• Journal of the Institute of Electronics Engineers of Korea SD
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• v.41 no.10
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• pp.105-113
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• 2004

This paper presents a design method for an asynchronous memory with a completion signal generation circuit meeting D-I model. The proposed design method is to generates a completion signal with dummy cell and a completion signal generation circuit to indicate completion of the required read or write operation to the processor. Dividing a memory exponentially to consider delay of a bit-line and a memory cell makes memory operates as a D-I model with minimum addition of redundant circuit. The proposed memory partitioning algorithm that divides entire memory into the several partitions with a exponentially increased size reduces the memory access delay by 40% compared with a conventional partitioning method to the same size.

• International Journal of Contents
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• v.5 no.2
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• pp.53-58
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• 2009

This paper presents a novel approach in the design of a CAM for an asynchronous cache. The architecture of cache mainly consists of four units: control logics, content addressable memory, completion signal logic units and instruction memory. The pseudo-DCVSL is useful to make a completion signal which is a reference for handshake control. The proposed CAM is a very simple extension of the basic circuitry that makes a completion signal based on DI model. The cache has 2.75KB CAM for 8KB instruction memory. We designed and simulated the proposed asynchronous cache including CAM. The results show that the cache hit ratio is up to 95% based on pseudo-LRU replacement policy.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.13 no.1
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• pp.206-221
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• 2019

Source localization in three-dimensional (3-D) wireless sensor networks (WSNs) is becoming a major research focus. Due to the complicated air-ground environments in 3-D positioning, many of the traditional localization methods, such as received signal strength (RSS) may have relatively poor accuracy performance. Benefit from prior learning mechanisms, fingerprinting-based localization methods are less sensitive to complex conditions and can provide relatively accurate localization performance. However, fingerprinting-based methods require training data at each grid point for constructing the fingerprint database, the overhead of which is very high, particularly for 3-D localization. Also, some of measured data may be unavailable due to the interference of a complicated environment. In this paper, we propose an efficient kernel based 3-D localization algorithm via tensor completion. We first exploit the spatial correlation of the RSS data and demonstrate the low rank property of the RSS data matrix. Based on this, a new training scheme is proposed that uses tensor completion to recover the missing data of the fingerprint database. Finally, we propose a kernel based learning technique in the matching phase to improve the sensitivity and accuracy in the final source position estimation. Simulation results show that our new method can effectively eliminate the impairment caused by incomplete sensing data to improve the localization performance.

• Architectural research
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• v.10 no.1
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• pp.41-48
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• 2008

Construction projects have frequently exceeded their schedule despite reliable estimates at the start of a project. This problem was attributed to unpredictable causes at the beginning and to shortage of proper tools to accurately predict project completion date. To supplement this difficulty, project managers need a comprehensive system that can be employed to monitor the progress of an ongoing project and to evaluate potential delay for achieving the goal on time. This paper proposed a progressive-based expert system for quantitative assessments of project delay at the early stages of the execution. Furthermore, the system is used to inspect the change of the uncertainty on completion date and its magnitude. The proposed expert system is helpful for furnishing project managers a warning signal as a project is going behind schedule and for tracking the changed uncertainty at a desired confidence level. The main objectives of this paper are to offer a new system to overcome the difficulties of conventional forecasting tools and to apply a construction project into the system to illustrate its effectiveness. This paper focuses on construction phase of project development and is intended for the use by project managers.

• International Journal of Contents
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• v.12 no.3
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• pp.22-28
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• 2016

Tensor with missing or incomplete values is a ubiquitous problem in various fields such as biomedical signal processing, image processing, and social network analysis. In this paper, we considered how to reconstruct a dataset with missing values by using tensor form which is called tensor completion process. We applied Tucker factorization to solve tensor completion which was built base on optimization problem. We formulated the optimization objective function using components of Tucker model after decomposing. The weighted least square matric contained only known values of the tensor with low rank in its modes. A first order optimization method, namely Nonlinear Conjugated Gradient, was applied to solve the optimization problem. We demonstrated the effectiveness of the proposed method in EEG signals with about 70% missing entries compared to other algorithms. The relative error was proposed to compare the difference between original tensor and the process output.

• Journal of Broadcast Engineering
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• v.27 no.6
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• pp.906-913
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• 2022

In this paper, we propose a new deep network architecture using nearest neighbor kernel for the estimation of dense depth map from its sparse map and corresponding color information. First, we propose to decompose the depth map signal into the structure and details for easier prediction. We then propose two separate subnetworks for prediction of both structure and details using classification and regression approaches, respectively. Moreover, the nearest neighboring kernel method has been newly proposed for accurate prediction of structure signal. As a result, the proposed method showed better results than other methods quantitatively and qualitatively.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.14 no.11
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• pp.5334-5337
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• 2013

In this paper, the structure of traffic lights removed the wire for the completion of urban aesthetics is analyzed. The finite element model consists of shell elements from three-dimensional CAD model of actual traffic signal. Traffic light pole, horizontal stand shape, thickness, stiffeners, etc. are considered in this study. Analysis of stress and deformation is performed by applying wind load. When the wind load is applied, the result on traffic signal is analyzed. This study is to perform the basic tasks for improving the design.

• The Journal of the Acoustical Society of Korea
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• v.41 no.4
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• pp.461-467
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• 2022

Sonobuoy is a disposable device that collects underwater acoustic information and is designed to transmit signals collected in a particular area to nearby aircraft or ships and sink to the seabed upon completion of its mission. In a conventional sonobouy signal transmission and reception system, collected signals are modulated and transmitted using techniques such as frequency division modulation or Gaussian frequency shift keying, and received and demodulated by an aircraft or a ship. However, this method has the disadvantage of the large amount of information to be transmitted and low security due to relatively simple modulation and demodulation methods. Therefore, in this paper, we propose a method that uses an autoencoder to encode a transmission signal into a low-dimensional latent vector to transmit the latent vector to an aircraft or ship and decode the received latent vector to improve signal security and to reduce the amount of transmission information by approximately a factor of a hundred compared to the conventional method. As a result of confirming the sample spectrogram reconstructed by the proposed method through simulation, it was confirmed that the original signal could be restored from a low-dimensional latent vector.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.13 no.8
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• pp.3880-3899
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• 2019

Distributive desynchronization algorithms based on pulse-coupled oscillator (PCO) models have been proposed for achieving collision-free wireless transmissions. These algorithms do not depend on a global clock or infrastructure overheads. Moreover, they gradually converge to fair time-division multiple access (TDMA) scheduling by broadcasting a periodic pulse signal (called a 'firing') and adjusting the next firing time based on firings from other nodes. The time required to achieve constant spacing between phase neighbors is estimated in a closed form or via stochastic modeling. However, because these algorithms cannot guarantee the completion of desynchronization in a short and bounded timeframe, they are not practical. Motivated by the limitations of these methods, we propose a practical solution called PD-DESYNC that provides a short and deterministic convergence time using a flag firing to indicate the beginning of a cycle. We demonstrate that the proposed method guarantees the completion of desynchronization within three cycles, regardless of the number of nodes. Through extensive simulations and experiments, we confirm that PD-DESYNC not only outperforms other algorithms in terms of convergence time but also is a practical solution.

• Journal of the Institute of Electronics Engineers of Korea SD
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• v.41 no.9
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• pp.57-64
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• 2004

In this paper, we propose a RZ/HRZ mixture data transmission method for the asynchronous circuit design to reduce Power consumption. The dual-rail data with Rf decoding scheme is used to design asynchronous circuit, and it is easy to get a completion signal of the data validity from the native data as contrasted with sin91e-rail. However, the dual-rail scheme suffers from large chip area and increasing of Power consumption from all signals by the switching of the return-to-zero. We need to diminish number of circuit switching. The proposed RZ/HRZ data transmission reduces a switching activity to about 50% and it shows 23% lower power consumption than the conventional dual-rail coding with RZ's.