• Journal of the Korea institute for structural maintenance and inspection
• /
• v.16 no.4
• /
• pp.107-115
• /
• 2012

The present study evaluates the validity of different equations specified in code provisions and proposed by the existing researchers to predict the concrete tensile capacities (direct tensile strength, splitting tensile strength and modulus of rupture) using a comprehensible database including 361 lightweight concrete (LWC), 1,335 normal-weight concrete (NWC) and 221 heavy-weight concrete (HWC) specimens. Most of the equations express the concrete tensile strengths as a function of its compressive strength based on the limited NWC concrete test data. However, the present database shows that the concrete tensile capacities are significantly affected by its unit weight as well. As a result, the inconsistency between experiments and predictions by the different models increases when the concrete unit weight is below 2,100 kg/$m^3$ and concrete compressive strength is above 50 MPa. On the other hand, new models proposed by the present study considering the concrete unit weight predict the tensile strengths of concrete with more accuracy.

• The Journal of the Institute of Internet, Broadcasting and Communication
• /
• v.20 no.4
• /
• pp.73-79
• /
• 2020

Due to the rapidly ageing population and low birth rates, most countries have faced with the problems of an ageing population. As a result, research into aging and the means to support an aging population has therefore become a priority for many governments around the world. Ambient Assisted Living(AAL) approach is the way to guarantee better life conditions for the aged and for monitoring their health conditions by the development of innovative technologies and services. AAL technologies can provide more safety for the elderly, offering emergency response mechanisms and fall detection solutions. Since the information transmitted in AAL systems is very personal, however, the security and privacy of such data are becoming important issues that must be dealt with. In this paper, we propose a Chameleon hash-based secure authentication protocol for AAL systems. The proposed authentication protocol not only supports several important security requirements needed by the AAL systems, but can also withstand various types of attacks. In addition, the security analysis results show that the proposed authentication protocol is more efficient and secure than the existing authentication protocols.

• Journal of the Korean Data and Information Science Society
• /
• v.22 no.4
• /
• pp.619-630
• /
• 2011

In order to estimate an appropriate threshold and evaluate its performance for the data mixed with two different distributions, nine kinds of well-known classification accuracy measures such as MVD, Youden's index, the closest-to- (0,1) criterion, the amended closest-to- (0,1) criterion, SSS, symmetry point, accuracy area, TA, TR are clustered into five categories on the basis of their characters. In credit evaluation study, it is assumed that the score random variable follows normal mixture distributions of the default and non-default states. For various normal mixtures, optimal cut-off points for classification measures belong to each category are obtained and type I and II error rates corresponding to these cut-off points are calculated. Then we explore the cases when these error rates are minimized. If normal mixtures might be estimated for these kinds of real data, we could make use of results of this study to select the best classification accuracy measure which has the minimum error rate.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
• /
• v.8 no.6
• /
• pp.483-490
• /
• 2015

There are many software reliability models that are based on the times of occurrences of errors in the debugging of software. It is shown that it is possible to do likelihood inference for software reliability models based on finite failure model and non-homogeneous Poisson Processes (NHPP). For someone making a decision about when to market software, the conditional failure rate is an important variables. The infinite failure model are used in a wide variety of practical situations. Their use in characterization problems, detection of outlier, linear estimation, study of system reliability, life-testing, survival analysis, data compression and many other fields can be seen from the many study. Statistical process control (SPC) can monitor the forecasting of software failure and thereby contribute significantly to the improvement of software reliability. Control charts are widely used for software process control in the software industry. In this paper, proposed a control mechanism based on NHPP using mean value function of Musa-Okumo and Power law type property.

• The Journal of Korean Institute of Communications and Information Sciences
• /
• v.40 no.10
• /
• pp.1958-1968
• /
• 2015

Things intelligence communication (M2M or IoT) service activation and global company of OneM2M-related business on aggressive investing and has led to the acceleration of change in the ICT market. But a variety of hacking security technology because of the possibility of secure communication (data exposure, theft, modification, deletion, etc.) has been issued as an important requirement. In this paper, we propose a mutual authentication protocol for secure communications chameleon hash based on the M2M environment. The results of performance analysis efficiency is encryption and decryption an average of 0.7%, calculated rate showed good results as compared to the target algorithm, equivalent to a 3%(Average 0.003 seconds) difference, mutual authentication and encryption region by using the key update advantage of ECC(Elliptic Curve Cryptography)based Chameleon hash function is signed of the operational efficiency, using a collision message verifiable properties demonstrated strong security of the communication section.

• The KIPS Transactions:PartD
• /
• v.19D no.1
• /
• pp.113-120
• /
• 2012

Today, Internet users can easily create and share the digital contents with others through various online content sharing services such as YouTube. So, many portal sites are flooded with lots of user created contents (UCC) in various media such as texts and videos. Estimating popularity of UCC is a crucial concern to both users and the site administrators. This paper proposes a method to predict the popularity of Internet articles, a kind of UCC, using the dynamics of the online contents themselves. To analyze the dynamics, we regarded the access counts of Internet posts as the popularity of them and analyzed the variation of the access counts. We derived a model to predict the popularity of a post represented by the time series of access counts, which is based on an exponential function. According to the experimental results, the difference between the actual access counts and the predicted ones is not more than 10 for 20,532 posts, which cover about 90.7% of the test set.

• Journal of the Korean Society of Safety
• /
• v.35 no.5
• /
• pp.15-21
• /
• 2020

Quantitative risk assessment (QRA) is used as a legal or voluntary safety management tool for the hazardous material industry and the utilization of the method is gradually increasing. Therefore, a leak frequency analysis based on reliable generic data is a critical element in the evolution of QRA and safety technologies. The aim of this paper is to derive the leak frequency function that can be applied more flexibly in QRA based on OGP report with high reliability and global utilization. For the purpose, we first reviewed the data on the 16 equipments included in the OGP report and selected the predictors. And then we found good equations to fit the OGP data using non-linear regression analysis. The various expectation functions were applied to search for suitable parameter to serve as a meaningful reference in the future. The results of this analysis show that the best fitting parameter is found in the form of DNV function and connection function in natural logarithm. In conclusion, the average percentage error between the fitted and the original value is very small as 3 %, so the derived prediction function can be applicable in the quantitative frequency analysis. This study is to contribute to expand the applicability of QRA and advance safety engineering as providing the generic equations for practical leak frequency analysis.

• Journal of the Korea institute for structural maintenance and inspection
• /
• v.20 no.4
• /
• pp.27-34
• /
• 2016

A new algorithm for determining optimal accelerometer locations is proposed by using a frequency-domain Hankel matrix which is much simpler to construct than a time-domain Hankel matrix. The algorithm was examined through simulation studies by comparing the outcomes with those from other available methods. To compare and analyze the results from different methods, a dynamic analysis was carried out under seismic excitation and acceleration data were obtained at the selected optimal sensor locations. Vibrational amplitudes at the selected sensor locations were determined and those of all the other degrees of freedom were determined by using a spline function. MAC index of each method was calculated and compared to look at which method could determine more effective locations of accelerometers. The proposed frequency-domain Hankel matrix could determine reasonable selection of accelerometer locations compared with the others.

• The Korean Journal of Applied Statistics
• /
• v.28 no.1
• /
• pp.83-92
• /
• 2015

Concerning the national health, it is important to develop an accurate prediction method of atmospheric particulate matter (PM) because being exposed to such fine dust can trigger not only respiratory diseases as well as dermatoses, ophthalmopathies and cardiovascular diseases. The National Institute of Environmental Research (NIER) employs a decision tree to predict bad weather days with a high PM concentration. However, the decision tree method (even with the inherent unstableness) cannot be a suitable model to predict bad weather days which represent only 4% of the entire data. In this paper, while presenting the inaccuracy and inappropriateness of the method used by the NIER, we present the utility of a new prediction model which adopts boosting with quantile loss functions. We evaluate the performance of the new method over various ${\tau}$-value's and justify the proposed method through comparison.

• Journal of KIISE
• /
• v.42 no.7
• /
• pp.852-859
• /
• 2015

As the amount of knowledge information significantly increases, a lot of progress has been made in the studies focusing on how to reason large scale ontology effectively at the level of RDFS or OWL. These reasoning methods are divided into TBox classifications and ABox realizations. A TBox classification mainly deals with integrity and dependencies in schema, whereas an ABox realization mainly handles a variety of issues in instances. Therefore, the ABox realization is very important in practical applications. In this paper, we propose a realization method for analyzing the constraint of the specified class, so that the reasoning system automatically infers the classes to which instances belong. Unlike conventional methods that take advantage of the object oriented language based distributed file system, we propose a large scale ontology reasoning method using spark, which is a functional programming-based in-memory system. To verify the effectiveness of the proposed method, we used instances created from the Wine ontology by W3C(120 to 600 million triples). The proposed system processed the largest 600 million triples and generated 951 million triples in 51 minutes (696 K triple / sec) in our largest experiment.