• The Transactions of the Korea Information Processing Society
• /
• v.2 no.2
• /
• pp.185-198
• /
• 1995

The development of automated quality evaluation tool is desperately needed to decrease the cost of maintenance, to measure quality of source program in developing course for the purpose of developing high quality software. Main goal in this paper is to develop the automated tool for software quality evaluation related with high quality and high reliability of software. In this paper, we proposed the four software quality model to evaluate software quality; functional -size model, understandability model, complexity model and object-oriented model. Also, we made a scanner and a parser to analyze the c and C＋＋ source program and to produce the metrics and function value. The measurement value is statistically analyzed for the distribution of the measurement value. we can extracted the characteristics of measurement value and this one is assisted to make scores of software quality evaluation. Finally, we made a software quality evaluation tool to support software evaluation activities.

• The Journal of Korean Institute of Communications and Information Sciences
• /
• v.32 no.11A
• /
• pp.1197-1205
• /
• 2007

An adaptive K-best detection scheme is proposed for MIMO systems. The proposed scheme changes the number of survivor paths, K based on the degree of the reliability of Zero-Forcing (ZF) estimates at each K-best step. The critical drawback of the fixed K-best detection is that the correct path's metric may be temporarily larger than K minimum paths metrics due to imperfect interference cancellation by the incorrect ZF estimates. Based on the observation that there are insignificant differences among path metrics (ML distances) when the ZF estimates are incorrect, we use the ratio of the minimum ML distance to the second minimum as a reliability indicator for the ZF estimates. So, we adaptively select the value of K according to the ML distance ratio. It is shown that the proposed scheme achieves the significant improvement over the conventional fixed K-best scheme. The proposed scheme effectively achieves the performance of large K-best system while maintaining the overall average computation complexity much smaller than that of large K system.

• Nuclear Engineering and Technology
• /
• v.56 no.7
• /
• pp.2756-2766
• /
• 2024

Small rod-controlled pressurized water reactors (PWR) are the ideal energy source for vessel propulsion, benefiting from their high reactivity control efficiency. Since the control rods (CRs) increase the complexity of reactivity control, this paper seeks to study the performance of CRs in small rod-controlled PWRs to extend the lifetime and reduce power offset due to CRs. This study investigates CR grouping, move-in/out strategies, and axially non-uniform design effects on core neutron physics metrics. These metrics include axial offset (AO), core lifetime (CL), fuel utilization (FU), and radial power peaking factor (R-PPF). To simulate the movement of the CRs, a "Critical-CR-burnup" function was developed in OpenMC. In CR designs, the CRs are grouped into three banks to study the simultaneous and prioritized move-in/out strategies. The results show CL extension from 590 effective full power days (EFPDs) to 638-698 EFPDs. A lower-worth prioritized strategy minimizes AO and the extremum values decrease from -0.69 and + 0.81 to -0.28 and + 0.51. Although an axially non-uniform CR design can improve AO at the beginning of cycle (BOC), considering the overall CR worth change is crucial, as a significant decrease can adversely impact axial power distribution during the middle of cycle (MOC).

• KIPS Transactions on Software and Data Engineering
• /
• v.12 no.5
• /
• pp.199-206
• /
• 2023

The current software becomes the huge size of source codes. Therefore it is increasing the importance and necessity of static analysis for high-quality product. With static analysis of the code, it needs to identify the defect and complexity of the code. Through visualizing these problems, we make it guild for developers and stakeholders to understand these problems in the source codes. Our previous visualization research focused only on the process of storing information of the results of static analysis into the Database tables, querying the calculations for quality indicators (CK Metrics, Coupling, Number of function calls, Bad-smell), and then finally visualizing the extracted information. This approach has some limitations in that it takes a lot of time and space to analyze a code using information extracted from it through static analysis. That is since the tables are not normalized, it may occur to spend space and time when the tables(classes, functions, attributes, Etc.) are joined to extract information inside the code. To solve these problems, we propose a regularized design of the database tables, an extraction mechanism for quality metric indicators inside the code, and then a visualization with the extracted quality indicators on the code. Through this mechanism, we expect that the code visualization process will be optimized and that developers will be able to guide the modules that need refactoring. In the future, we will conduct learning of some parts of this process.

• Journal of Communications and Networks
• /
• v.14 no.4
• /
• pp.451-460
• /
• 2012

Natural disasters often lead to regional failures that can cause network nodes and links co-located in a large geographical area to fail. Novel approaches are required to assess the network vulnerability under such regional failures. In this paper, we investigate the vulnerability of networks by considering the geometric properties of regional failures and network nodes. To evaluate the criticality of node locations and determine the critical areas in a network, we propose the concept of ${\alpha}$-critical-distance with a given failure impact ratio ${\alpha}$, and we formulate two optimization problems based on the concept. By analyzing the geometric properties of the problems, we show that although finding critical nodes or links in a pure graph is a NP-complete problem, the problem of finding critical areas has polynomial time complexity. We propose two algorithms to deal with these problems and analyze their time complexities. Using real city-level Internet topology data, we conducted experiments to compute the ${\alpha}$-critical-distances for different networks. The computational results demonstrate the differences in vulnerability of different networks. The results also indicate that the critical area of a network can be estimated by limiting failure centers on the locations of network nodes. Additionally, we find that with the same impact ratio ${\alpha}$, the topologies examined have larger ${\alpha}$-critical-distances when the network performance is measured using the giant component size instead of the other two metrics. Similar results are obtained when the network performance is measured using the average two terminal reliability and the network efficiency, although computation of the former entails less time complexity than that of the latter.

• Journal of the Institute of Electronics Engineers of Korea SD
• /
• v.42 no.9 s.339
• /
• pp.73-80
• /
• 2005

The Turbo decoders based on Log-MAP decoding algorithm inherently requires large amount of memory and intensive complexity of hardware due to iterative decoding, despite of excellent decoding efficiency. To decrease the large amount of memory and reduce hardware complexity, the result of previous research. And this paper design the Turbo decoder applicable to the 3G W-CDMA systems. Through the result of previous research, we decided 5-bits for the received data 6-bits for a priori information, and 7-bits for the quantization state metrics. The error correction term for $MAX^{*}$ operation which is the main function of Log-MAP decoding algorithm is implemented with very small hardware overhead. The proposed Turbo decoder is synthesized in $0.35\mu$m Hynix CMOS technology. The synthesized result for the Turbo decoder shows that it supports a maximum 9Mbps data rate, and a BER of $10^{-6}$ is achieved(Eb/No=1.0dB, 5 iterations, and the interleaver size $\geq$ 2000).

• The Journal of Korean Institute of Communications and Information Sciences
• /
• v.37B no.12
• /
• pp.1208-1218
• /
• 2012

Disseminating broadcast information stably and reliably in IEEE 802.11-like CSMA wireless networks requires that a source should seek collision-free transmission to multiple receivers and keep track of the reception state of the multiple receivers. We propose a simple yet efficient feedback scheme for stable reliable broadcast in wireless networks, called 2-polling feedback, where the state of two receivers are checked by a source before its broadcast transmission attempt We present a performance analysis of the class of reliable broadcast feedback schemes in terms of two performance metrics (packet transmission delay and packet stable time). The analysis results show that the proposed 2-polling feedback scheme outperforms the current existing classes of feedback schemes in the literature, i.e., all-polling feedback and 1-polling feedback. The 2-polling feedback scheme has lower asymptotic complexity than the all-polling feedback, and has the same asymptotic complexity as the 1-polling feedback but exhibits almost 50 % reduction in packet stable time.

• Journal of Preventive Medicine and Public Health
• /
• v.53 no.6
• /
• pp.405-408
• /
• 2020

In epidemiology, the basic reproduction number (R₀) is a term that describes the expected number of infections generated by 1 case in a susceptible population. At the beginning of the coronavirus disease 2019 (COVID-19) pandemic, R₀ was frequently referenced by the public health community and the wider public. However, this metric is often misused or misinterpreted. Moreover, the complexity of the process of estimating R₀ has caused difficulties for a substantial number of researchers. In this article, in order to increase the accessibility of this concept, we address several misconceptions related to the threshold characteristics of R₀ and the effective reproduction number (R_t). Moreover, the appropriate interpretation of the metrics is discussed. R₀ should be considered as a population-averaged value that pools the contact structure according to a stochastic transmission process. Furthermore, it is necessary to understand the unavoidable time lag for R_t due to the incubation period of the disease.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.4 no.1
• /
• pp.5-24
• /
• 2010

Data fusion is an attractive technology because it allows various trade-offs related to performance metrics, e.g., energy, latency, accuracy, fault-tolerance and security in wireless sensor networks (WSNs). Under a complicated environment, each sensor node must be equipped with more than one type of sensor module to monitor multi-targets, so that the complexity for the fusion process is increased due to the existence of various physical attributes. In this paper, we first investigate the process and performance of multi-attribute fusion in data gathering of WSNs, and then propose a self-adaptive threshold method to balance the different change rates of each attributive data. Furthermore, we present a method to measure the energy-conservation efficiency of multi-attribute fusion. Based on our proposed methods, we design a novel energy equilibrium routing method for WSNs, viz., multi-attribute fusion tree (MAFT). Simulation results demonstrate that MAFT achieves very good performance in terms of the network lifetime.

• The KIPS Transactions:PartD
• /
• v.10D no.4
• /
• pp.689-696
• /
• 2003

Criticality prediction models that determine whether a design entity is fault-prone or non fault-prone are used for identifying trouble spots of software system in analysis or design phases. Many criticality prediction models for identifying fault-prone modules using complexity metrics have been suggested. But most of them need training data set. Unfortunately very few organizations have their own training data. To solve this problem, this paper builds a new prediction model, KSM, based on Kohonen SOM neural networks. KSM is implemented and compared with a well-known prediction model, BackPropagation neural network Model (BPM), considering internal characteristics, utilization cost and accuracy of prediction. As a result, this paper shows that KSM has comparative performance with BPM.