• Journal of Broadcast Engineering
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• v.25 no.6
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• pp.944-953
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• 2020

Object detection plays a crucial role in a self-driving system. With the advances of image recognition based on deep convolutional neural networks, researches on object detection have been actively explored. In this paper, we proposed a lightweight model of the mask R-CNN, which has been most widely used for object detection, to efficiently predict location and shape of various objects on the road environment. Furthermore, feature maps are adaptively re-calibrated to improve the detection performance by applying an attention module to the neural network layer that plays different roles within the mask R-CNN. Various experimental results for real driving scenes demonstrate that the proposed method is able to maintain the high detection performance with significantly reduced network parameters.

• ETRI Journal
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• v.35 no.1
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• pp.41-50
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• 2013

Network Mobility (NEMO) handles mobility of multiple nodes in an aggregate manner as a mobile network. The standard NEMO suffers from a number of limitations, such as inefficient routing and increased handoff latency. Most previous studies attempting to solve such problems have imposed an extra signaling load and/or modified the functionalities of the main entities. In this paper, we propose a more secure and lightweight route optimization (RO) mechanism based on exploiting the firewall in performing the RO services on behalf of the correspondent nodes (CNs). The proposed mechanism provides secure communications by making an authorized decision about the mobile router (MR) home of address, MR care of address, and the complete mobile network prefixes underneath the MR. In addition, it reduces the total signaling required for NEMO handoffs, especially when the number of mobile network nodes and/or CNs is increased. Moreover, our proposed mechanism can be easily deployed without modifying the mobility protocol stack of CNs. A thorough analytical model and network simulator (Ns-2) are used for evaluating the performance of the proposed mechanism compared with NEMO basic support protocol and state-of-the-art RO schemes. Numerical and simulation results demonstrate that our proposed mechanism outperforms other RO schemes in terms of handoff latency and total signaling load on wired and wireless links.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2009.01a
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• pp.385-389
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• 2009

Multi-hop wireless mesh networks (WMNs) suffer from significant packet losses due to insufficient available bandwidth and high channel error probability. To conquer packet losses, end-to-end (E2E) error control schemes have been proposed. However, in WMNs, E2E error control schemes are not effective in adapting to the time-varying network condition due to large delay. Thus, in this paper, we propose a network-adaptive error control for video streaming over WMNs that flexibly operates E2E and hop-by-hop (HbH) error control according to network condition. Moreover, to provide lightweight support at intermediate nodes for HbH error control, we use path-partition-based adaptation. To verify the proposed scheme, we implement it and evaluate its transport performance through MPEG-2 video streaming over a real IEEE 802.11a-based WMN testbed.

• Journal of Information Processing Systems
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• v.7 no.1
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• pp.53-62
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• 2011

With the steady growth of mobile technology and applications, demand for more storage in mobile devices has also increased. A lightweight block-level protocol, Internet Advanced Technology Attachment (iATA), has been developed to deliver a cost-effective storage network solution for mobile devices to obtain more storage. This paper seeks to contribute to designing and implementing Load Balancing (LB), Network Monitoring (NM) and Write Replication (WR) modules to improve the protocol's scalability and data availability. LB and NM modules are invoked to collect system resources states and current network status at each associate node (server machine). A dynamic weight factor is calculated based on the collected information and sent to a referral server. The referral server is responsible to analyze and allocate the most ideal node with the least weight to serve the client. With this approach, the client can avoid connecting to a heavily loaded node that may cause delays in subsequent in-band I/O operations. Write replication is applied to the remaining nodes through a WR module by utilizing the Unison file synchronization program. A client initially connected to node IP A for write operations will have no hindrances in executing the relevant read operations at node IP B in new connections. In the worst case scenario of a node crashing, data remain recoverable from other functioning nodes. We have conducted several benchmark tests and our results are evaluated and verified in a later section.

• Proceedings of the IEEK Conference
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• 1998.10a
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• pp.207-210
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• 1998

Providing the connectivity interworking between the lightweight signaling function using in VOD set-top box and the broadband signaling function In the access node system, it can diminish the cost-burden of user about set-top box and we shall use efficiently the network resources. Therefore, In this paper, we shall design the signaling brokerage agent function for the connectivityinterworking in access node system and discuss the result applied its function to the real-time VOD service.

• Transactions on Control, Automation and Systems Engineering
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• v.3 no.3
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• pp.190-195
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• 2001

The advance of computer, network, and Internet technology enables the control systems to process the massive data in the distributed computing environments. To implement and maintain the software in distributed environment, the component-based methodology is widely used. This paper proposes the middleware architecture for the distributed computer control system. With the proposed middleware services, it is relatively easy to maintain compatibility between products and to implement a portable control application. To achieve the compatibility between heterogeneous systems, the proposed architecture provides the communication protocols based on the XML with lightweight event-based service.

• Proceedings of the Korea Information Processing Society Conference
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• 2009.04a
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• pp.1264-1266
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• 2009

We introduce a location-based routing model applied for grid backbone nodes in wireless mesh network. The number of paths with nearest distance between two nodes is calculated and used as key parameter to execute routing algorithm. Node will increase the transmission range that makes a trade off with data rate to reach its neighbors when node itself is isolated. The routing model is lightweight and oriented thanks to the simple but efficient routing algorithm.

• Smart Structures and Systems
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• v.10 no.3
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• pp.209-228
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• 2012

Structural health monitoring with wireless sensor networks has received much attention in recent years due to the ease of sensor installation and low deployment and maintenance costs. However, sensor network technology needs to solve numerous challenges in order to substitute conventional systems: large amounts of data, remote configuration of measurement parameters, on-site calibration of sensors and robust networking functionality for long-term deployments. We present a structural health monitoring network that addresses these challenges and is used in several deployments for monitoring of bridges and buildings. Our system supports a diverse set of sensors, a library of highly optimized processing algorithms and a lightweight solution to support a wide range of network runtime configurations. This allows flexible partitioning of the application between the sensor network and the backend software. We present an analysis of this partitioning and evaluate the performance of our system in three experimental network deployments on civil structures.

• Journal of Institute of Control, Robotics and Systems
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• v.19 no.10
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• pp.901-906
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• 2013

Chaff is a kind of matter spreading atmosphere with the purpose of preventing aircraft from detecting by radar. The chaff is commonly composed of small aluminum pieces, metallized glass fiber, or other lightweight strips which consists of reflecting materials. The chaff usually appears on the radar images as narrow bands shape of highly reflective echoes. And the chaff echo has similar characteristics to precipitation echo, and it interrupts weather forecasting process and makes forecasting accuracy low. In this paper, the chaff echo recognizing and removing method is suggested using Bayesian network. After converting coordinates from spherical to Cartesian in UF (Universal Format) radar data file, the characteristics of echoes are extracted by spatial and temporal clustering. And using the data, as a result of spatial and temporal clustering, a classification process for analyzing is performed. Finally, the inference system using Bayesian network is applied. As a result of experiments with actual radar data in real chaff echo appearing case, it is confirmed that Bayesian network can distinguish between chaff echo and non-chaff echo.

• Transactions on Semiconductor Engineering
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• v.2 no.1
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• pp.17-20
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• 2024

This paper presents a novel lightweight object detection model tailored for low-powered edge devices, addressing the limitations of traditional resource-intensive computer vision models. Our proposed detector, inspired by the Single Shot Detector (SSD), employs a compact yet robust network design. Crucially, it integrates an 'enhancer block' that significantly boosts its efficiency in detecting smaller objects. The model comprises two primary components: the Light_Block for efficient feature extraction using Depth-wise and Pointwise Convolution layers, and the Enhancer_Block for enhanced detection of tiny objects. Trained from scratch on the Udacity Annotated Dataset with image dimensions of 300x480, our model eschews the need for pre-trained classification weights. Weighing only 5.5MB with approximately 0.43M parameters, our detector achieved a mean average precision (mAP) of 27.7% and processed at 140 FPS, outperforming conventional models in both precision and efficiency. This research underscores the potential of lightweight designs in advancing object detection for edge devices without compromising accuracy.