• Smart Structures and Systems
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• 제21권4호
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• pp.521-535
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• 2018

The main purpose of this paper is to predict missing absolute out-of-plane displacements and failure limits of infill walls by artificial neural network (ANN) models. For this purpose, two shake table experiments are performed. These experiments are conducted on a 1:1 scale one-bay one-story reinforced concrete frame (RCF) with an infill wall. One of the experimental models is composed of unreinforced brick model (URB) enclosures with an RCF and other is composed of an infill wall with bed joint reinforcement (BJR) enclosures with an RCF. An artificial earthquake load is applied with four acceleration levels to the URB model and with five acceleration levels to the BJR model. After a certain acceleration level, the accelerometers are detached from the wall to prevent damage to them. The removal of these instruments results in missing data. The missing absolute maximum out-of-plane displacements are predicted with ANN models. Failure of the infill wall in the out-of-plane direction is also predicted at the 0.79 g acceleration level. An accuracy of 99% is obtained for the available data. In addition, a benchmark analysis with multiple regression is performed. This study validates that the ANN-based procedure estimates missing experimental data more accurately than multiple regression models.

• 한국GIS학회:학술대회논문집
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• 한국GIS학회 2010년도 춘계학술대회
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• pp.175-179
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• 2010

본 연구의 목적은 캠퍼스 내 설치된 CCTV의 현황과 설치환경을 파악하고, CCTV의 설치위치 주변 환경 기계적 성능 동을 고려하지 않을 때 발생하는 방범용 CCTV의 설치 및 운용에 문제점을 평가하는데 있다. CCTV의 설치 위치 평가를 위해 네트워크 분석을 활용 했으며, CCTV의 설치환경 분석을 위해서 기계적재원의 확인과 가로등 및 보안등의 조도측정이 이루어졌다. 그 결과 경북대학교 CCTV의 문제점은 크게 학생들의 보행패턴과 무관한 곳에 설치된 지역, 야간 촬영 시 요구되는 조도가 부족한 지역에 설치되어 있음이 확인 되었고, 44대의 CCTV 중 25대만이 범죄 예방이라는 소기의 목적을 위해 활용될 수 있음이 확인되었다.

• 전기전자학회논문지
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• 제22권3호
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• pp.672-679
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• 2018

Recently, microgrid (MG) has been proposed as one of the most critical solutions for various energy problems. For the optimal and economic operation of MGs, it is very important to forecast the load profile. However, it is not easy to predict the load accurately since the load in a MG is small and highly variable. In this paper, we propose an artificial neural network (ANN) based method to predict the energy use in campus buildings in short-term time series from one hour up to one week. The proposed method analyzes and extracts the features from the historical data of load and temperature to generate the prediction of future energy consumption in the building based on sparsified K-means. To evaluate the performance of the proposed approach, historical load data in hourly resolution collected from the campus buildings were used. The experimental results show that the proposed approach outperforms the conventional forecasting methods.

• 신재생에너지
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• 제18권1호
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• pp.35-45
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• 2022

The renewable energy based MG is becoming one of the prominent solutions for greenhouse gas and constructing less power lines. However, how to procure the economics of MG considering the CO₂ emission and utility network impact is one of major issues as the proportion of renewable resource increases. This paper proposes the feasibility study scheme of campus MG and shows that the LCOE and CO₂ emission can be reduced by utilizing the excess power and introducing hydrogen system and plus DR. For this, the three cases: (a) adding the PV and selling excess power to utility, (b) producing and selling hydrogen using excess power, and (c) participating in plus DR are considered. For each case, not only the topology and component capacity of MG to secure economic feasibility, but also CO₂ emission and utility network effects are derived. If an electrolyzer with a capacity of 400 kW participates in plus DR for 3,730hours/year, the economic feasibility is securable if plus DR settlement and hydrogen sale price are more than 7.08¢/kWh and 8.3USD/kg or 6.25¢/kWh and 8.6USD/kg, respectively. For this end, continuous technical development and policy support for hydrogen system and plus DR are required.

• The Journal of Asian Finance, Economics and Business
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• 제9권3호
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• pp.203-215
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• 2022

Bayesian Networks are multivariate probabilistic factor graphs that are used to assess underlying factor relationships. From January 2005 to December 2018, the study examines how Dynamic Bayesian Networks can be utilized to estimate portfolio risk and return as well as determine inter-factor relationships among reversal profit-generating components in Pakistan's emerging market (PSX). The goal of this article is to uncover the factors that cause reversal profits in the Pakistani stock market. In visual form, Bayesian networks can generate causal and inferential probabilistic relationships. Investors might update their stock return values in the network simultaneously with fresh market information, resulting in a dynamic shift in portfolio risk distribution across the networks. The findings show that investments in low net profit margin, low investment, and high volatility-based designed portfolios yield the biggest dynamical reversal profits. The main triggering aspects related to generation reversal profits in the Pakistan market, in the long run, are net profit margin, market risk premium, investment, size, and volatility factor. Investors should invest in and build portfolios with small companies that have a low price-to-earnings ratio, small earnings per share, and minimal volatility, according to the most likely explanation.

• International Journal of Computer Science & Network Security
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• 제24권4호
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• pp.147-154
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• 2024

The continuous increase in urban population due to migration of mases from rural areas to big cities has set urban water supply under serious stress. Urban water resources face scarcity of available water quantity, which ultimately effects the water supply. It is high time to address this challenging problem by taking appropriate measures for the improvement of water utility services linked with better understanding of demand side management (DSM), which leads to an effective state of water supply governance. We propose a dynamic framework for preventive DSM that results in optimization of water resource management. This paper uses Agent Based Modeling (ABM) with Digital Twin (DT) to model water consumption behavior of a population and consequently forecast water demand. DT creates a digital clone of the system using physical model, sensors, and data analytics to integrate multi-physical quantities. By doing so, the proposed model replicates the physical settings to perform the remote monitoring and controlling jobs on the digital format, whilst offering support in decision making to the relevant authorities.

• International Journal of Computer Science & Network Security
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• 제24권5호
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• pp.103-110
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• 2024

In the quickly developing world, the idea of the conventional advancement needs to advance[1]. When applied to the advanced work environment, the conventional strategies give as much damage as they do great. Tragically, an absence of versatility in the customary techniques has prompted an inflexible work structure that is truly not viable with the present business. The Agile technique is, subsequently, a more adequate practice, in view of creating programming at a faster speed, while as yet looking after proficiency. The coordinated programming improvement strategies are concentrated in this paper. As per study results, Agile software development group needs solid client association; great light-footed task the executives' measures; item proprietor expands business esteem conveyed by group and need and draw in partners; great deft designing procedures or practices; and great advancements and advancement apparatuses[2]. This examination has suggestions for positive social change since associations that comprehend the basic components might have the option to improve project the executives' systems and money saving advantages prompting higher effectiveness, productivity, and efficiency hence profiting the board, representatives, and client. This survey paper incorporates various methodologies of Agile and their analysis.

• Bulletin of the Korean Chemical Society
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• 제33권6호
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• pp.2017-2022
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• 2012

Three isostructural lanthanide coordination polymers, $[Ln(L)_3(H_2O)_2](H_2O)_3$ {Ln = Eu (1), Tb (2), Gd (3); L = $trans$-3-(3-pyridyl)acrylate, (3-py)-CH=CH-COO}, were prepared from HL, lanthanide nitrate, and NaOH in $H_2O$ by microwave heating. In all coordination polymers, the metal is bonded to eight oxygen atoms, and all pyridyl nitrogen atoms do not coordinate to the metals. All polymers have a 1-D loop-connected chain structure. The hydrogen atoms in the aqua ligands and lattice water molecules all participate in the hydrogen bonds of the O-$H{\cdots}O$ or O-$H{\cdots}N$ type. The hydrogen bonds connect the 1-D chains to create a 2-D network. Polymer 1 exhibited red luminescence in the solid state at room temperature.

• IMMUNE NETWORK
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• 제21권6호
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• pp.45.1-45.13
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• 2021

Many mouse models of rheumatoid arthritis have been identified, but only a limited number are present for axial spondyloarthritis (AxSpA). Collagen Ab-induced arthritis (CAIA) is one of the most widely used mouse models of arthritis, and it is complement-dependent. We found that mice developing CAIA also developed spinal lesions similar to those found in AxSpA. To induce CAIA, mice were injected intraperitoneally at day 0 with anti-collagen Abs, followed by LPS injection at day 3. CAIA mice demonstrated a significant kyphosis through the spine, as well as hypertrophic cartilage and osseous damage of the intravertebral joints. Immunohistochemical staining of the kyphotic area revealed increased complement C3 deposition and macrophage infiltration, with localization to the intravertebral joint margins. Near Infrared (NIR) in vivo imaging showed that anti-collagen Abs conjugated with IRDye^® 800CW not only localized to cartilage surface in the joints but also to the spine in arthritic mice. We report here a novel preclinical mouse model in which, associated with the induction of CAIA, mice also exhibited salient features of AxSpA; this new experimental model of AxSpA may allow investigators to shed light on the local causal mechanisms of AxSpA bone and soft tissue changes as well as treatment.

• 한국산업경영시스템학회:학술대회논문집
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• 한국산업경영시스템학회 2002년도 춘계학술대회
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• pp.105-111
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• 2002

Presented is a Genetic Algorithm(GA) for dynamic partitioning an ATM LANE(LAN Emulation) network. LANE proves to be one of the best solutions to provide guaranteed Quality of Service(QoS) for mid-size campus or enterprise networks with a little modification of legacy LAN facilities. However, there are few researches on the efficient LANE network operations to deal with scalability issues arising from broadcast traffic delivery. To cope with this scalability issue, proposed is a decision model named LANE Partitioning Problem(LPP) which aims at partitioning the entire LANE network into multiple Emulated LANs(ELANs), each of which works as an independent virtual LAN.