• Title/Summary/Keyword: smart aggregate

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Two-dimensional water seepage monitoring in concrete structures using smart aggregates

  • Zou, Dujian;Li, Weijie;Liu, Tiejun;Teng, Jun
    • Structural Monitoring and Maintenance
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    • v.5 no.2
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    • pp.313-323
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    • 2018
  • The presence of water inside concrete structures is an essential condition for the deterioration of the structures. The free water in the concrete pores and micro-cracks is the culprit for the durability related problems, such as alkali-aggregate reaction, carbonation, freeze-thaw damage, and corrosion of steel reinforcement. To ensure the integrity and safe operation of the concrete structures, it is very important to monitor water seepage inside the concrete. This paper presents the experimental investigation of water seepage monitoring in a concrete slab using piezoelectric-based smart aggregates. In the experimental setup, an $800mm{\times}800mm{\times}100mm$ concrete slab was fabricated with 15 SAs distributed inside the slab. The water seepage process was monitored through interrogating the SA pairs. In each SA pair, one SA was used as actuator to emit harmonic sine wave, and the other was used as sensor to receive the transmitted stress wave. The amplitudes of the received signals were able to indicate the water seepage process inside the concrete slab.

Swarm-based hybridizations of neural network for predicting the concrete strength

  • Ma, Xinyan;Foong, Loke Kok;Morasaei, Armin;Ghabussi, Aria;Lyu, Zongjie
    • Smart Structures and Systems
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    • v.26 no.2
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    • pp.241-251
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    • 2020
  • Due to the undeniable importance of approximating the concrete compressive strength (CSC) in civil engineering, this paper focuses on presenting four novel optimizations of multi-layer perceptron (MLP) neural network, namely artificial bee colony (ABC-MLP), grasshopper optimization algorithm (GOA-MLP), shuffled frog leaping algorithm (SFLA-MLP), and salp swarm algorithm (SSA-MLP) for predicting this crucial parameter. The used dataset consists of 103 rows of information concerning seven influential parameters (cement, slag, water, fly ash, superplasticizer, fine aggregate, and coarse aggregate). In this work, the best-fitted complexity of each ensemble is determined by a population-based sensitivity analysis. The GOA distinguished its self by the least complexity (population size = 50) and emerged as the second time-effective optimizer. Referring to the prediction results, all tested algorithms are able to construct reliable networks. However, the SSA (Correlation = 0.9652 and Error = 1.3939) and GOA (Correlation = 0.9629 and Error = 1.3922) performed more accurately than ABC (Correlation = 0.7060 and Error = 4.0161) and SFLA (Correlation = 0.8890 and Error = 2.5480). Therefore, the SSA-MLP and GOA-MLP can be promising alternatives to laboratorial and traditional CSC evaluative methods.

Metaheuristic-reinforced neural network for predicting the compressive strength of concrete

  • Hu, Pan;Moradi, Zohre;Ali, H. Elhosiny;Foong, Loke Kok
    • Smart Structures and Systems
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    • v.30 no.2
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    • pp.195-207
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    • 2022
  • Computational drawbacks associated with regular predictive models have motivated engineers to use hybrid techniques in dealing with complex engineering tasks like simulating the compressive strength of concrete (CSC). This study evaluates the efficiency of tree potential metaheuristic schemes, namely shuffled complex evolution (SCE), multi-verse optimizer (MVO), and beetle antennae search (BAS) for optimizing the performance of a multi-layer perceptron (MLP) system. The models are fed by the information of 1030 concrete specimens (where the amount of cement, blast furnace slag (BFS), fly ash (FA1), water, superplasticizer (SP), coarse aggregate (CA), and fine aggregate (FA2) are taken as independent factors). The results of the ensembles are compared to unreinforced MLP to examine improvements resulted from the incorporation of the SCE, MVO, and BAS. It was shown that these algorithms can considerably enhance the training and prediction accuracy of the MLP. Overall, the proposed models are capable of presenting an early, inexpensive, and reliable prediction of the CSC. Due to the higher accuracy of the BAS-based model, a predictive formula is extracted from this algorithm.

The Influence of the Introduction of Smart Phone on Using Portal Sites: An Exploratory Study by the Analysis on Smart Phone Users' Web Traffic (스마트폰 도입이 포털사이트 이용에 미친 영향: 스마트폰 이용자의 웹 트래픽 분석을 통한 탐색적 연구)

  • Kim, Wi-Geun
    • Korean journal of communication and information
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    • v.64
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    • pp.109-135
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    • 2013
  • This study is for empirical verification of the influence of the introduction of smart phone on using the portal sites that were affected the most in the previous media environment. To achieve this, Web traffic data that are the result of smart phone users' practical Web uses have collected longitudinally and analyzed. The research results are the following: First, the use hours of portal sites have decreased about 15% and the page views have did about 35%, since using smart phones was diffused and habituated in earnest during the past two years. Using the community, news media, video, mobile, and game section of portal site sections have reduced. Second, the portal site portion of using smart phone Web is much more than that portion of using PC Web. More than two thirds of smart phone Web use traffic occurs in using portal sites, while more than one third of PC Web use traffic does in using that. Using the news media section is the most of using portal site sections on a smart phone. Third, since the introduction of smart phone, using the news media, communication, and life section of portal site sections have greatly increased, while the community, mobile, and game section have greatly decreased in the aggregate.

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Implementation of Secure System for Blockchain-based Smart Meter Aggregation (블록체인 기반 스마트 미터 집계 보안 시스템 구축)

  • Kim, Yong-Gil;Moon, Kyung-Il
    • The Journal of the Institute of Internet, Broadcasting and Communication
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    • v.20 no.2
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    • pp.1-11
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    • 2020
  • As an important basic building block of the smart grid environment, smart meter provides real-time electricity consumption information to the utility. However, ensuring information security and privacy in the smart meter data aggregation process is a non-trivial task. Even though the secure data aggregation for the smart meter has been a lot of attention from both academic and industry researchers in recent years, most of these studies are not secure against internal attackers or cannot provide data integrity. Besides, their computation costs are not satisfactory because the bilinear pairing operation or the hash-to-point operation is performed at the smart meter system. Recently, blockchains or distributed ledgers are an emerging technology that has drawn considerable interest from energy supply firms, startups, technology developers, financial institutions, national governments and the academic community. In particular, blockchains are identified as having the potential to bring significant benefits and innovation for the electricity consumption network. This study suggests a distributed, privacy-preserving, and simple secure smart meter data aggregation system, backed up by Blockchain technology. Smart meter data are aggregated and verified by a hierarchical Merkle tree, in which the consensus protocol is supported by the practical Byzantine fault tolerance algorithm.

Effect of Loading Rate on Self-stress Sensing Capacity of the Smart UHPC (하중 속도가 Smart UHPC의 자가 응력 감지 성능에 미치는 영향)

  • Lee, Seon Yeol;Kim, Min Kyoung;Kim, Dong Joo
    • Journal of the Korea Academia-Industrial cooperation Society
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    • v.22 no.5
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    • pp.81-88
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    • 2021
  • Structural health monitoring (SHM) systems have attracted considerable interest owing to the frequent earthquakes over the last decade. Smart concrete is a technology that can analyze the state of structures based on their electro-mechanical behavior. On the other hand, most research on the self-sensing response of smart concrete generally investigated the electro-mechanical behavior of smart concrete under a static loading rate, even though the loading rate under an earthquake would be much faster than the static rate. Thus, this study evaluated the electro-mechanical behavior of smart ultra-high-performance concrete (S-UHPC) at three different loading rates (1, 4, and 8 mm/min) using a Universal Testing Machine (UTM). The stress-sensitive coefficient (SC) at the maximum compressive strength of S-UHPC was -0.140 %/MPa based on a loading rate of 1 mm/min but decreased by 42.8% and 72.7% as the loading rate was increased to 4 and 8 mm/min, respectively. Although the sensing capability of S-UHPC decreased with increased load speed due to the reduced deformation of conductive materials and increased microcrack, it was available for SHM systems for earthquake detection in structures.

Sequential sampling method for monitoring potato tuber moths (Phthorimaea operculella) in potato fields

  • Jung, Jae-Min;Byeon, Dae-hyeon;Kim, Eunji;Byun, Hye-Min;Park, Jaekook;Kim, Jihoon;Bae, Jongmin;Kim, Kyutae;Roca-Cusachs, Marcos;Kang, Minjoon;Choi, Subin;Oh, Sumin;Jung, Sunghoon;Lee, Wang-Hee
    • Korean Journal of Agricultural Science
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    • v.47 no.3
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    • pp.615-624
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    • 2020
  • An effective sampling method is necessary to monitor potato tuber moths (Phthorimaea operculella) because they are the biggest concern in potato-cultivating areas. In this study, a sequential sampling method was developed based on the results of field surveys of potato tuber moths in South Korea. Potato tuber moths were collected in fields cultivating potatoes at six sites, and their spatial distribution was investigated using the Taylor power law. The optimal sampling size and cumulative number of potato tuber moths in traps to stop sampling were determined based on the spatial distribution pattern and mean density of the collected potato tuber moths. Finally, the developed sampling method was applied to propose a control action, and its sampling efficiency was compared with that of the traditional sampling method using a binomial distribution. The potato tuber moths tended to aggregate; the optimal number was approximately 5 - 16 traps for sampling, and the number varied with the mean density of potato tuber moths according to the sampling sites. In addition, one, two, and three sites might require the following actions: Continued sampling, control, and no control, respectively. Sampling with the binomial distribution showed the minimum sample size was 12 when considering the economic threshold level. Here, we propose an effective sampling method that can be applied for future monitoring and field surveys of potato tuber moths in South Korea.

An exploratory study of stress wave communication in concrete structures

  • Ji, Qing;Ho, Michael;Zheng, Rong;Ding, Zhi;Song, Gangbing
    • Smart Structures and Systems
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    • v.15 no.1
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    • pp.135-150
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    • 2015
  • Large concrete structures are prone to cracks and damages over time from human usage, weathers, and other environmental attacks such as flood, earthquakes, and hurricanes. The health of the concrete structures should be monitored regularly to ensure safety. A reliable method of real time communications can facilitate more frequent structural health monitoring (SHM) updates from hard to reach positions, enabling crack detections of embedded concrete structures as they occur to avoid catastrophic failures. By implementing an unconventional mode of communication that utilizes guided stress waves traveling along the concrete structure itself, we may be able to free structural health monitoring from costly (re-)installation of communication wires. In stress-wave communications, piezoelectric transducers can act as actuators and sensors to send and receive modulated signals carrying concrete status information. The new generation of lead zirconate titanate (PZT) based smart aggregates cause multipath propagation in the homogeneous concrete channel, which presents both an opportunity and a challenge for multiple sensors communication. We propose a time reversal based pulse position modulation (TR-PPM) communication for stress wave communication within the concrete structure to combat multipath channel dispersion. Experimental results demonstrate successful transmission and recovery of TR-PPM using stress waves. Compared with PPM, we can achieve higher data rate and longer link distance via TR-PPM. Furthermore, TR-PPM remains effective under low signal-to-noise (SNR) ratio. This work also lays the foundation for implementing multiple-input multiple-output (MIMO) stress wave communication networks in concrete channels.

Simulated Dynamic C&C Server Based Activated Evidence Aggregation of Evasive Server-Side Polymorphic Mobile Malware on Android

  • Lee, Han Seong;Lee, Hyung-Woo
    • International journal of advanced smart convergence
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    • v.6 no.1
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    • pp.1-8
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    • 2017
  • Diverse types of malicious code such as evasive Server-side Polymorphic are developed and distributed in third party open markets. The suspicious new type of polymorphic malware has the ability to actively change and morph its internal data dynamically. As a result, it is very hard to detect this type of suspicious transaction as an evidence of Server-side polymorphic mobile malware because its C&C server was shut downed or an IP address of remote controlling C&C server was changed irregularly. Therefore, we implemented Simulated C&C Server to aggregate activated events perfectly from various Server-side polymorphic mobile malware. Using proposed Simulated C&C Server, we can proof completely and classify veiled server-side polymorphic malicious code more clearly.

Modeling shear capacity of RC slender beams without stirrups using genetic algorithms

  • Nehdi, M.;Greenough, T.
    • Smart Structures and Systems
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    • v.3 no.1
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    • pp.51-68
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    • 2007
  • High-strength concrete (HSC) is becoming increasingly attractive for various construction projects since it offers a multitude of benefits over normal-strength concrete (NSC). Unfortunately, current design provisions for shear capacity of RC slender beams are generally based on data developed for NSC members having a compressive strength of up to 50 MPa, with limited recommendations on the use of HSC. The failure of HSC beams is noticeably different than that of NSC beams since the transition zone between the cement paste and aggregates is much denser in HSC. Thus, unlike NSC beams in which micro-cracks propagate around aggregates, providing significant aggregate interlock, micro-cracks in HSC are trans-granular, resulting in relatively smoother fracture surfaces, thereby inhibiting aggregate interlock as a shear transfer mechanism and reducing the influence of compressive strength on the ultimate shear strength of HSC beams. In this study, a new approach based on genetic algorithms (GAs) was used to predict the shear capacity of both NSC and HSC slender beams without shear reinforcement. Shear capacity predictions of the GA model were compared to calculations of four other commonly used methods: the ACI method, CSA method, Eurocode-2, and Zsutty's equation. A parametric study was conducted to evaluate the ability of the GA model to capture the effect of basic shear design parameters on the behaviour of reinforced concrete (RC) beams under shear loading. The parameters investigated include compressivestrength, amount of longitudinal reinforcement, and beam's depth. It was found that the GA model provided more accurate evaluation of shear capacity compared to that of the other common methods and better captured the influence of the significant shear design parameters. Therefore, the GA model offers an attractive user-friendly alternative to conventional shear design methods.