• Journal of Internet Computing and Services
• /
• v.10 no.4
• /
• pp.115-126
• /
• 2009

A software size estimation has to be analyzed in the beginning of the software life-cycle and helpful to the prediction of its size and cost. The software cost has been calculated by estimating software size from the user's point of view since the function point method based on international standards was introduced for the estimation of software size in 2004. However, the current function point method is not easy to be exploited for unfamiliar user, and has a problem that it cannot estimate the proper size for software such as engineering software, scientific calculations and simulation with complicated internal computational logic. This paper presents an improved model which can simplify the existing function point measurement procedure, and perform the estimation of software size in easy and fast way at the initial stage of project. Moreover, it presents a mathematical weighted value calculation model which can solve the problem of the fixed complexity weighted value and reflect the characteristics of organization as its data is pilled up. Our evaluation shows that the presented model has advantage that it can measure the size more rapidly than the existing FPA methods and has more correlation with LOC.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
• /
• v.32 no.3
• /
• pp.233-244
• /
• 2014

Precise Point Positioning (PPP) is an increasingly recognized precisely the GPS/GNSS positioning technique. In order to improve the accuracy of PPP, the error sources in PPP measurements should be reduced as much as possible and the ambiguities should be correctly resolved. The correct ambiguity resolution requires a careful control of residual errors that are normally categorized into random and systematic errors. To understand effects from two categorized errors on the PPP ambiguity resolution, those two GPS datasets are simulated by generating in locations in South Korea (denoted as SUWN) and Hong Kong (PolyU). Both simulation cases are studied for each dataset; the first case is that all the satellites are affected by systematic and random errors, and the second case is that only a few satellites are affected. In the first case with random errors only, when the magnitude of random errors is increased, L1 ambiguities have a much higher chance to be incorrectly fixed. However, the size of ambiguity error is not exactly proportional to the magnitude of random error. Satellite geometry has more impacts on the L1 ambiguity resolution than the magnitude of random errors. In the first case when all the satellites have both random and systematic errors, the accuracy of fixed ambiguities is considerably affected by the systematic error. A pseudorange systematic error of 5 cm is the much more detrimental to ambiguity resolutions than carrier phase systematic error of 2 mm. In the $2^{nd}$ case when only a portion of satellites have systematic and random errors, the L1 ambiguity resolution in PPP can be still corrected. The number of allowable satellites varies from stations to stations, depending on the geometry of satellites. Through extensive simulation tests under different schemes, this paper sheds light on how the PPP ambiguity resolution (more precisely L1 ambiguity resolution) is affected by the characteristics of the residual errors in PPP observations. The numerical examples recall the PPP data analysts that how accurate the error correction models must achieve in order to get all the ambiguities resolved correctly.

• The KIPS Transactions:PartB
• /
• v.10B no.4
• /
• pp.397-402
• /
• 2003

This paper proposes an efficient fixed-point (FP) algorithm for improving performances of the independent component analysis (ICA) based on neural networks. The proposed algorithm is the FP algorithm based on Newton method for ICA using the adaptive learning parameters. The purpose of this algorithm is to improve the separation speed and performance by using the learning parameters in Newton method, which is based on the first order differential computation of entropy optimization function. The learning rate and the moment are adaptively adjusted according to an updating state of inverse mixing matrix. The proposed algorithm has been applied to the fingerprints and the images generated by random mixing matrix in the 8 fingerprints of 256${\times}$256-pixel and the 10 images of 512$\times$512-pixel, respectively. The simulation results show that the proposed algorithm has the separation speed and performance better than those using the conventional FP algorithm based on Newton method. Especially, the proposed algorithm gives relatively larger improvement degree as the problem size increases.

• The KIPS Transactions:PartB
• /
• v.11B no.7 s.96
• /
• pp.813-820
• /
• 2004

This paper proposes a digital image watermarking which is robust to geometric distortions using an independent component analysis(ICA) of fixed-point(FP) algorithm based on secant method. The FP algorithm of secant method is applied for better performance in a separation time and rate, and ICA is applied to reject the prior knowledges for original image, key, and watermark such as locations and size, etc. The proposed method embeds the watermark into the spatial domain of original image The proposed watermarking technique has been applied to lena, key, and two watermarks(text and Gaussian noise) respectively. The simulation results show that the proposed method has higher speed and better rate for extracting the original images than the FP algorithm of Newton method. And the proposed method has a watermarking which is robust to geometric distortions such as resizing, rotation, and cropping. Especially, the watermark of images with Gaussian noise has better extraction performance than the watermark with text since Gaussian noise has lower correlation coefficient than the text to the original and key images. The watermarking of ICA doesn't require the prior knowledge for the original images.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
• /
• 2010.10a
• /
• pp.722-725
• /
• 2010

In this paper, BER performance and error convergence speed of layered LDPC(Low Density Parity Check) decoder which supports IEEE 802.16e WiMAX standard is analyzed, and optimal design conditions for hardware implementation are derived. A LDPC decoder is modeled and simulated at AWGN channel with QPSK modulation by Matlab. The parity check matrix(PCM) for IEEE 802.16e standard which has block lengths of 576, 1440, 2304 and code rates of 1/2, 2/3A, 2/3B, 3/4A, 3/4B, 5/6 are used. Fixed-point simulation results show that fixed-point bit-width should be more than 8 bits for acceptable decoding performance.

• The KIPS Transactions:PartB
• /
• v.13B no.1 s.104
• /
• pp.27-34
• /
• 2006

In this study, we propose this new algorithm that generates score function in ICA(Independent Component Analysis) using entropy theory. To generate score function, estimation of probability density function about original signals are certainly necessary and density function should be differentiated. Therefore, we used kernel density estimation method in order to derive differential equation of score function by original signal. After changing formula to convolution form to increase speed of density estimation, we used FFT algorithm that can calculate convolution faster. Proposed score function generation method reduces the errors, it is density difference of recovered signals and originals signals. In the result of computer simulation, we estimate density function more similar to original signals compared with Extended Infomax and Fixed Point ICA in blind source separation problem and get improved performance at the SNR(Signal to Noise Ratio) between recovered signals and original signal.

• Journal of the Institute of Electronics Engineers of Korea TC
• /
• v.37 no.1
• /
• pp.1-11
• /
• 2000

We propose a predistorter to compensate for nolinear distortion induced by a high power amplifier employed in multi carrier-code division multiple access (MC-CDMA) systems. The proposed scheme rests upon the fixed point iteration (FPI) associated with the contraction mapping theorem. Unlike the predistorter based on the FPI already presented by the authors in other literatures which operates on complex-valued modulation signals, the proposed predistorter in this paper deals with real-valued FPI on modulation signal amplitudes, resulting in less complexity. Simulation results on a BPSK-modulated, 64-subcarrier synchronous MC-CDMA baseband system with a traveling wave tube amplifier in the transmitter, indicate that the proposed predistorter achieves significant improvement in terms of bit error rate and total degradation over those without the predistorter. Moreover, the proposed predistorter outperforms the complex-valued counterpart, in particular, for small output back-off levels.

• The KIPS Transactions:PartB
• /
• v.9B no.5
• /
• pp.643-652
• /
• 2002

This paper proposes an efficient hybrid fixed-point (FP) algorithm for improving performances of the independent component analysis (ICA) based on neural networks. The proposed algorithm is the FP algorithm based on secant method and momentum for ICA. Secant method is applied to improve the separation performance by simplifying the computation process for estimating the root of objective function, which is to minimize the mutual informations of the independent components. The momentum is applied for high-speed convergence by restraining the oscillation if the process of converging to the optimal solution. It can simultaneously achieve a superior properties of the secant method and the momentum. The proposed algorithm has been applied to the composite fingerprints and the images generated by random mixing matrix in the 8 fingerprints of $256\times{256}$-pixel and the 10 images of $512\times{512}$-pixel, respectively. The simulation results show that the proposed algorithm has better performances of the separation speed and rate than those using the FP algorithm based on Newton and secant method. Especially, the secant FP algorithm can be solved the separating performances depending on initial points settings and the nonrealistic learning time for separating the large size images by using the Newton FP algorithm.

• The KIPS Transactions:PartC
• /
• v.18C no.4
• /
• pp.265-278
• /
• 2011

The objective of this paper is to analyze and characterize end-to-end packet statistics after modeling and simulation of WiFi (IEEE 802.11g) and WiMAX (IEEE 802.16e) of a virtual wireless network using OPNET Modeler Wireless Suite. Wireless internal and external network simulators such as Remcom's Wireless InSite Real Time (RT) module, WinProp: W-LAN/Fixed WiMAX/Mobile WiMAX, and SMI system, are designed to consider data transfer rate based on wireless propagation signal strength. However, we approached our research in a different perspective without support for characteristic of these wireless network simulators. That is, we will discuss the purpose of a visual analysis for these packets, how to receive each point packets (e.g., wireless user, base station or access point, and http server) through end-to-end virtual network modeling based on integrated wired and wireless network without wireless propagation signal strength. Measuring packet statistics is important in QoS metric analysis among wireless network performance metrics. Clear packet statistics is an especially essential metric in guaranteeing QoS for WiMAX users. We have found some interesting results through modeling and simulation for virtual wireless network using OPNET Modeler Wireless Suite. We are also able to analyze multi-view efficiency through experiment/observation result.

• Journal of the Korea Institute of Information and Communication Engineering
• /
• v.7 no.5
• /
• pp.907-915
• /
• 2003

A very efficient packet transmission scheme is needed in the radio environment where radio resource is insufficient as compared with the environment of the wired communication. In general, dual mode packet transmission scheme is used broadly. Packets are transmitted through the dedicated or common chamois according to a switching criterion. The general criteria are the length and generation frequency of packet, that is, large and frequent packets are transmitted using a dedicated channel and small and infrequent packets are transmitted using a common channel. The performance of dual mode packet transmission scheme is closely related to the switching criteria. However, it is very difficult to find the optimal switching point because that is not fixed but variable according to the environment such as traffic load, length of generated packets, and the number of channels. In this paper, a new scheme for the dual mode packet transmission scheme using a dynamic switching threshold is proposed where the switching threshold is not fixed but variable according to the network environment. The performance of the proposed method is analyzed using a simulation. From the simulation results, it is shown that the performance of the proposed scheme is not very influenced by the network environment unlike the conventional dual mode packet transmission scheme.