• Journal of Information Processing Systems
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• v.15 no.6
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• pp.1438-1448
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• 2019

We present a new technique, called VED (very effective debugging), for detecting and correcting division by zero errors for all types of .NET application. We use applications written in C# because C# applications are distributed through the internet and its executable format is used extensively. A tool called Immunity Debugger is used to reverse engineer executable code to get binaries of source code. With this technique, we demonstrate integer division by zero errors, the location of the error causing assembly language code, as well as error recovery done according to user preference. This technique can be extended to work for other programming languages in addition to C#. VED can work on different platforms such as Linux. This technique is simple to implement and economical because all the software used here are open source. Our aims are to simplify the maintenance process and to reduce the cost of the software development life cycle.

• Journal of Information Processing Systems
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• v.8 no.2
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• pp.279-300
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• 2012

Uncertainty and dynamism surrounding pervasive systems require new and sophisticated approaches to defining, detecting, and handling complex exceptions. This is because the possible erroneous conditions in pervasive systems are more complicated than conditions found in traditional applications. We devised a novel exception description and detection mechanism based on "situation"- a novel extension of context, which allows programmers to devise their own handling routines targeting sophisticated exceptions. This paper introduces the syntax of a language support that empowers the expressiveness of exceptions and their handlers, and suggests an implementation algorithm with a straw man analysis of overhead.

• The KIPS Transactions:PartC
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• v.12C no.3 s.99
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• pp.457-464
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• 2005

This paper describes an Adaptive Context-aware Service (ACS) using Model Driven Architecture (MDA)-based Service Creation Environment (SCE) on PARLAY X based service delivery platform in ubiquitous computing environments. It can be expected that both the context-awareness and adaptation in ubiquitous computing environments will be deployed. But the existing context-aware middleware lacks in considering adaptation. Therefore, the object of this paper is to support the architecture and the Application Programming Interface (API) of the network service for both the context-awareness and adaptation in ubiquitous computing environment. ACS is to provide users with the adaptive network service to the changing context constraints as well as detecting the changing context. For instance, ACS can provide users with QoS in network according to the detected context, after detecting the context such as location and speed. The architecture of ACS is comprised of a Service Creation Environment (SCE), Adaptive Context Broker and PARLAY gateway. SCE is to use Context-based Constraint Language (CCL) for an expression of context-awareness and adaptation. Adaptive Context Broker is to make a role of the broker between SCE and PARLAY G/W. PARLAY G/W is to support API for PARLAY X-based service delivery platform.

• Journal of KIISE:Software and Applications
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• v.32 no.4
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• pp.290-299
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• 2005

Stealing the source code of a program is a serious problem not only in a moral sense but also in a legal sense. However, it is not clear whether the code of a program is copied from another or not. There was a program similarity checker detecting code-copy by comparing the syntax trees of programs. However this method has a limitation that it cannot detect the code-copy attacks when the attacker modifies the syntax of the program on purpose. We propose a program similarity check by program control graph, which reveals not only syntax information but also control dependancy. Our method can detect the code-copy attacks that do not change control dependancy Moreover, we define what code-copy means and establish the connection between code-copy and similarity of program control graph: we prove that two programs are related by copy congruence if and only if the program control graphs of these programs are equivalent. We implemented our method on a functional programming language, nML. The experimental results show us that the suggested method can detect code similarity that is not detected by the existing method.

• The Journal of the Korea Contents Association
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• v.13 no.11
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• pp.37-47
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• 2013

Recently, lots of research results on program comparison have been reported since the code theft become frequent as the increase of code mobility. This paper proposes a plagiarism detection method using class structures. The proposed method constructs a graph representing the referential relationship between the member variables and the methods. This relationship is shown as a bipartite graph and the test for graph isomorphism is applied on the set of graphs to measure the similarity of the programs. In order to measure the effectiveness of this method, an experiment was conducted on the test set, the set of Java source codes submitted as solutions for the programming assignments in Object-Oriented Programming course of Pusan National University in 2012. In order to evaluate the accuracy of the proposed method, the F-measure is compared to those of JPlag and Stigmata. According to the experimental result, the F-measure of the proposed method is higher than those of JPlag and Stigmata by 0.17 and 0.34, respectively.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.39 no.9
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• pp.848-857
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• 2011

Vision-based collision avoidance system for air traffic management requires a excellent multiple target detection algorithm under low signal-to-noise ratio (SNR) levels. The track-before-detect (TBD) approaches have significant applications such as detection of small and dim targets from an image sequence. In this paper, two detection algorithms with the TBD approaches are proposed to satisfy the multiple target detection requirements. The first algorithm, based on a dynamic programming approach, is designed to classify multiple targets by using a k-means clustering algorithm. In the second approach, a hidden Markov model (HMM) is slightly modified for detecting multiple targets sequentially. Both of the proposed approaches are used in numerical simulations with variations in target appearance properties to provide satisfactory performance as multiple target detection methods.

• 제어로봇시스템학회:학술대회논문집
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• 2003.10a
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• pp.2588-2593
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• 2003

Any system has the possibility of an error occurrence. Even if trivial errors were occurred, the original system would be fatally affected by the occurring errors. Accordingly, the error detection must be demanded. In this paper, we developed a real-time error detection system would be able to apply to an electronic Jacquard system. A Jacquard is a machine, which controls warps while weaving textiles, for manufacturing patterned cloth. There are two types of mechanical and electronic Jacquard. An electronic Jacquard is better than a mechanical Jacquard in view of the productivity and realizability for weaving various cloths. Recent weaving industry is growing up increasingly due to the electronic Jacquard. But, the problem of wrong weaving from error data exists in the electronic Jacquard. In this research, a real-time error detection system for an electronic Jacquard is developed for detecting errors in an electronic Jacquard in real-time. The real-time system is constructed using PC-based embedded system architecture. The system detects the occurring errors in real-time by storing 1344 data transferred in serial from an electronic Jacquard into memory, and then by comparing synchronously 1344 data stored into memory with 1344 data in a design file before the next data would be transferred to the Jacquard for weaving. The information of detected errors are monitored to the screen and stored into a file in real-time as the outputs of the system. In this research, we solve the problem of wrong weaving through checking the weaving data and detecting the occurred errors of an electronic Jacquard in real-time.

• Journal of the Korea Society of Computer and Information
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• v.10 no.6 s.38
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• pp.219-226
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• 2005

This paper describes the open API with integration of semantic web service with PARLAY X based open API in 4G mobile network. It can be expected that the intelligence such as the context-awareness, adaptation and personalization in 4G mobile network will be deployed. But the existing PARLAY based network lacks in considering context-awareness, adaptation and personalization. Therefore, the object of this paper is to support the architecture and the Application Programming Interface (API) of the network service for the context-awareness, adaptation and Personalization in 4G mobile network The open API is to provide users with the adaptive network service to the changing context constraints as well as detecting the changing context and user's Preference. For instance, the open API can Provide users with QoS in network according to the detected context and user's preference, after detecting the context such as location and speed and user's preference.

• The korean journal of orthodontics
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• v.52 no.2
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• pp.112-122
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• 2022

Objective: This study aimed to present and evaluate a new deep learning model for determining cervical vertebral maturation (CVM) degree and growth spurts by analyzing lateral cephalometric radiographs. Methods: The study sample included 890 cephalograms. The images were classified into six cervical stages independently by two orthodontists. The images were also categorized into three degrees on the basis of the growth spurt: pre-pubertal, growth spurt, and post-pubertal. Subsequently, the samples were fed to a transfer learning model implemented using the Python programming language and PyTorch library. In the last step, the test set of cephalograms was randomly coded and provided to two new orthodontists in order to compare their diagnosis to the artificial intelligence (AI) model's performance using weighted kappa and Cohen's kappa statistical analyses. Results: The model's validation and test accuracy for the six-class CVM diagnosis were 62.63% and 61.62%, respectively. Moreover, the model's validation and test accuracy for the three-class classification were 75.76% and 82.83%, respectively. Furthermore, substantial agreements were observed between the two orthodontists as well as one of them and the AI model. Conclusions: The newly developed AI model had reasonable accuracy in detecting the CVM stage and high reliability in detecting the pubertal stage. However, its accuracy was still less than that of human observers. With further improvements in data quality, this model should be able to provide practical assistance to practicing dentists in the future.

• 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.