• Asian Pacific Journal of Cancer Prevention
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• v.17 no.5
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• pp.2597-2603
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• 2016

Ovarian cancer is a highly malignant neoplasm with high mortality rates. Research to identify markers facilitating early detection has been pursued for many years. Currently, diagnosis is based on the CA 125 and HE4 markers, as well as the ROMA algorithm. The search continues for new proteins that meet the criteria of good markers A total of 90 patients were included in the present study, allocated into: group 1, ovarian cancer, with 29 patients; group 2, endometrial cysts, with 30s; and group 3, simple ovarian cysts, with 31. Following histopathological verification, the CA 125, HE4, and metalloproteinase 3 (MMP3) levels were determined and the ROMA algorithm was calculated for all patients. The mean concentrations of all determined proteins, CA 125, HE4, and MMP3, as well as the ROMA values, were significantly higher in group 1 (ovarian cancer) compared to group 3 (simple ovarian cysts). The highest significant differences for the CA 125 levels (p<0.000001) and ROMA (p<0.000001) values were observed in postmenopausal women. For HE4, statistical significance was at the level of p=0.00001 compared to p=0.002 for MMP3. For the differentiation between ovarian cancer and endometrial cysts, the respective AUC ratios were obtained for CA 125, HE4, and MMP3 levels, as well as the ROMA values ( 0,93 / 0,96 / 0,75 / 0,98). After removing the post-menopausal patients, the MMP3 AUC value for ovarian cancer vs. benign ovarian cysts increased to 0.814. For post-menopausal women, the MMP3 AUC value for ovarian cancer vs. endometrial cysts was 0.843. As suggested by the results above, both the CA 125 and HE4 markers, as well as the ROMA algorithm, meet the criteria of a good diagnostic test for ovarian cancer. MMP3 seems to meet the criteria of a good diagnostic test, particularly in postmenopausal women; however, it is not superior to the tests used to date.

• The Journal of the Korea institute of electronic communication sciences
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• v.10 no.11
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• pp.1225-1230
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• 2015

MAC protocol for WBAN performs CSMA/CA(:Carrier Sense Multiple Access with Collision Avoidance)algorithm that handles traffic which occurs in emergency with top priority in order to deal with variable data of sensor node for medicine. Emergency message that node sends undergoes collision and delay of transmission by retransmission of emergency message and waste of energy by retransmission. This paper suggests algorithm that minimizes loss of frame caused by collision and applies different backoff parameters by setting order of priority between MAC instruction frame and data frame in CSMA/CA algorithm case which applies order of priority queuing to improve aforementioned problem. According to performance evaluation, it has been found that using suggested MAC protocol showed lower collision probability, higher packet transmission processing ratio and lower packet loss compared with using IEEE 802.15.6.

• International journal of advanced smart convergence
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• v.1 no.1
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• pp.14-18
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• 2012

This paper presents a fair MAC protocol based on the CSMA/CA algorithm in visible light communication (VLC) networks. The problem of bandwidth sharing among differentiated priority in VLC networks can be solved by using number of backoff time and backoff exponent parameters with AIFS. The proposed algorithm can achieve fair allocation of the bandwidth resource among differentiated priority. The two dimension Markov chain is assisted for analyzing the proposed mechanism about throughput and delay metrics. Numerical results show that our proposed algorithm improves the fairness among different traffic flows.

• Proceedings of the KOR-KST Conference
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• 2007.11a
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• pp.852-858
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• 2007

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2001.12a
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• pp.255-258
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• 2001

This paper is implementation of cellular automata neural network system which is a living creatures' brain using evolving hardware concept. Cellular automata neural network system is based on the development and the evolution, in other words, it is modeled on the ontogeny and phylogeny of natural living things. The proposed system developes each cell's state in neural network by CA. And it regards code of CA rule as individual of genetic algorithm, and evolved by genetic algorithm. In this paper we implement this system using evolving hardware concept Evolving hardware is reconfigurable hardware whose configuration is under the control of an evolutionary algorithm. We design genetic algorithm process for evolutionary algorithm and cells in cellular automata neural network for the construction of reconfigurable system. The effectiveness of the proposed system is verified by applying it to time-series prediction.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.11 no.6
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• pp.2263-2268
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• 2010

In this paper, the hybrid compensation algorithm($A_{HB}$) for localization using the Compensation Algorithm distance($CA_d$) and the Algorithm of Equivalent Distance Rate(AEDR) in SDS-TWR(Symmetric Double-Sided Two-Way Ranging) is suggested and the performance of the proposed algorithm is analyzed by practical experimentations. From experimentations, it is confirmed that the errors are reduced in 28 coordinates of total 32 coordinates in the experimental region and the errors are reduced about above 70% in the assigned 3 type error level ranges by $A_{HB}$. Also, it is analyzed that the average localization error is reduced from 2.67m to 1.19m as 55.4% in total 32 coordinates by $A_{HB}$ and the error compensation capability of $A_{HB}$ is very excellent as above 90%. From above results, we have seen that the error reduction ratio and error compensation capability of $A_{HB}$ is more excellent than each $CA_d$ or AEDR.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.34 no.10B
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• pp.964-972
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• 2009

Wireless mesh network (WMN) is emerging a future core technology to resolve many problems derived from exist wireless networks by employing multi-interface and multi-channel. Ability to utilize multiple channels in WMNs substantially increases the effective bandwidth available to wireless network nodes. However, minimum interference channel assignment algorithms are required to use the effective bandwidth in multi-channel environments. This paper proposes a cluster-based minimum interference channel assignment (MI-CA) algorithm to improve the performance of WMN. The MI-CA algorithm is consists of Inter-Cluster and Intra-Cluster Intrchannel assignment between clusters and in the internal clusters, respectively. The Inter-Cluster channel assignment assigns a barebone channel to cluster heads and border nodes based on minimum spanning tree (MST) and the Intra-Cluster channel assignment minimizes channel interference by reassigning ortasgonal channels between cluster mespann. Our simheation results show that MI-CA can improve the performance of WMNs by minimizing channel interference.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.25 no.8
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• pp.849-856
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• 2014

This paper proposes a new efficient CFAR algorithm. The structure of the proposed CFAR is relatively simple as compared with the OS-CFAR or ML-CFAR which are considered to deal with the nonhomogeneous environment such as clutter and multiple targets. The proposed algorithm is effectively applied to the radar signal processor with reduced computation burden. The relationship between the threshold and PFA of the proposed CFAR is derived analytically. The CFAR loss of the proposed CFAR algorithm is compared with CA-CFAR and OS-CFAR based on both SNR and ADT(Average Detection Threshold).

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.9 no.12
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• pp.4799-4818
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• 2015

In this paper, we investigate the problem of achieving global optimization for distributed carrier aggregation (CA) in small cell networks, using a game theoretic solution. To cope with the local interference and the distinct cost of intra-band and inter-band CA, we propose a non-cooperation game which is proved as an exact potential game. Furthermore, we propose a spatial adaptive play learning algorithm with heterogeneous learning parameters to converge towards NE of the game. In this algorithm, heterogeneous learning parameters are introduced to accelerate the convergence speed. It is shown that with the proposed game-theoretic approach, global optimization is achieved with local information exchange. Simulation results validate the effectivity of the proposed game-theoretic CA approach.

• Journal of information and communication convergence engineering
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• v.4 no.2
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• pp.71-74
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• 2006

A basic access method about IEEE 802.11 MAC layer protocol using IEEE 802.11 wireless LANs is the DCF thatis based on the CSMA/CA. But, cause of IEEE 802.11 MAC layer uses original backoff algorithm (exponential backoff method), when collision occurred, the size of contention windows increases the double size Also, a time of packet transmission delay increases and efficienty is decreased by original backoff scheme. In this paper, we have analyzed TCP packet transmission time of IEEE 802.11 MAC DCF protocol for wireless LANs a proposed enhanced backoff algorithm. It is considered the transmission time of transmission control protocol (TCP) packet on the orthogonal frequency division multiplexing (OFDM) in additive white gaussian noise (A WGN) and Rician fading channel. From the results, a proposed enhanced backoff algorithm produces a better performance improvement than an original backoff in wireless LAN environment. Also, in OFDM/quadrature phase shift keying channel (QPSK), we can achieve that the transmission time in wireless channel decreases as the TCP packet size increases and based on the data collected, we can infer the correlation between packet size and the transmission time, allowing for an inference of the optimal packet size in the TCP layer.