information Protection Act and related legal guides revised in 2023, proposes a framework for a consignment contract through the items necessary in the consignment relationship for personal information work, and inspects the status of personal information protection for consignees that are absent in Korea. By proposing common items that must be included, we prevent the occurrence of personal information leakage incidents by strengthening the basic personal information protection capabilities of trustees handling personal information work and alleviating the burden of essential personal information protection inspections. I want to do it.

• Journal of the Korean Society of Industry Convergence
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• v.27 no.2_2
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• pp.445-456
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• 2024

This study aims to suggest service improvement opportunities by analyzing user review data of the top three OTT service apps(Netflix, Coupang Play, and TVING) on Google Play Store. To achieve this objective, we proposed a framework for uncovering service opportunities through the analysis of negative user reviews from OTT service providers. The framework involves automating the labeling of identified topics and generating service improvement opportunities using topic modeling and prompt engineering, leveraging GPT-4, a generative AI model. Consequently, we pinpointed five dissatisfaction topics for Netflix and TVING, and nine for Coupang Play. Common issues include "video playback errors", "app installation and update errors", "subscription and payment" problems, and concerns regarding "content quality". The commonly identified service enhancement opportunities include "enhancing and diversifying content quality". "optimizing video quality and data usage", "ensuring compatibility with external devices", and "streamlining payment and cancellation processes". In contrast to prior research, this study introduces a novel research framework leveraging generative AI to label topics and propose improvement strategies based on the derived topics. This is noteworthy as it identifies actionable service opportunities aimed at enhancing service competitiveness and satisfaction, instead of merely outlining topics.

• ETRI Journal
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• v.31 no.5
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• pp.554-564
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• 2009

In information security and network management, attacks based on vulnerabilities have grown in importance. Malicious attackers break into hosts using a variety of techniques. The most common method is to exploit known vulnerabilities. Although patches have long been available for vulnerabilities, system administrators have generally been reluctant to patch their hosts immediately because they perceive the patches to be annoying and complex. To solve these problems, we propose a security vulnerability evaluation and patch framework called PKG-VUL, which evaluates the software installed on hosts to decide whether the hosts are vulnerable and then applies patches to vulnerable hosts. All these operations are accomplished by the widely used simple network management protocol (SNMP). Therefore, system administrators can easily manage their vulnerable hosts through PKG-VUL included in the SNMP-based network management systems as a module. The evaluation results demonstrate the applicability of PKG-VUL and its performance in terms of devised criteria.

• Journal of Institute of Control, Robotics and Systems
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• v.10 no.12
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• pp.1233-1240
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• 2004

Recently the need for cooperative control among robots is increasing in a variety of industrial robot applications. Such a control framework enhances the efficiency of the real robotic assembly environment along with extending the robot application. In this paper, an ethernet-based cooperative control framework was proposed. The cooperative control of robots can multiply the handling capacity of robot system, and make it possible to implement jigless cooperation, due to realization of trajectory-synchronized movement between a master robot and slave robots. Coordinate transformation was used to relate among robots in a common coordinate. An optimized ethernet protocol of HiNet was developed to maximize the speed of communication and to minimize the error of synchronous movement. The proposed algorithm and optimization of network protocol was tested in several class of robots.

• Electronics and Telecommunications Trends
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• v.33 no.1
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• pp.111-122
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• 2018

In this review, several new technologies considered when providing an open service environment in a mobile communication network are described. Recently, 3GPP developed some standards related to IoT services for opening a service platform in an SCS environment based on the OSA concept in a 3GPP LTE system. Similarly, the development of a new framework is underway to allow a plurality of services to commonly use an API environment in which a service provider or client accesses a 5G mobile communication system. Extending the existing LTE SCEF concept, the standardization of the northbound API is applied in the 5G CAPIF environment. Therefore, it is possible to construct a framework that facilitates access from outside, and takes advantage of the common management of various open service environments. An open service platform environment is expected to play an important role in transforming a network with simple connectivity services into a variety of new service markets, or into a service environment that can create added value.