• Journal of the Korean Society of Manufacturing Process Engineers
• /
• v.13 no.6
• /
• pp.54-60
• /
• 2014

In industry, several casting process are widely used to manufacture complex and accurate blank part of hard materials such as aluminum, casting steels, bronze and magnesium alloys which are difficult to manufacture in a blank shape. Even if the casting process does not high accuracy superior surface characteristics other machining process, the casting process is widely used in manufacturing blank part. Furthermore, it is difficult to select appropriate casting process a part among several casting process. for effective selection different process, a careful decision given casting application is necessary. An appropriate casting for a given material and shape condition must be selected for novice engineers in industry. In this paper, an expert system based on an analytic network process(ANP) is suggested for best selection of casting considering a prior interdependency effect among various factors such as material, geometry, process capability, economy and equipment.

• Journal of the Korea Academia-Industrial cooperation Society
• /
• v.9 no.2
• /
• pp.508-514
• /
• 2008

Knowledge management has been spread rapidly since Knowledge is regarded as a crucial asset in future. Once, Knowledge had been obtained freely but hard to be shared. Studies on importance and share of knowledge have been taking place and it leads to development of knowledge management systems. However, decision makers still have problems even though they are using knowledge management systems. Eventually, for the decision makers are needed concentrated knowledge which is unconscious and embodied, when they make a decision. This is wisdom. Thus, wisdom is superior to knowledge for the decision makers. There are some researches on wisdom but wisdom management were overlooked. This study presents differences between knowledge and wisdom with theoretical research and empirical analysis on the wisdom management.

• The Journal of Korean Institute of Communications and Information Sciences
• /
• v.31 no.7A
• /
• pp.682-688
• /
• 2006

In this paper, a soft-decision method for initial PN code acquisition in pilot-channel aided Direct Sequence Code Division Multiple Access (DS-CDMA) systems is proposed in order to improve the acquisition performance. We apply this technique to the conventional hybrid search algorithm and analyze it in terms of mean code acquisition time. For the analysis, we present mathematical model of proposed algorithm and also perform the simulation under IMT-2000 channel models. Numerical results show that our proposed scheme outperforms the conventional one by 0.2 - 0.4 sec with respect to the mean code acquisition time because the soft decision technique can mitigate the possible decline in search performance caused by the use of a hard-decision technique.

• The Journal of Korean Institute of Communications and Information Sciences
• /
• v.32 no.7C
• /
• pp.616-626
• /
• 2007

In spatially multiplexed MIMO systems that enable high data rate transmission over wireless communication channels, the spatial demultiplexing at the receiver is a challenging task, and various demultiplexing methods have been developed recently by many researchers. Among the previous methods, maximum likelihood detection with QR decomposition and M-algorithm (QRM-MM)), and sphere decoding (SD) schemes have been reported to achieve a (near) maximum likelihood (ML) performance. In this paper, we propose a novel signal detection method that achieves a near ML performance in a computationally efficient manner. The proposed method is demonstrated via a set of computer simulations that the proposed method achieves a near ML performance while requiring a complexity that is comparable to that of the conventional MMSE-OSIC. We also show that the log likelihood ratio (LLR) values for all bits are obtained without additional calculation but as byproduct in the proposed detection method, while in the previous QRM-MLD, SD, additional computation is necessary after the hard decision for LLR calculation.

• Journal of Communications and Networks
• /
• v.16 no.2
• /
• pp.172-182
• /
• 2014

In this paper, we investigate the fundamental performance limits of the cooperative sensing using energy detection by considering the unlimited number of sensing nodes. Although a lot of cognitive radio research so far proposed various uses of energy detection because of its simplicity, the performance limits of energy detection have not been studied when a large number of sensing nodes exist. First, we show that when the sensing nodes see the independent and identically distributed channel conditions, then as the number of sensing nodes N goes to infinity, the OR rule of hard decision achieves zero of false alarm Pf for any given target probability of detection $\bar{P_d}$ irrespective of the non-zero received primary user signal to noise ratio ${\gamma}$. Second, we show that under the same condition, when the AND rule of hard decision is used, there exists a lower bound of $P_f$. Interestingly, however, for given $\bar{P_d}$, $P_f$ goes to 1 as N goes to infinity. Third, we show that when the soft decision is used, there exists a way of achieving 100% utilization of secondary user, i.e., the sensing time overhead ratio goes to zero so does $P_f$.We verify our analyses by performing extensive simulations of the proposed unlimited cooperative sensing. Finally, we suggest a way of incorporating the unlimited cooperative sensing into a practical cellular system such as long term evolutionadvanced by exploiting the existing frame structure of absolute blank subframe to implement the in-band sensing.

• Nuclear Engineering and Technology
• /
• v.53 no.8
• /
• pp.2534-2546
• /
• 2021

Nuclear emergency preparedness and response is an essential part to ensure the safety of nuclear power plant (NPP). Key support technologies of nuclear emergency decision-making usually consist of accident diagnosis, source term estimation, accident consequence assessment, and protective action recommendation. Source term estimation is almost the most difficult part among them. For example, bad communication, incomplete information, as well as complicated accident scenario make it hard to determine the reactor status and estimate the source term timely in the Fukushima accident. Subsequently, it leads to the hard decision on how to take appropriate emergency response actions. Hence, this paper aims to develop a method for rapid source term estimation to support nuclear emergency decision making in pressurized water reactor NPP. The method aims to make our knowledge on NPP provide better support nuclear emergency. Firstly, this paper studies how to build a Bayesian network model for the NPP based on professional knowledge and engineering knowledge. This paper presents a method transforming the PRA model (event trees and fault trees) into a corresponding Bayesian network model. To solve the problem that some physical phenomena which are modeled as pivotal events in level 2 PRA, cannot find sensors associated directly with their occurrence, a weighted assignment approach based on expert assessment is proposed in this paper. Secondly, the monitoring data of NPP are provided to the Bayesian network model, the real-time status of pivotal events and initiating events can be determined based on the junction tree algorithm. Thirdly, since PRA knowledge can link the accident sequences to the possible release categories, the proposed method is capable to find the most likely release category for the candidate accidents scenarios, namely the source term. The probabilities of possible accident sequences and the source term are calculated. Finally, the prototype software is checked against several sets of accident scenario data which are generated by the simulator of AP1000-NPP, including large loss of coolant accident, loss of main feedwater, main steam line break, and steam generator tube rupture. The results show that the proposed method for rapid source term estimation under nuclear emergency decision making is promising.

• The Journal of Korean Institute of Communications and Information Sciences
• /
• v.37 no.7A
• /
• pp.512-521
• /
• 2012

In this paper, we propose feasible combining rules for a decoding scheme of product codes to apply finite soft decision. Since the decoding scheme of product codes are based on complex tanh calculation with infinite soft decision, it requires high decoding complexity and is hard to practically implement. Thus, simple methods to construct look-up tables for finite soft decision are derived by analyzing the operations of the scheme. Moreover, we focus on using convolutional codes, which is popular for easy application of finite soft decision, as the horizontal codes of product codes so that the proposed decoding scheme can be properly implemented. Numerical results show that the performance of the product codes with convolutional codes using 4-bit soft decision approaches to that of same codes using infinite soft decision.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.6 no.12
• /
• pp.3061-3080
• /
• 2012

To improve the sensing performance, cooperation among secondary users can be utilized to collect space diversity. In this paper, we focus on the optimization of cooperative spectrum sensing in which multiple cognitive users efficiently cooperate to achieve superior detection accuracy with minimum sensing error probability in multiple cross-over cognitive radio networks. The analysis focuses on two fusion strategies: soft information fusion and hard information fusion. Under soft information fusion, the optimal threshold of the energy detector is derived in both noncooperative single-user and cooperative multiuser sensing scenarios. Under hard information fusion, the optimal randomized rule and the optimal decision threshold are derived according to the rule of minimum sensing error (MSE). MSE rule shows better performance on improving the final false alarm and detection probability simultaneously. By simulations, our proposed strategy optimizes the sensing performance for each cognitive user which is randomly distributed in the multiple cross-over cognitive radio networks.

• Journal of the Institute of Electronics Engineers of Korea SP
• /
• v.47 no.6
• /
• pp.66-74
• /
• 2010

Recently distributed video coding (DVC) is spotlighted for the environment which has restriction in computing resource at encoder. Wyner-Ziv (WZ) coding is a representative scheme of DVC. The WZ encoder independently encodes key frame and WZ frame respectively by conventional intra coding and channel code. WZ decoder generates side information from reconstructed two key frames (t-1, t+1) based on temporal correlation. The side information is regarded as a noisy version of original WZ frame. Virtual channel noise can be removed by channel decoding process. So the performance of WZ coding greatly depends on the performance of channel code. Among existing channel codes, Turbo code and LDPC code have the most powerful error correction capability. These channel codes use stochastically iterative decoding process. However the iterative decoding process is quite time-consuming, so complexity of WZ decoder is considerably increased. Analysis of the complexity of LPDCA with real video data shows that the portion of complexity of LDPCA decoding is higher than 60% in total WZ decoding complexity. Using the HDA (Hard Decision Aided) method proposed in channel code area, channel decoding complexity can be much reduced. But considerable RD performance loss is possible according to different thresholds and its proper value is different for each sequence. In this paper, we propose an adaptive HDA method which sets up a proper threshold according to sequence. The proposed method shows about 62% and 32% of time saving, respectively in LDPCA and WZ decoding process, while RD performance is not that decreased.

• Journal of Broadcast Engineering
• /
• v.16 no.4
• /
• pp.635-646
• /
• 2011

In distributed video coding, low complexity encoder can be realized by shifting encoder-side complex processes to decoder-side. However, not only motion estimation/compensation processes but also complex LDPC decoding process are imposed to the Wyner-Ziv decoder, therefore decoder-side complexity has been one important issue to improve. LDPC decoding process consists of numerous iterative decoding processes, therefore complexity increases as the number of iteration increases. This iterative LDPC decoding process accounts for more than 60% of whole WZ decoding complexity, therefore it can be said to be a main target for complexity reduction. Previously, HDA (Hard Decision Aided) method is introduced for fast LDPC decoding process. For currently received parity bits, HDA method certainly reduces the complexity of decoding process, however, LDPC decoding process is still performed even with insufficient amount of parity request which cannot lead to successful LDPC decoding. Therefore, we can further reduce complexity by avoiding the decoding process for insufficient parity bits. In this paper, therefore, a parity request estimation method is proposed using bit plane-wise correlation and temporal correlation. Joint usage of HDA method and the proposed method achieves about 72% of complexity reduction in LDPC decoding process, while rate distortion performance is degraded only by -0.0275 dB in BDPSNR.