• Journal of the Microelectronics and Packaging Society
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• v.21 no.1
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• pp.31-39
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• 2014

For mobile application, semiconductor packages are increasingly moving toward high density, miniaturization, lighter and multi-functions. Typical wafer level packages (WLP) is fan-in design, it can not meet high I/O requirement. The fan-out wafer level packages (FOWLPs) with reconfiguration technology have recently emerged as a new WLP technology. In FOWLP, warpage is one of the most critical issues since the thickness of FOWLP is thinner than traditional IC package and warpage of WLP is much larger than the die level package. Warpage affects the throughput and yield of the next manufacturing process as well as wafer handling and fabrication processability. In this study, we investigated the characteristics of warpage and main parameters which affect the warpage deformation of FOWLP using the finite element numerical simulation. In order to minimize the warpage, the characteristics of warpage for various epoxy mold compounds (EMCs) and carrier materials are investigated, and DOE optimization is also performed. In particular, warpage after EMC molding and after carrier detachment process were analyzed respectively. The simulation results indicate that the most influential factor on warpage is CTE of EMC after molding process. EMC material of low CTE and high Tg (glass transition temperature) will reduce the warpage. For carrier material, Alloy42 shows the lowest warpage. Therefore, considering the cost, oxidation and thermal conductivity, Alloy42 or SUS304 is recommend for a carrier material.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.39 no.3
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• pp.18-31
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• 2002

In this study, we introduce a concept of advanced neurofuzzy polynomial networks(ANFPN), a hybrid modeling architecture combining neurofuzzy networks(NFN) and polynomial neural networks(PNN). These networks are highly nonlinear rule-based models. The development of the ANFPN dwells on the technologies of Computational Intelligence(Cl), namely fuzzy sets, neural networks and genetic algorithms. NFN contributes to the formation of the premise part of the rule-based structure of the ANFPN. The consequence part of the ANFPN is designed using PNN. At the premise part of the ANFPN, NFN uses both the simplified fuzzy inference and error back-propagation learning rule. The parameters of the membership functions, learning rates and momentum coefficients are adjusted with the use of genetic optimization. As the consequence structure of ANFPN, PNN is a flexible network architecture whose structure(topology) is developed through learning. In particular, the number of layers and nodes of the PNN are not fixed in advance but is generated in a dynamic way. In this study, we introduce two kinds of ANFPN architectures, namely the basic and the modified one. Here the basic and the modified architecture depend on the number of input variables and the order of polynomial in each layer of PNN structure. Owing to the specific features of two combined architectures, it is possible to consider the nonlinear characteristics of process system and to obtain the better output performance with superb predictive ability. The availability and feasibility of the ANFPN are discussed and illustrated with the aid of two representative numerical examples. The results show that the proposed ANFPN can produce the model with higher accuracy and predictive ability than any other method presented previously.

• Spatial Information Research
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• v.12 no.1
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• pp.13-27
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• 2004

The current industrial development and the increase of population in Daecheong Reservoir basin have produced a rapid increase of wastewater discharge. This has resulted in problem of water quality control and management. Although many efforts have been carried out, reservoir water quality has not significantly improved. In this sense, the development of water quality management system is required to improve reservoir water quality. The goal of this study is to design a GIS-based water quality management system for the scientific water quality control and management in the Daecheong Reservoir. For general water quality analysis, WASP5 model was applied to the Daecheong Reservoir. A sensitivity analysis was made to determine significant parameters and an optimization was made to estimate optimal values. The calibration and verification were performed by using observed water quality data for Daecheong Reservoir. A water quality management system for Daecheong Reservoir was made by connecting the WASP5 model to ArcView. It allows a Windows-based Graphic User Interface(GUI) to implement all operation with regard to water quality analysis. The proposed water quality management system has capability for the on-line data process including water quality simulation, and has a post processor far the reasonable visualization for various output. The modeling system in this study will be an efficient NGIS(National Geographic Information System) far planning of reservoir water quality management.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.12 no.10
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• pp.4678-4702
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• 2018

Traffic Matrix estimation has always caught attention from researchers for better network management and future planning. With the advent of high traffic loads due to Cloud Computing platforms and Software Defined Networking based tunable routing and traffic management algorithms on the Internet, it is more necessary as ever to be able to predict current and future traffic volumes on the network. For large networks such origin-destination traffic prediction problem takes the form of a large under- constrained and under-determined system of equations with a dynamic measurement matrix. Previously, the researchers had relied on the assumption that the measurement (routing) matrix is stationary due to which the schemes are not suitable for modern software defined networks. In this work, we present our Compressed Sensing with Dynamic Model Estimation (CS-DME) architecture suitable for modern software defined networks. Our main contributions are: (1) we formulate an approach in which measurement matrix in the compressed sensing scheme can be accurately and dynamically estimated through a reformulation of the problem based on traffic demands. (2) We show that the problem formulation using a dynamic measurement matrix based on instantaneous traffic demands may be used instead of a stationary binary routing matrix which is more suitable to modern Software Defined Networks that are constantly evolving in terms of routing by inspection of its Eigen Spectrum using two real world datasets. (3) We also show that linking this compressed measurement matrix dynamically with the measured parameters can lead to acceptable estimation of Origin Destination (OD) Traffic flows with marginally poor results with other state-of-art schemes relying on fixed measurement matrices. (4) Furthermore, using this compressed reformulated problem, a new strategy for selection of vantage points for most efficient traffic matrix estimation is also presented through a secondary compression technique based on subset of link measurements. Experimental evaluation of proposed technique using real world datasets Abilene and GEANT shows that the technique is practical to be used in modern software defined networks. Further, the performance of the scheme is compared with recent state of the art techniques proposed in research literature.

• Korean journal of food and cookery science
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• v.29 no.3
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• pp.291-300
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• 2013

This study was conducted to develop the optimum mixing rates of a functional instant pumpkin gruel including pumpkin powder and to have the high preference to all age groups. The produced of this study were to optimum the composite recipe by making instant pumpkin gruel, respectively, with the different 16 experimental point with 3 replicates of the weight of pumpkin powder ($X_1$), roasted soybean flour ($X_2$) and gelatinized rice flour ($X_3$), and by quantities of the using response surface methodology(RSM). The color, pH, viscosity, and sensory characteristics(appearance, color, flavor, taste, viscosity, overall acceptability) were dependent parameters. The color of instant pumpkin gruel L value decreased with increasing amounts of pumpkin powder and a value and b value increased. pH and viscosity increased with increasing amounts of pumpkin powder and roasted soybean powder. The optimal mixing percentage of pumpkin powder, roasted soybean flour and gelatinized rice flour were 5.25 g, 3.00 g and 4.50 g for overall quality of 5.72 g, 4.30 g and 3.00 g for maximum score of overall organoleptic quality, respectively.

• Applied Chemistry for Engineering
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• v.31 no.4
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• pp.377-382
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• 2020

A sequential design of experiments was employed to optimize MOF-235 synthesis for acetylene adsorption process. Two experimental designs were applied: a two-level factorial design for screening and a central composite design, one of response surface methodologies (RSM). In this study, 2³ factorial design of experiment was used to evaluate the effect of parameters of synthesis temperature and time, and also mixing speed on crystallinity of MOF-235. Experiments were conducted 16 times follwing MINITAB 19 design software for MOF-235 synthesis. Half-normal, pareto, residual, main and interaction effects were drawn based on the XRD results. The analysis of variance (ANOVA) of test results depicts that the synthesis temperature and time have significant effects on the crystallinity of MOF-235 (response variable). After screening, a central composite design was performed to optimize the acetylene adsorption capacity of MOF-235 based on synthesis conditions. From nine runs designed by MINITAB 19, the result was calculated using the second order model equation. It was estimated that the maximum adsorption capacity (18.7 mmol/g) was observed for MOF-235 synthesized at optimum conditions of 86.3 ℃ and 28.7 h.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.9 no.5
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• pp.38-48
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• 2010

Adverse weather (e.g. strong winds, snow and ice) will probably appear as a more serious and frequent threat to road traffic than in clear climate. Another consequence of climate change with a natural disastrous on road traffic is respond to traffic accident more the large and high-rise bridge zone, tunnel zone, inclined plane zone and de-icing zone than any other zone, which in turn calls for continuous adaption of monitoring procedures. Accident mitigating measures against this accident category may consist of intense winter maintenance, the use of road weather information systems for data collection and early warnings, road surveillance and traffic control. While hazard from reduced road friction due to snow and ice may be eliminated by snow removal and de-icing measures, the effect of strong winds on road traffic are not easily avoided. The purpose of the study described here, was to design of amber information the relationship between traffic safety, weather, user information on road weather and driving conditions in local-scale Geographic. The most applications are the optimization of the amber information definition, improvements to road surveillance, road weather monitoring and improved accuracy of user information delivery. Also, statistics on wind gust, surface condition, vehicle category and other relevant parameters for wind induced accidents provide basis for traffic control, early warning policies and driver education for improved road safety at bad weather-exposed locations.

• Journal of Korea Multimedia Society
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• v.5 no.5
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• pp.512-522
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• 2002

In this paper, we propose a hybrid method which is mixed with frame selection and weighting model rank method, based on GMM(gaussian mixture model), for real-time text-independent speaker recognition system. In the system, maximum likelihood estimation was used for GMM parameter optimization, and maximum likelihood was used for recognition basically Proposed hybrid method has two steps. First, likelihood score was calculated with speaker models and test data at frame level, and the difference is calculated between the biggest likelihood value and second. And then, the frame is selected if the difference is bigger than threshold. The second, instead of calculated likelihood, weighting value is used for calculating total score at each selected frame. Cepstrum coefficient and regressive coefficient were used as feature parameters, and the database for test and training consists of several data which are collected at different time, and data for experience are selected randomly In experiments, we applied each method to baseline system, and tested. In speaker recognition experiments, proposed hybrid method has an average of 4% higher recognition accuracy than frame selection method and 1% higher than W method, implying the effectiveness of it.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.48 no.10
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• pp.791-799
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• 2020

Launched in October 2019, Northrop Grumman's MEV-1 was the world's first unmanned mission demonstrating the practical feasibility of on-orbit servicing. Although the concept of on-orbit servicing was proposed several decades ago, it has been developed to various mission concepts providing services such as orbit change, station keeping, propellant and equipment supply, upgrade, repair, on-orbit assembly and production, and space debris removal. The historical success of MEV-1 is expected to expand the market of on-orbit servicing for government agencies and commercial sectors worldwide. The on-orbit servicing essentially requires the utilization of a highly propellant efficient electric propulsion system due to the nature of the mission. In this study, the space mission analysis for a simple on-orbit mission involving Hall thruster is conducted, which is life extension mission for geostationary orbit satellites. In order to analyze the mission, design space exploration for various Hall thruster design variable combinations is performed. The values of design variables and operational parameters of Hall thruster suitable for the mission are proposed through design space analysis and optimization, and mission performance is derived. In addition, the direction of further improvement for the current on-orbit mission analysis process and space mission analysis involving Hall thruster is reviewed.

• The KIPS Transactions:PartA
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• v.12A no.5 s.95
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• pp.451-460
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• 2005

We present a methodology to design energy-efficient data paths using FPGAs. Our methodology integrates domain specific modeling, coarse-grained performance evaluation, design space exploration, and low-level simulation to understand the tradeoffs between energy, latency, and area. The domain specific modeling technique defines a high-level model by identifying various components and parameters specific to a domain that affect the system-wide energy dissipation. A domain is a family of architectures and corresponding algorithms for a given application kernel. The high-level model also consists of functions for estimating energy, latency, and area that facilitate tradeoff analysis. Design space exploration(DSE) analyzes the design space defined by the domain and selects a set of designs. Low-level simulations are used for accurate performance estimation for the designs selected by the DSE and also for final design selection We illustrate our methodology using a family of architectures and algorithms for matrix multiplication. The designs identified by our methodology demonstrate tradeoffs among energy, latency, and area. We compare our designs with a vendor specified matrix multiplication kernel to demonstrate the effectiveness of our methodology. To illustrate the effectiveness of our methodology, we used average power density(E/AT), energy/(area x latency), as themetric for comparison. For various problem sizes, designs obtained using our methodology are on average $25\%$ superior with respect to the E/AT performance metric, compared with the state-of-the-art designs by Xilinx. We also discuss the implementation of our methodology using the MILAN framework.