• The KIPS Transactions:PartC
• /
• v.13C no.4 s.107
• /
• pp.397-404
• /
• 2006

Successful software attacks require both injecting malicious code into a program's address space and altering the program's flow control to the injected code. Code section can not be changed at program's runtime, so malicious code must be injected into data section. Detoured flow control into data section is a signal of software attack. We propose a new software attack detection method which verify the target address of CALL, JMP, RET instructions, which alter program's flow control, and detect a software attack when the address is not in code section. Proposed method can detect all change of flow control related data, not only program's return address but also function pointer, buffer of longjmp() function and old base pointer, so it can detect the more attacks.

• Journal of Korea Multimedia Society
• /
• v.9 no.2
• /
• pp.255-263
• /
• 2006

It is common that a junk mail has an inconsistency of mail addresses between those of the mail headers and the mail recipients. In addition, users easily know that an email is a junk or legitimate mail only by looking for the title of the email. In this paper, we tried to apply the filtering classifiers of mail address validation check and the combination method of title-content weighting to improve the performance of junk mail filtering system. In order to verify the effectiveness of the proposed method, we performed an experiment by applying them to Naive Bayesian classifier. The experiment includes the unit testing and the combination of the filtering techniques. As a result, we found that our method improved 11.6% of recall and 2.1% of precision that it contributed the enhancement of the junk mail filtering system.

• Coupled systems mechanics
• /
• v.4 no.1
• /
• pp.37-65
• /
• 2015

Modeling and simulation of mechanical response of infrastructure object, solids and structures, relies on the use of computational models to foretell the state of a physical system under conditions for which such computational model has not been validated. Verification and Validation (V&V) procedures are the primary means of assessing accuracy, building confidence and credibility in modeling and computational simulations of behavior of those infrastructure objects. Validation is the process of determining a degree to which a model is an accurate representation of the real world from the perspective of the intended uses of the model. It is mainly a physics issue and provides evidence that the correct model is solved (Oberkampf et al. 2002). Our primary interest is in modeling and simulating behavior of porous particulate media that is fully saturated with pore fluid, including cyclic mobility and liquefaction. Fully saturated soils undergoing dynamic shaking fall in this category. Verification modeling and simulation of fully saturated porous soils is addressed in more detail by (Tasiopoulou et al. 2014), and in this paper we address validation. A set of centrifuge experiments is used for this purpose. Discussion is provided assessing the effects of scaling laws on centrifuge experiments and their influence on the validation. Available validation test are reviewed in view of first and second order phenomena and their importance to validation. For example, dynamics behavior of the system, following the dynamic time, and dissipation of the pore fluid pressures, following diffusion time, are not happening in the same time scale and those discrepancies are discussed. Laboratory tests, performed on soil that is used in centrifuge experiments, were used to calibrate material models that are then used in a validation process. Number of physical and numerical examples are used for validation and to illustrate presented discussion. In particular, it is shown that for the most part, numerical prediction of behavior, using laboratory test data to calibrate soil material model, prior to centrifuge experiments, can be validated using scaled tests. There are, of course, discrepancies, sources of which are analyzed and discussed.

• Journal of Information Processing Systems
• /
• v.14 no.5
• /
• pp.1075-1086
• /
• 2018

In this paper a cross-validation algorithm for training probabilistic neural networks (PNNs) is presented in order to be applied to automatic face identification. Actually, standard PNNs perform pretty well for small and medium sized databases but they suffer from serious problems when it comes to using them with large databases like those encountered in biometrics applications. To address this issue, we proposed in this work a new training algorithm for PNNs to reduce the hidden layer's size and avoid over-fitting at the same time. The proposed training algorithm generates networks with a smaller hidden layer which contains only representative examples in the training data set. Moreover, adding new classes or samples after training does not require retraining, which is one of the main characteristics of this solution. Results presented in this work show a great improvement both in the processing speed and generalization of the proposed classifier. This improvement is mainly caused by reducing significantly the size of the hidden layer.

• Journal of Advanced Information Technology and Convergence
• /
• v.9 no.2
• /
• pp.15-27
• /
• 2019

This paper deals with a web-based public address system for conveying information for different institutions. An architecture for a Short Messaging Service (SMS) based public address (PA) system that can be programmed by an authorized mobile phone or device is proposed. This PA system will facilitate information transfer from heads of offices, managers, directors, and deans of the institutions to its constituents or unit area as well as enable postings of information with proper authentication and validation remotely. The system supports high priority messaging, allowing the conveyance of critical and time sensitive information. The mobility management support for the PA system will be based on the Hierarchical Mobile Internet Protocol version 6 (HMIPv6), hence, allowing for a seamless connectivity to the system. The major advantage of this proposed PA system as compared with the traditional electronic displays and bulletin boards is seamless mobility wherein the display devices can be programmed remotely by heads of the institutions and business organization. It also allows faster communication and immediate actions concerning the different institutions, organizations, and businesses, thus, ensuring high productivity.

• Journal of Internet Computing and Services
• /
• v.22 no.1
• /
• pp.31-39
• /
• 2021

Obtaining delivery addresses from calls is one of the most important processes in TV home shopping business. By automating this process, the operational efficiency of TV home shopping can be increased. In this paper, a method of recognizing and validating road name address, which is the address system of South Korea, from speech oriented text is proposed. The speech oriented text has three challenges. The first is that the numbers are represented in the form of pronunciation. The second is that the recorded address has noises that are made from repeated pronunciation of the same address, or unordered address. The third is that the readability of the resulted address. For resolving these problems, the proposed method enhances the existing address databases provided by the Korea Post and Ministry of the Interior and Safety. Various types of pronouncing address are added, and heuristic rules for dividing ambiguous pronunciations are employed. And the processed address is validated by checking the existence in the official address database. Even though, this proposed method is for the STT result of the address pronunciation, this also can be used for any 3^rd party services that need to validate road name address. The proposed method works robustly on noises such as positions change or omission of elements.

• Journal of the Korea Society of Computer and Information
• /
• v.20 no.6
• /
• pp.151-159
• /
• 2015

In traditional programing education, computers were used as the main tool. Consequently, it was problematic to provide education in an environment without computers or for learners without computer skills. To address this problem, this study developed and validated an unplugged robot education system capable of computerless programming education. The key feature of the proposed system is that programing can be done only by connecting programming blocks in symbols of a flow chart with built-in commands. Validation of the system was performed by a specialist group. Validity was very high with values of content validity ratio (CVR) over 0.7 in all evaluation criteria except "Ease of error debugging" and "Linkages to educational curriculum," whose CVR values were each 0.6. Future directions include improvement in the two areas that scored lower than the others did by, respectively, system improvement to support debugging in error conditions that may occur during the programming process, and development of user guide to support linkages to educational curriculum.

• Journal of the Korean Data and Information Science Society
• /
• v.28 no.2
• /
• pp.461-471
• /
• 2017

In this paper we propose a feature selection method identifying important features in the semivarying coefficient model. One important issue in semivarying coefficient model is how to estimate the parametric and nonparametric components. Another issue is how to identify important features in the varying and the constant effects. We propose a feature selection method able to address this issue using generalized cross validation functions of the varying coefficient least squares support vector regression (LS-SVR) and the linear LS-SVR. Numerical studies indicate that the proposed method is quite effective in identifying important features in the varying and the constant effects in the semivarying coefficient model.

• Nuclear Engineering and Technology
• /
• v.49 no.6
• /
• pp.1358-1367
• /
• 2017

The data integration with modeled predictions (DIMP) model is a promising inverse radiation transport method for solving the special nuclear material (SNM) holdup problem. Unlike previous methods, DIMP is a completely passive nondestructive assay technique that requires no initial assumptions regarding the source distribution or active measurement time. DIMP predicts the most probable source location and distribution through Bayesian inference and quasi-Newtonian optimization of predicted detector responses (using the adjoint transport solution) with measured responses. DIMP performs well with forward hemispherical collimation and unshielded measurements, but several considerations are required when using narrow-view collimated detectors. DIMP converged well to the correct source distribution as the number of synthetic responses increased. DIMP also performed well for the first experimental validation exercise after applying a collimation factor, and sufficiently reducing the source search volume's extent to prevent the optimizer from getting stuck in local minima. DIMP's simple point detector response function (DRF) is being improved to address coplanar false positive/negative responses, and an angular DRF is being considered for integration with the next version of DIMP to account for highly collimated responses. Overall, DIMP shows promise for solving the SNM holdup inverse problem, especially once an improved optimization algorithm is implemented.

• Korean Journal of Radiology
• /
• v.22 no.3
• /
• pp.442-453
• /
• 2021

Artificial intelligence (AI) will likely affect various fields of medicine. This article aims to explain the fundamental principles of clinical validation, device approval, and insurance coverage decisions of AI algorithms for medical diagnosis and prediction. Discrimination accuracy of AI algorithms is often evaluated with the Dice similarity coefficient, sensitivity, specificity, and traditional or free-response receiver operating characteristic curves. Calibration accuracy should also be assessed, especially for algorithms that provide probabilities to users. As current AI algorithms have limited generalizability to real-world practice, clinical validation of AI should put it to proper external testing and assisting roles. External testing could adopt diagnostic case-control or diagnostic cohort designs. A diagnostic case-control study evaluates the technical validity/accuracy of AI while the latter tests the clinical validity/accuracy of AI in samples representing target patients in real-world clinical scenarios. Ultimate clinical validation of AI requires evaluations of its impact on patient outcomes, referred to as clinical utility, and for which randomized clinical trials are ideal. Device approval of AI is typically granted with proof of technical validity/accuracy and thus does not intend to directly indicate if AI is beneficial for patient care or if it improves patient outcomes. Neither can it categorically address the issue of limited generalizability of AI. After achieving device approval, it is up to medical professionals to determine if the approved AI algorithms are beneficial for real-world patient care. Insurance coverage decisions generally require a demonstration of clinical utility that the use of AI has improved patient outcomes.