• The Korean Journal of Applied Statistics
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• v.35 no.1
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• pp.49-62
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• 2022

Realized volatility is well known to have long memory, strong association with other global financial markets and interdependences among macroeconomic indices such as exchange rate, oil price and interest rates. This paper proposes autoencoder factor-augmented heterogeneous autoregressive (AE-FAHAR) model for realized volatility forecasting. AE-FAHAR incorporates long memory using HAR structure, and exogenous variables into few factors summarized by autoencoder. Autoencoder requires intensive calculation due to its nonlinear structure, however, it is more suitable to summarize complex, possibly nonstationary high-dimensional time series. Our AE-FAHAR model is shown to have smaller out-of-sample forecasting error in empirical analysis. We also discuss pre-training, ensemble in autoencoder to reduce computational cost and estimation errors.

• Journal of Information Processing Systems
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• v.17 no.2
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• pp.242-252
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• 2021

Following the intuition that the local information in time instances is hardly incorporated into the posterior sequence in long short-term memory (LSTM), this paper proposes an attention augmented mechanism for fault diagnosis of the complex chemical process data. Unlike conventional fault diagnosis and classification methods, an attention mechanism layer architecture is introduced to detect and focus on local temporal information. The augmented deep network results preserve each local instance's importance and contribution and allow the interpretable feature representation and classification simultaneously. The comprehensive comparative analyses demonstrate that the developed model has a high-quality fault classification rate of 95.49%, on average. The results are comparable to those obtained using various other techniques for the Tennessee Eastman benchmark process.

• Journal of the Korean Society for Library and Information Science
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• v.44 no.4
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• pp.33-59
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• 2010

Library 2.0 advocates a socially rich, multimedia enabled, user originated and communally innovative environment that poses significant opportunities for the libraries to evolve and make themselves even more relevant and significant for her users. This paper presents a case study of the National Library Board of Singapore, in playing a vital role to facilitate the realisation of a long-term key national program, The Singapore Memory (SM) Project. SM embraces the attributes of the Library 2.0 environment to enable the nation's memory to be collected, organised, preserved, discovered, researched, augmented and created. The output of is an evolving collection of knowledge assets on Singapore along a Singapore Memory Content Continuum of existing content that is steadily augmented with new content. The content will be collected across all formats, in any language, from Singaporeans and non-Singaporeans, from any institution and agency, from Singapore and abroad, and from official and unofficial sources. The utopian scenario of SM Project is that any person, community, group or institution who has ever experienced Singapore in any way or has any material on Singapore will engage actively in the contribution, discovery and creation of content for the project, and thus become advocates to further encourage and catalyse more contribution, discovery and creation. The paper outlines the key approaches, concepts and ideas for the project. An important element is the proliferation, exposure and accessibility of the rich contents envisaged in the project. The SM proliferation plan along with examples of how two existing resources, namely, the Singapore Infopedia, a database of articles on Singapore's history, culture, people and events 4 and NewspaperSG, an online resource of current and historic Singapore and Malayan newspapers, have been designed are presented to demonstrate how content can be exposed, searched and discovered.

• Journal of the Korea Society of Computer and Information
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• v.17 no.1
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• pp.97-104
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• 2012

Natural User Interface(NUI) technologies introduce new trends in using devices such as computer and any other electronic devices. In this paper, an augmented reality on a mobile device is implemented by using face detection, recognition and motion tracking. The face detection is obtained by using Viola-Jones algorithm from the images of the front camera. The Eigenface algorithm is employed for face recognition and face motion tracking. The augmented reality is implemented by overlapping the rear camera image and GPS, accelerator sensors' data with the 3D graphic object which is correspond with the recognized face. The algorithms and methods are limited by the mobile device specification such as processing ability and main memory capacity.

• Transactions of the Korean Society of Mechanical Engineers
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• v.19 no.1
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• pp.263-270
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• 1995

The use of the shape memory alloy, Nitinol wire, is investigated as an actuator for enhancing the damping in structural vibration systems. The first-order mathematical model of the Nitinol wire is obtained from the experimental data for an actuator. Finite element method is utilized for the strain gage sensor model, which is installed at the root of cantilever beam. A simple system, cantilever beam, is built as a flexible structural system to implement a control law with the Nitinol wire actuator. The system model including sensor and actuator is derived, which agrees with the experimental results. The actuator dynamics is augmented with the system so as to design PI controller and the one of robust controllers, LQG/LTR controller, and the control laws are implemented experimentally. The experimental study shows the feasibility of utilizing the Nitinol wire as an actuator for the purpose of vibration control.

• The Transactions of the Korea Information Processing Society
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• v.4 no.9
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• pp.2259-2268
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• 1997

Multistage interconnection networks(MINs) provide a high-bandwidth communication between processors and/or memory modules in a cost-effective way. In this paper, we propose a class of multipath MINs, called the Augmented Modified Delta(AMD) network, and analyze its performance and reliability. The salient features of the AMD network include fault-tolerant capability, modular structure, and high performance, which are essential for real-time parallel/distributed processing environments. The class of the AMD network retains well-known characteristics of the Kappa network, but it's design procedure is more systematic. Like Delta networks, all the AMD networks are topologically equivalent with each other.

• Journal of the Korean Institute of Telematics and Electronics
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• v.25 no.8
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• pp.972-982
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• 1988

In multiprocessor systems, there are Omega network and M network among various MIN's which interconnect the processor and memory modules. Both one-path Omega network and two-path M network are composed of Log2N stages. In this paper, Augmented M network (AMN) with 2**k+1 paths and Augmented Omega network (AON) with 2**k paths are proposed. The proposed networks can be acomplished by adding K stage(s) to M network and Omega network. Using destination tag, routing algorithm for AMN and AON becomes simple and multiple faults are tolerant. By evaluating RST(request service time) performance of AMN and AON with (Log2N)+K stages, we demonstrated the fact that MMIN (AMN) with 2**k+1 paths performs better than MMIN(AON) with 2**k+1. paths.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.15 no.3
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• pp.837-852
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• 2021

Recurrent neural network (RNN) architectures have been used for language modeling (LM) tasks that require learning long-range word or character sequences. However, the RNN architecture is still suffered from unstable gradients on long-range sequences. To address the issue of long-range sequences, an attention mechanism has been used, showing state-of-the-art (SOTA) performance in all LM tasks. A differentiable neural computer (DNC) is a deep learning architecture using an attention mechanism. The DNC architecture is a neural network augmented with a content-addressable external memory. However, in the write operation, some information unrelated to the input word remains in memory. Moreover, DNCs have been found to perform poorly with low numbers of weight parameters. Therefore, we propose a robust memory deallocation method using a limited retention vector. The limited retention vector determines whether the network increases or decreases its usage of information in external memory according to a threshold. We experimentally evaluate the robustness of a DNC implementing the proposed approach according to the size of the controller and external memory on the enwik8 LM task. When we decreased the number of weight parameters by 32.47%, the proposed DNC showed a low bits-per-character (BPC) degradation of 4.30%, demonstrating the effectiveness of our approach in language modeling tasks.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2018.05a
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• pp.622-624
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• 2018

인간에게 경험이란 삶의 흔적이며 과정이다. 어떤 경험을 했는지, 느낌을 갖게 되었는지, 본적이 있는지, 만진 적이 있는지 등 다양한 인지 요소들은 그 기억만으로 그 인간의 특성이 되고 성질이 된다. 이러한 모든 경우를 재인이라고 한다. 이러한 기억 인출 단서들이 현존감이 강한 가상환경에서 발견되느냐, 발견되지 않느냐에 따라 미디어적 환상성이 아닌 사용자에게 가상에서의 '현실'을 제공하는 중요 요소로 작용할 것이다. 또한 가상현실 콘텐츠의 이해가 미숙한 사용자라도 가상환경에서 선행경험에 대한 재인요소를 제공받을 수 있는 중요한 단서가 될 수 있다면, 콘텐츠에 대한 높은 만족감을 기대할 수 있을 것이다. 본 연구는 가상현실 콘텐츠의 만족도를 올리는 요소로서, 재인에 대하여 고찰하고 개인의 재인과 가상현실 콘텐츠 만족과의 상관관계를 연구하여 양질의 콘텐츠 서비스를 제공하는데 기여하고 가상현실을 경험하는 사용자의 심리적인 영역까지 이해의 폭을 넓히고자 함이다.

• Smart Structures and Systems
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• v.24 no.3
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• pp.361-377
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• 2019

The stiffness of shape memory alloy (SMA) spring while in actuation is represented by an empirical model that is derived from the logistic differential equation. This model correlates the stiffness to the alloy temperature and the functionality of SMA spring as active variable stiffness actuator (VSA) is analyzed based on factors that are the input conditions (activation current, duty cycle and excitation frequency) and operating conditions (pre-stress and mechanical connection). The model parameters are estimated by adopting the nonlinear least square method, henceforth, the model is validated experimentally. The average correlation factor of 0.95 between the model response and experimental results validates the proposed model. In furtherance, the justification is augmented from the comparison with existing stiffness models (logistic curve model and polynomial model). The important distinction from several observations regarding the comparison of the model prediction with the experimental states that it is more superior, flexible and adaptable than the existing. The nature of stiffness variation in the SMA spring is assessed also from the Dynamic Mechanical Thermal Analysis (DMTA), which as well proves the proposal. This model advances the ability to use SMA integrated mechanism for enhanced variable stiffness actuation. The investigation proves that the stiffness of SMA spring may be altered under controlled conditions.