• Journal of Korea Multimedia Society
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• v.8 no.11
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• pp.1496-1509
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• 2005

In this paper, an adaptive license plate recognition system which detects and recognizes license plate at real-time by using projected plane convolution and Decision Tree Classifier is proposed. And it was tested in circumstances which presence of complex background. Generally, in expressway tollgate or gateway of parking lots, it is very difficult to detect and segment license plate because of size, entry angle and noisy problem of vehicles due to CCD camera and road environment. In the proposed algorithm, we suggested to extract license plate candidate region after going through image acquisition process with inputted real-time image, and then to compensate license size as well as gradient of vehicle with change of vehicle entry position. The proposed algorithm can exactly detect license plate using accumulated edge, projected convolution and chain code labeling method. And it also segments letter of license plate using adaptive binary method. And then, it recognizes license plate letter by applying hybrid pattern vector method. Experimental results show that the proposed algorithm can recognize the front and rear direction license plate at real-time in the presence of complex background environments. Accordingly license plate detection rate displayed $98.8\%$ and $96.5\%$ successive rate respectively. And also, from the segmented letters, it shows $97.3\%$ and $96\%$ successive recognition rate respectively.

• The KIPS Transactions:PartD
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• v.12D no.3 s.99
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• pp.461-470
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• 2005

This paper suggests a new policy for consolidating a company's profits by segregating the clients using the contents service and allocating the media server's resources distinctively by clusters using the cluster analysis method of CRM, which is mainly applied to marketing. In this case, CRM refers to the strategy of consolidating a company's profits by efficiently managing the clients, providing them with a more effective, personalized service, and managing the resources more effectively. For the realization of a new service policy, this paper analyzes the level of contribution $vis-\acute{a}-vis$ the clients' service pattern (total number of visits to the homepage, service type, service usage period, total payment, average service period, service charge per homepage visit) and profits through the cluster analysis of clients' data applying the K-Means Method. Clients were grouped into 4 clusters according to the contribution level in terms of profits. Likewise, the CRFA (Client Request Filtering algorithm) was suggested per cluster to allocate media server resources. CRFA issues approval within the resource limit of the cluster where the client belongs. In addition, to evaluate the efficiency of CRFA within the Client/Server environment the acceptance rate per class was determined, and an evaluation experiment on network traffic was conducted before and after applying CRFA. The results of the experiments showed that the application of CRFA led to the decrease in network expenses and growth of the acceptance rate of clients belonging to the cluster as well as the significant increase in the profits of the company.

• The KIPS Transactions:PartD
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• v.11D no.5
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• pp.1049-1062
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• 2004

With the popularization of a World Wide Web (WWW), the quantity of web information has been increased. Therefore, an efficient searching system is needed to offer the exact result of diverse Information to user. Due to this reason, it is important to extract and analysis of user requirements in the distributed information environment. The conventional searching method used the only keyword for the web searching. However, the searching method proposed in this paper adds the context information of keyword for the effective searching. In addition, this searching method extracts keywords by the new keyword extraction method proposed in this paper and it executes the web searching based on a keyword mining profile generated by the extracted keywords. Unlike the conventional searching method which searched for information by a representative word, this searching method proposed in this paper is much more efficient and exact. This is because this searching method proposed in this paper is searched by the example based query included content information as well as a representative word. Moreover, this searching method makes a domain keyword list in order to perform search quietly. The domain keyword is a representative word of a special domain. The performance of the proposed algorithm is analyzed by a series of experiments to identify its various characteristic.

• Journal of KIISE:Software and Applications
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• v.36 no.4
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• pp.261-272
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• 2009

The EJB 3.0 specifications, which were improved in terms of performance and ease of development, were recently announced. Accordingly, for the EJB 3.0 application environment, developers generally prefer the gradual transformation of components whose performance must be improved to the complete transformation of all the EJB 2.1 components into EJB 3.0 components. Previous studies, however, did not consider the service of the application and did not ensure the compatibility and reusability of the components in the full replacement of EJB 3.0 due to the transformation using different specifications. This study proposed three transformation techniques that consider the service supported in the existing application, wherein the compatibility and reusability of the components are ensured in the case of the full replacement of EJB 3.0. The proposed transformation techniques are techniques for gradual transformation, such as direct transformation that directly connects components, indirect transformation that uses the EJB connector, and indirect template transformation wherein the template pattern is applied to the indirect transformation. The proposed transformation techniques were verified by comparing the reusability and processing capability of the components per second, and the standards for selecting a technique were provided based on the characteristics of the transformation into EJB 3.0 that were found in this study.

• The KIPS Transactions:PartD
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• v.19D no.2
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• pp.187-202
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• 2012

As a representative reuse paradigm, the theme of service-oriented Paradigm (SOC) is largely centered on publishing and subscribing reusable services. Here, SOC is the term including service oriented architecture and cloud computing. Service providers can produce high profits with reusable services, and service consumers can develop their applications with less time and effort by reusing the services. Design Patterns (DP) is a set of reusable methods to resolve commonly occurring design problems and to provide design structures to deal with the problems by following open/close princples. However, since DPs are mainly proposed for building object-oriented systems and there are distinguishable differences between object-oriented paradigm and SOC, it is challenging to apply the DPs to SOC design problems. Hence, DPs need to be customized by considering the two aspects; for service providers to design services which are highly reusable and reflect their unique characteristics and for service consumers to develop their target applications by reusing and customizing services as soon as possible. Therefore, we propose a set of DPs that are customized to SOC. With the proposed DPs, we believe that service provider can effectively develop highly reusable services, and service consumers can efficiently adapt services for their applications.

• The KIPS Transactions:PartA
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• v.16A no.6
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• pp.453-462
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• 2009

Studies on software plagiarism detection, prevention and judgement have become widespread due to the growing of interest and importance for the protection and authentication of software intellectual property. Many previous studies focused on comparing all pairs of submitted codes by using attribute counting, token pattern, program parse tree, and similarity measuring algorithm. It is important to provide a clear-cut model for distinguishing plagiarism and collaboration. This paper proposes a source code clustering algorithm using a probability model on extreme value distribution. First, we propose an asymmetric distance measure pdist($P_a$, $P_b$) to measure the similarity of $P_a$ and $P_b$ Then, we construct the Plagiarism Direction Graph (PDG) for a given program set using pdist($P_a$, $P_b$) as edge weights. And, we transform the PDG into a Gumbel Distance Graph (GDG) model, since we found that the pdist($P_a$, $P_b$) score distribution is similar to a well-known Gumbel distribution. Second, we newly define pseudo-plagiarism which is a sort of virtual plagiarism forced by a very strong functional requirement in the specification. We conducted experiments with 18 groups of programs (more than 700 source codes) collected from the ICPC (International Collegiate Programming Contest) and KOI (Korean Olympiad for Informatics) programming contests. The experiments showed that most plagiarized codes could be detected with high sensitivity and that our algorithm successfully separated real plagiarism from pseudo plagiarism.

• The KIPS Transactions:PartA
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• v.16A no.3
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• pp.209-216
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• 2009

The ubiquitous smart home is the home of the future that takes advantage of context information from the human and the home environment and provides an automatic home service for the human. Human location and motion are the most important contexts in the ubiquitous smart home. We present a real-time human tracker that predicts human location and motion for the ubiquitous smart home. We used four network cameras for real-time human tracking. This paper explains the real-time human tracker's architecture, and presents an algorithm with the details of two functions (prediction of human location and motion) in the real-time human tracker. The human location uses three kinds of background images (IMAGE1: empty room image, IMAGE2: image with furniture and home appliances in the home, IMAGE3: image with IMAGE2 and the human). The real-time human tracker decides whether the human is included with which furniture (or home appliance) through an analysis of three images, and predicts human motion using a support vector machine. A performance experiment of the human's location, which uses three images, took an average of 0.037 seconds. The SVM's feature of human's motion recognition is decided from pixel number by array line of the moving object. We evaluated each motion 1000 times. The average accuracy of all the motions was found to be 86.5%.

• KIPS Transactions on Software and Data Engineering
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• v.6 no.9
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• pp.419-428
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• 2017

In an embedded system, modules exchange data by interacting among themselves. Exchanging erroneous resource data among modules may lead to execution errors. The interacting resources produce dependencies between the two modules where any change of the resources by one module affects the functionality of another module. Several investigations of the embedded systems show that interaction faults between the modules are one of the major cause of critical software failure. Therefore, interaction testing is an essential phase for reducing the interaction faults and minimizing the risk. The direct and indirect interactions between the modules generate interaction faults. The direct interaction is the explicit call relation between the modules, and the indirect interaction is the remaining relation that is made underneath the interface that possesses data dependence relationship with resources. In this paper, we investigate the errors that are based on the indirect interaction between modules and introduce a new test criterion for identifying the errors that are undetectable by existing approaches at the integration level. We propose a novel approach for generating the interaction model using the indirect interaction pattern and design test criteria that are based on different interaction errors to generate test cases. Finally, we use the fault injection technique to evaluate the feasibility and effectiveness of our approach.

• KIPS Transactions on Computer and Communication Systems
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• v.6 no.4
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• pp.189-196
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• 2017

BIS(Bus Information System) provides the different information related to buses including predictions of arriving times at stations. BIS have been deployed almost all cities in our country and played active roles to improve the convenience of public transportation systems. Moving average filters, Kalman filter and regression models have been representative in forecasting the arriving times of buses in current BIS. The accuracy in prediction of arriving times depends largely on the forecasting algorithms and traffic conditions considered when forecasting in BIS. In present BIS, the simple prediction algorithms are used only considering the passage times and distances between stations. The forecasting of arrivals, however, have been influenced by the traffic conditions such as traffic signals, traffic accidents and pedestrians ets., and missing data. To improve the accuracy of bus arriving estimates, there are big troubles in building models including the above problems. Hidden Markov Models have been effective algorithms considering various restrictions above. So, we have built the HMM forecasting models for bus arriving times in the current BIS. When building models, the data collected from Sunchean City at 2015 have been utilized. There are about 2298 stations and 217 routes in Suncheon city. The models are developed differently week days and weekend. And then the models are conformed with the data from different districts and times. We find that our HMM models can provide more accurate forecasting than other existing methods like moving average filters, Kalmam filters, or regression models. In this paper, we propose Hidden Markov Model to obtain more precise and accurate model better than Moving Average Filter, Kalman Filter and regression model. With the help of Hidden Markov Model, two different sections were used to find the pattern and verified using Bootstrap process.

• KIPS Transactions on Software and Data Engineering
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• v.8 no.12
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• pp.507-516
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• 2019

Costs invested in road maintenance and road development are on the rise. However, due to accidents such as portholes and ground subsidence, the risks to the drivers' safety and the material damage caused by accidents are also increasing. Following this trend, we have developed a system that determines road damage, according to the magnitude of vibration generated without directly intervening the driver when driving. In this paper, we implemented the system using a remote control car (RC car) simulator due to the limitation of the environment in which the actual vehicle is not available in the process of developing the system. In addition, we attached a vibration sensor and GPS sensor to the body of the RC car simulator to measure the vibration value and location information generated by the movement of the vehicle in real-time while driving, and transmitting the corresponding data to the server. In this way, we implemented a system that allows external users to check the damage of roads and the maintenance of the repaired roads based on data more easily than the existing systems. By using this system, we can perform early prediction of road breakage and pattern prediction based on the data. Further, for the RC car simulator, commercialization will be possible by combining it with business in other fields that require flatness.