• 한국정보통신설비학회:학술대회논문집
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• 2008.08a
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• pp.233-236
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• 2008

There are several kinds of service standards for 3G($3^{rd}$-Generation) wireless communication as WCDMA, CDMA2000 and WiBro(Wireless Broadband Internet). Especially WiBro Wave2 system is a marked currnt issue. In this paper, we describe on the cell plan tool to desgin WiBro Wave2 network. For this, we treat from basic theory to practical substance to produce new(or modified) path loss prediction model for 2.3GHz. And we explain the method how to implement new technology MIMO(Multiple Input Multiple Output) deployed in Wave2 system. Also we emphasize on the importance of LOS(Line Of Sight) analysis in WiBro network design.

• Computers and Concrete
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• v.15 no.2
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• pp.167-181
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• 2015

"Mortar or concrete pneumatically projected at high velocity onto a surface" is called Shotcrete. Models that predict shotcrete design parameters (e.g. compressive strength, slump etc) from any mixing proportions of admixtures could save considerable experimentation time consumed during trial and error based procedures. Artificial Neural Network (ANN) has been widely used for similar purposes; however, such models have been rarely applied on shotcrete design. In this study 19 samples of shotcrete test panels with varying quantities of water, steel fibers and silica fume were used to determine their slump, cost and compressive strength at different ages. A number of 3-layer Back propagation Neural Network (BPNN) models of different network architectures were used to train the network using 15 samples, while 4 samples were randomly chosen to validate the model. The predicted compressive strength from linear regression lacked accuracy with $R^2$ value of 0.36. Whereas, outputs from 3-5-3 ANN architecture gave higher correlations of $R^2$ = 0.99, 0.95 and 0.98 for compressive strength, cost and slump parameters of the training data and corresponding $R^2$ values of 0.99, 0.99 and 0.90 for the validation dataset. Sensitivity analysis of output variables using ANN can unfold the nonlinear cause and effect relationship for otherwise obscure ANN model.

• ETRI Journal
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• v.40 no.3
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• pp.355-365
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• 2018

The increase in data traffic calls for investment in mobile networks; however, the saturating revenue of mobile broadband and increasing capital expenditure are discouraging mobile operators from investing in next-generation mobile networks. Mobile network sharing is a viable solution for operators and regulators to resolve this dilemma. This research uses a difference-in-differences analysis of 33 operators (including 11 control operators) to empirically evaluate the cost reduction effect of mobile network sharing. The results indicate a reduction in overall operating expenditure and short-term capital expenditure by national roaming. This finding implies that future technology and standards development should focus on flexible network operation and maintenance, energy efficiency, and maximizing economies of scale in radio access networks. Furthermore, mobile network sharing will become more viable and relevant in a 5G network deployment as spectrum bands are likely to increase the total cost of ownership of mobile networks and technical enablers will facilitate network sharing.

• Agricultural and Biosystems Engineering
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• v.3 no.1
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• pp.18-28
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• 2002

Neural network based models were developed and evaluated for predicting corn yield from aerial images based on 1998 and 1994 image data. The model used images in multi-spectral bands such as R, G, B, and IR (Red, Green, Blue and Infrared). The inputs to the neural network consisted of mean and standard deviation of multispectral bands of the aerial images. Performances of several neural network architectures using back-propagation with momentum were compared. The maximum yield prediction accuracy obtained was 97.81%. The BPNN model prediction accuracy could be enhanced by using more number of observations to the model, other data transformation techniques, or by performing optical calibration of the aerial image.

• ETRI Journal
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• v.38 no.3
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• pp.463-468
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• 2016

With the constant increase in network traffic, wireless operators are finding it more challenging to keep network hardware costs to a minimum. At the same time, the energy cost associated with operating a network has increased proportionally. Therefore, the search for higher network capacity is simultaneously accompanied by the search for a cost-efficient network deployment. In this paper, we show that a saving in transmitted signal energy can be achieved at the signal design level by deploying very specific signal processing techniques. Using an orthogonal frequency-division multiplexing signal for Long-Term Evolution networks as an example, we utilize a novel non-uniform companding quantizer to save a transmitted signal energy. Our results show that by using non-uniform quantization it is possible to further optimize 4G wireless networks.

• Industrial Engineering and Management Systems
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• v.9 no.3
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• pp.227-241
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• 2010

A memory module industry's supply chain usually consists of multiple manufacturing sites and multiple distribution centers. In order to fulfill the variety of demands from downstream customers, production planners need not only to decide the order allocation among multiple manufacturing sites but also to consider memory module industrial characteristics and supply chain constraints, such as multiple material substitution relationships, capacity, and transportation lead time, fluctuation of component purchasing prices and available supply quantities of critical materials (e.g., DRAM, chip), based on human experience. In this research, a directed graph-based supply network planning (DGSNP) model is developed for memory module industry. In addition to multi-site order allocation, the DGSNP model explicitly considers production planning for each manufacturing site, and purchasing planning from each supplier. First, the research formulates the supply network's structure and constraints in a directed-graph form. Then, a proposed genetic algorithm (GA) solves the matrix form which is transformed from the directed-graph model. Finally, the final matrix, with a calculated maximum profit, can be transformed back to a directed-graph based supply network plan as a reference for planners. The results of the illustrative experiments show that the DGSNP model, compared to current memory module industry practices, determines a convincing supply network planning solution, as measured by total profit.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.38B no.3
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• pp.172-179
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• 2013

In this paper, we consider network-coded bi-directional relaying (NCBR) schemes over an asymmetric channel, in which bi-directional links have the different channel quality, as well as the asymmetric traffic load. In order to deal with asymmetric nature, two different types of NCBR schemes are considered: network coding after padding (NaP) and network coding after fragmentation (NaF). Even if NaP has been known as only a useful means of dealing with the asymmetry in traffic load up to now, our analysis shows that its gain can be significantly lost by the asymmetry in channel quality, under the given bit error performance constraint. Furthermore, it is shown that NaF always outperforms NaP, as well as traditional bi-directional relaying scheme.

• Journal of the Korean Ceramic Society
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• v.44 no.3 s.298
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• pp.162-168
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• 2007

Silica wet gels were prepared ken water glass ($29\;wt%\;SiO_{2}$) by using Amberlite as a ion exchange resin. After washing in distilled water, the wet gels were further aged in a solution of TEOS/EtOH to strengthen of 3-dimensional network structure. As increase TEOS content in aging solution, BET surface area and porosity of the ambient dried silica aerogels were significantly decreased, and average pore diameter was also decreased 30 nm to -10 nm. Also, higher density and compressive strength were obtained in case of higher TEOS content. This is due to precipitation of $SiO_{2}$ nano particles by TEOS. Hence, TEOS addition plays an important role of both strengthening and stiffness of silica wet gel network. By adding over 30 vol% TEOS, a crack-free monolithic silica aerogel tiles were obtained and its density, compressive strength, and thermal conductivity were shown $0.232g/cm^{3}$, 7.3 MPa, and 0.029 W/mk, respectivly.

• Journal of the Korea Society for Simulation
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• v.15 no.1
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• pp.77-85
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• 2006

The cost of downloading content from the Internet may be costly for mobile device users using its 3G connection, because the 3G connection cost to download data from the Internet is a function of the amount of data downloaded. This paper introduces an approach in which mobile devices, called peers, form an ad hoc network and share their downloaded content with others. As an example, spectators may want to collect/share information about players and game records in a stadium. In an art gallery, visitors may want to retrieve some background information about the displayed work from the nearby ad hoc network. In an outdoor class, a teacher may download today's topic files from the Internet, and all students may share the content with minimal or no cost paid. This is possible if mobile device has both a 3G interface and a wireless LAN interface. If the peers want to improve privacy md discourage traffic analysis when sharing content, this paper describes a low-delay anonymous connection between the sending peer and the receiving peer using two additional peers. Simulation results show that the transmission time overhead of the anonymous connection may increase 50% or less as the number of peers increase or the peers are scattered over the larger area.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.26 no.3
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• pp.469-478
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• 2022

This paper contains the results of developing smart devices and applications to monitor the load power of the industrial manufacturing machine and evaluate its performance. The smart devices in this paper are divided into two functionalities, which are collecting load power along with operating environment data of industrial manufacturing machines and transmitting the data to servers. Load power data collected from the smart devices are uploaded to MariaDB inside the Amazon Web Service (AWS) server. Using the RESTFul API, the uploaded power data can be retrieved and shown on the web and mobile application in the form of a graph to provide monitoring capability. To evaluate the performance of the developed system, the response time from MariaDB to web and mobile applications was measured. The results is ranging from 0.0256 to 0.0545 seconds in a 4G (LTE) network environment and from 0.6126 to 1.2978 seconds in a 3G network environment, which is considered a satisfactory result.