• The Journal of Engineering Research
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• v.7 no.1
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• pp.53-60
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• 2005

Community Wireless Networks define the next generation wireless services. Multimedia usages for financial services over community Wireless LAN (WLAN) based mesh networks require link stability. Several new services are being proposed for multimedia over WLANs. Portable Internet Services are implemented by several wireless carriers to proliferate their customer base. However, these services are still expensive and require a central telecom/wireless carrier whose monopoly and preference defines the availability of new services. Our research project identifies the usage of these critical services in public places over the financial services backbone architecture to provide efficient easy-to-use and economical services to their customers and merchants without being dependent on the central wireless carrier. The user connects to the network using his regular WLAN NIC using the Mesh Router/Bridge interconnectivity and obtains the needed multimedia and financial services from the ATM-AP Gateway, In our proposed scenario, the ATN AP-MR use AODV protocol and MR-MC is based on 802.11g/a/b IEEE standard. We use multi path routing protocols for reducing the congestion over a particular route. We demonstrate the results of our simulations and test-bed outcome to evaluate link failure rate and oversubscription factors to eliminate network congestion and non-availability of the critical financial services.

• Journal of Communications and Networks
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• v.15 no.1
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• pp.31-37
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• 2013

Mobile ad hoc networks (MANET) refers to a network designed for special applications for which it is difficult to use a backbone network. In MANETs, applications are mostly involved with sensitive and secret information. Since MANET assumes a trusted environment for routing, security is a major issue. In this paper we analyze the vulnerabilities of a pro-active routing protocol called optimized link state routing (OLSR) against a specific type of denial-of-service (DOS) attack called node isolation attack. Analyzing the attack, we propose a mechanism called enhanced OLSR (EOLSR) protocol which is a trust based technique to secure the OLSR nodes against the attack. Our technique is capable of finding whether a node is advertising correct topology information or not by verifying its Hello packets, thus detecting node isolation attacks. The experiment results show that our protocol is able to achieve routing security with 45% increase in packet delivery ratio and 44% reduction in packet loss rate when compared to standard OLSR under node isolation attack. Our technique is light weight because it doesn't involve high computational complexity for securing the network.

• Journal of Broadcast Engineering
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• v.26 no.7
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• pp.868-876
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• 2021

Deploying deep neural network model training performs remarkable performance in the fields of Object detection and Instance segmentation. To train these models, features are first extracted from the input image using a backbone network. The extracted features can be reused by various tasks. Research has been actively conducted to serve various tasks by using these learned features. In this process, standardization discussions about encoding, decoding, and transmission methods are proceeding actively. In this scenario, it is necessary to analyze the response characteristics of features against various distortions that may occur in the data transmission or data compression process. In this paper, experiment was conducted to inject various distortions into the feature in the object recognition task. And analyze the mAP (mean Average Precision) metric between the predicted value output from the neural network and the target value as the intensity of various distortions was increased. Experiments have shown that features are more robust to distortion than images. And this points out that using the feature as transmission means can prevent the loss of information against the various distortions during data transmission and compression process.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2020.11a
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• pp.68-71
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• 2020

최근 딥러닝을 이용한 인체 자세 추정(human pose estimation) 연구가 활발히 진행되고 있다. 그 중 구조가 간단하면서도 성능이 강력하여 널리 사용되고 있는 딥러닝 네트워크 모델은 이미지 분류(image classification)에 사용되는 백본 네트워크(backbone network)와 디컨볼루션 출력망(deconvolution head network)을 이어 붙인 구조를 갖는다[1]. 기존의 디컨볼루션 출력망은 디컨볼루션 층을 쌓아 낮은 해상도의 특징맵을 모두 높은 해상도로 변환한 후 최종 인체 자세 추정을 하는데 이는 다양한 해상도에서 얻어낸 특징들을 골고루 활용하기 힘들다는 단점이 있다. 따라서 본 논문에서는 매 디컨볼루션 층 이후에 인체 자세 추정을 하여 다양한 해상도에서 연산을 하고 이를 종합하여 최종 인체 자세 추정을 하는 방법을 제안한다. 실험 결과 Res50 과 기존의 디컨볼루션 출력망의 경우 0.717 AP 를 얻었는데 Res101 과 기존의 디컨볼루션 출력망을 사용한 결과 50% 이상의 파라미터 수 증가와 함께 0.727 AP, 즉 0.010AP 의 성능 향상이 이루어졌다. 이에 반해 Res50 에 다중 해상도 디컨볼루션 출력망을 사용한 결과 약 1%의 파라미터 수 증가 만으로 0.720 AP, 즉 0.003 AP 의 성능 향상이 이루어졌다. 이를 통해 디컨볼루션 출력망 구조를 개선하면 매우 적은 파라미터 수 증가 만으로도 인체 자세 추정의 성능을 효과적으로 향상시킬 수 있음을 확인하였다.

• Journal of Information Processing Systems
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• v.19 no.5
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• pp.614-630
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• 2023

Dead trees significantly impact forest production and the ecological environment and pose constraints to the sustainable development of forests. A lightweight YOLOv4 dead tree detection algorithm based on unmanned aerial vehicle images is proposed to address current limitations in dead tree detection that rely mainly on inefficient, unsafe and easy-to-miss manual inspections. An improved logarithmic transformation method was developed in data pre-processing to display tree features in the shadows. For the model structure, the original CSPDarkNet-53 backbone feature extraction network was replaced by MobileNetV3. Some of the standard convolutional blocks in the original extraction network were replaced by depthwise separable convolution blocks. The new ReLU6 activation function replaced the original LeakyReLU activation function to make the network more robust for low-precision computations. The K-means++ clustering method was also integrated to generate anchor boxes that are more suitable for the dataset. The experimental results show that the improved algorithm achieved an accuracy of 97.33%, higher than other methods. The detection speed of the proposed approach is higher than that of YOLOv4, improving the efficiency and accuracy of the detection process.

• ETRI Journal
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• v.45 no.5
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• pp.822-835
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• 2023

Recent semantic segmentation frameworks usually combine low-level and high-level context information to achieve improved performance. In addition, postlevel context information is also considered. In this study, we present a Context ReFinement Network (CRFNet) and its training method to improve the semantic predictions of segmentation models of the encoder-decoder structure. Our study is based on postprocessing, which directly considers the relationship between spatially neighboring pixels of a label map, such as Markov and conditional random fields. CRFNet comprises two modules: a refiner and a combiner that, respectively, refine the context information from the output features of the conventional semantic segmentation network model and combine the refined features with the intermediate features from the decoding process of the segmentation model to produce the final output. To train CRFNet to refine the semantic predictions more accurately, we proposed a sequential training scheme. Using various backbone networks (ENet, ERFNet, and HyperSeg), we extensively evaluated our model on three large-scale, real-world datasets to demonstrate the effectiveness of our approach.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.33 no.9B
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• pp.760-766
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• 2008

As a backbone network, wireless mesh network (WMN) aims to provide reliable high throughput network connectivity to wireless users. Recent research has focused on routing and channel allocation to increase the capacity of wireless mesh backbones. Wireless mesh networking is an attractive solution for home, community, and enterprise networks as it is a self-configuring, instantly deployable, and lowcost networking system. In this paper, we empirically evaluate and analyze charateristic of WMN to establish WMN testbed by measurement. We use laptops and net4826 Soekris board widely used. Soekris boards are equipped with one network interface card (NIC) or above in our measurements. We also use paket generator, routing demon tools and so on. Throughout this measurements, we show limitation of Soekris board and software we use, and suggest guideline to establish WMN.

• Journal of the Institute of Electronics and Information Engineers
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• v.53 no.9
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• pp.38-45
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• 2016

For higher efficiency and reliability of railroad trains with many electronic sensors and actuators, a distributed control system with which electronic components communicate with each other in a distributed manner via a data network is considered. This paper considers Ethernet-based Train Communication Network (TCN) for this purpose and proposes a methodology to optimize the topology in terms of transmission latency and reliability, each of which is modeled as the number of traversing backbone nodes and the number of cables between vehicles, respectively. An objective function is derived accordingly and a closed-form optimum is obtained by relaxing the integer constraint of the number of vehicles for a unit network. Then, the final integer optimum is searched around it. Through numerical evaluation, the validity of the proposed methodology and the characteristics of the resulting solutions are shown.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.15 no.6
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• pp.79-88
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• 2015

In this paper, we examine Ethernet based vehicle network which is recently emerging technology. Current MOST for entertainment will be soon replaced with the emerging Ethernet based vehicle network. Although legacy standard Ethernet has several advantages it is not suitable for vehicle backbone network without any modification. As a result, many researches are happening on extending and modification of the Ethernet function for realtime and reliability. Time-triggered Ethernet, one of many trials known as AS6802, is investigated on the architecture and functionalities. We design the traffic model on Time-triggered Ethernet and analyse the latency of the network. We also consider the QoS requirement and environment of operating configuration for vehicle network.

• Journal of the Korea Society of Computer and Information
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• v.14 no.11
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• pp.91-96
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• 2009

In this paper, interoperability in heterogeneous wireless mesh network, and mesh nodes for providing efficient IP mobility technique offers multi-hop ARP. Heterogeneous wireless mesh networks to MANETs based on a wireless mesh network backbone and non-MANET architecture is based on a client wireless mesh network and the two mobile networks, combined with a hybrid wireless mesh network are separate. In two different hybrid wireless mesh network routing protocols used to connect the two protocols in the protocol conversion at the gateway to parallel processing problems seriously overload occurs. All of the network reliability and stability are factors that reduce. Therefore, for efficient integration with L3 routing protocols, design techniques to build ARP multi-hop go through the experiment to increase the number of mesh nodes, the packet forwarding rate and an increased hop number of the node was to ensure reliability and stability.