• Advances in Computational Design
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• v.8 no.1
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• pp.37-59
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• 2023

Squat reinforced concrete (SRC) shear walls are a critical part of the structure for both office/residential buildings and nuclear structures due to their significant role in withstanding seismic loads. Despite this, empirical formulae in current design standards and published studies demonstrate a considerable disparity in predicting SRC wall shear strength. The goal of this research is to develop and evaluate hybrid and ensemble artificial neural network (ANN) models. State-of-the-art population-based algorithms are used in this research for hybrid intelligence algorithms. Six models are developed, including Honey Badger Algorithm (HBA) with ANN (HBA-ANN), Hunger Games Search with ANN (HGS-ANN), fitness-distance balance coyote optimization algorithm (FDB-COA) with ANN (FDB-COA-ANN), Averaging Ensemble (AE) neural network, Snapshot Ensemble (SE) neural network, and Stacked Generalization (SG) ensemble neural network. A total of 434 test results of SRC walls is utilized to train and assess the models. The results reveal that the SG model not only minimizes prediction variance but also produces predictions (with R²= 0.99) that are superior to other models.

• Steel and Composite Structures
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• v.51 no.6
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• pp.713-727
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• 2024

Damage detection in structures using the change of modal parameters (modal shapes and natural frequencies) has achieved satisfactory results. However, as modal shapes and natural frequencies alone may not provide enough information to accurately detect damages. Therefore, a hybrid singular value decomposition and deep belief network approach is developed to effectively identify damages in aluminum plate structures. Firstly, damage locations are determined using singular value decomposition (SVD) to reveal the singularities of measured displacement modal shapes. Secondly, using experimental modal analysis (EMA) to measure the natural frequencies of damaged aluminum plates as inputs, deep belief network (DBN) is employed to search damage severities from the damage evaluation database, which are calculated using finite element method (FEM). Both simulations and experimental investigations are performed to evaluate the performance of the presented hybrid method. Several damage cases in a simply supported aluminum plate show that the presented method is effective to identify multiple damages in aluminum plates with reasonable precision.

• Journal of the Korea Society of Computer and Information
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• v.23 no.9
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• pp.35-42
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• 2018

In this paper, we propose an optimal streaming service method based on Hybrid CDN/P2P architecture. Recently, video streaming utilizes a CDN (Content Delivery Network) operation technique based on a Proxy Server, which is an end node located close to a user. However, since CDN has a fixed network traffic bandwidth and data information exchange among CDNs in the network is not smooth, it is difficult to guarantee traffic congestion and quality of image service. In the hybrid CDN/P2P network, a data selection technique is used to select only the data that is expected to be continuously requested among all the data in order to guarantee the QoS of the user who utilizes the limited bandwidth efficiently. In order to search user requested data, this technique effectively retrieves the storage information of the constituent nodes of CDN and P2P, and stores the new image information and calculates the deletion priority based on the request possibility as needed. Therefore, the streaming service scheme proposed in this paper can effectively improve the quality of the video streaming service on the network.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.13 no.9
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• pp.1905-1912
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• 2009

Clustering results based on the FCM algorithm sometimes produces undesirable clustering result through data distribution in the clustered space because data is classified by comparison with membership degree which is calculated by the Euclidean distance between input vectors and clusters. Symmetrical measurement of clusters and fuzzy theory are applied to the classification to tackle this problem. The enhanced FCM algorithm has a low impact with the variation of changing distance about each cluster, middle of cluster and cluster formation. Improved hybrid network of applying FCM algorithm is proposed to classify patterns effectively. The proposed enhanced FCM algorithm is applied to the learning structure between input and middle layers, and normalized delta learning rule is applied in learning stage between middle and output layers in the hybrid network. The proposed algorithms compared with FCM-based RBF network using Max_Min neural network, FMC-based RBF network and HCM-based RBF network to evaluate learning and recognition performances in the two-dimensional coordinated data.

• Journal of Korea Society of Industrial Information Systems
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• v.22 no.1
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• pp.1-9
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• 2017

With the Development of Wireless Network Technology and Wireless Link Technology, Wireless Mesh Network (WMN) is Attracting Attention as a Key Technology to Construct the Wireless Transit Network. The WMN has been Studied for a Long Time in Various Fields, however there are still many Problems that have not been solved yet. One of them is the Routing Problem to find an Optimal path in a Multi-hop Network Composed of Wireless Links. In the Hybrid-WMN, which is one of the Three Types of WMN, Optimal Path Selection Requires Research on Path Search Protocols that Effectively use the Infrastructure Mesh as a Transit Network, Together with Research for a Routing Metric with Excellent Performance. Therefore, this Paper Proposes a Dual Mode-AODV(Ad hoc On-demand Distance Vector) for Hybrid-WMN. Simulation result shows that the Path Selection Delay was Reduced by 52% than AODV when the Proposed Dual Mode-AODV was applied.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.5 no.11
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• pp.2143-2159
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• 2011

The hybrid architecture of content delivery networks (CDN) and peer-to-peer overlay networks (P2P) is a promising technology enables effective real-time streaming services. It complements the advantages of quality control and reliability in a CDN, and the scalability of a P2P system. With real-time streaming services, however, high connection setup and media delivery latency are becoming the critical issues in deploying the CDN-P2P system. These issues result from biased peer selection without location awareness or content awareness, and can lead to significant service disruption. To reduce service disruption latency, we propose a group-based CDN-P2P hybrid architecture (iCDN-P2P) with a location/content-aware selection of peers. Specifically, a SuperPeer network makes a location-aware peer selection by employing a content addressable network (CAN) to distribute channel information. It also manages peers with content awareness, forming a group of peers with the same channel as the sub-overlay. Through a performance evaluation, we show that the proposed architecture outperforms the original CDN-P2P hybrid architecture in terms of connection setup delay and media delivery time.

• Journal of Electrical Engineering and Technology
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• v.13 no.2
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• pp.568-579
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• 2018

Virtual power plants can be regarded as systems that have entered the network after restructure of power systems. In fact, these plants are a set of consumers capable of consuming and generating power. In response to widespread implementation of plug-in hybrid electric vehicles, further investigation of energy management in this type of power plants seems to be of great value. In effect, these vehicles are able to receive and inject power from/into the network. Hence, study of the effects of these vehicles on management of virtual power plants seems to be illuminative. In this paper, management of power consumption/generation in virtual power plants has been investigated in the presence of hybrid electric vehicles. The objective function of virtual power plants problem management is to minimize the overall costs including not only the costs of energy production in power generation units, fuels, and degradation of batteries of vehicles, but also the costs of purchasing electricity from the network. Furthermore, the constraints on the operational of plants, loads and hybrid vehicles, level of penalty for greenhouse gas emissions ($CO_2$ and $NO_x$) produced by power plants and vehicles, and demand response to the immediate price of market have all been attended to in the present study. GAMS/Cplex software system and sample power system have been employed to pursue computer implementation and simulation.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.15 no.9
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• pp.3151-3168
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• 2021

Internet of Things (IoT) connects several objects with embedded sensors and they are capable of exchanging information between devices to create a smart environment. IoT smart devices have limited resources, such as batteries, computing power, and bandwidth, but comprehensive sensing causes severe energy restrictions, lowering data quality. The main objective of the proposal is to build a hybrid protocol which provides high data quality and reduced energy consumption in IoT sensor network. The hybrid protocol gives a flexible and complete solution for sensor selection problem. It selects a subset of active sensor nodes in the network which will increase the data quality and optimize the energy consumption. Since the unused sensor nodes switch off during the sensing phase, the energy consumption is greatly reduced. The hybrid protocol uses Dijkstra's algorithm for determining the shortest path for sensing data and Ant colony inspired variable path selection algorithm for selecting active nodes in the network. The missing data due to inactive sensor nodes is reconstructed using enhanced belief propagation algorithm. The proposed hybrid method is evaluated using real sensor data and the demonstrated results show significant improvement in energy consumption, data utility and data reconstruction rate compared to other existing methods.

• International Journal of Computer Science & Network Security
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• v.24 no.4
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• pp.11-25
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• 2024

The proliferation of IoT devices has presented an unprecedented challenge in managing device identities securely and efficiently. In this paper, we introduce an innovative Hybrid Blockchain-Based Approach for IoT Identity Management that prioritizes both security and efficiency. Our hybrid solution, strategically combines the advantages of direct and indirect connections, yielding exceptional performance. This approach delivers reduced latency, optimized network utilization, and energy efficiency by leveraging local cluster interactions for routine tasks while resorting to indirect blockchain connections for critical processes. This paper presents a comprehensive solution to the complex challenges associated with IoT identity management. Our Hybrid Blockchain-Based Approach sets a new benchmark for secure and efficient identity management within IoT ecosystems, arising from the synergy between direct and indirect connections. This serves as a foundational framework for future endeavors, including optimization strategies, scalability enhancements, and the integration of advanced encryption methodologies. In conclusion, this paper underscores the importance of tailored strategies in shaping the future of IoT identity management through innovative blockchain integration.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.11 no.12
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• pp.5981-5997
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• 2017

Advanced Television Systems Committee (ATSC) produced ATSC 2.0 standard, which has been used for a HD/SD digital broadcasting service with MPEG-2 Transport Stream (TS) as a delivery protocol. Recently, users might want to consume multimedia services without being constrained by transport network. However, MPEG-2 TS is not suitable protocol for IP network. Thus, ATSC has enacted ATSC 3.0 standard, which is designed for a hybrid service through a conversion of both broadcasting and broadband channels. The ATSC 3.0 specifies delivery protocols as MPEG Media Transport (MMT) for a broadcasting environment and Dynamic Adaptive Streaming over HTTP (DASH) for a broadband. However, it seems difficult to combine broadcast and broadband for hybrid broadcasting, and it is difficult to synchronize media data between MMT and DASH. This paper suggests various new service scenarios to be brought up by a hybrid broadcasting, ATSC 3.0, and also proposes a stable mechanism for switching contents between different delivery protocols such as MMT and DASH.