• Journal of the Korea Institute of Information and Communication Engineering
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• v.20 no.9
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• pp.1704-1709
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• 2016

In this paper, we propose efficient uplink data transmission method in ultra dense wireless networks as in intra-aircraft, where large-scale APs and wireless sensors are deployed. In the ultra dense wireless networks, a performance degradation is inevitable due to the inter-AP interference. However, the performance degradation can be avoided if a scheduling algorithm can estimate the amount of interference caused by each wireless sensor and reflects it. SGIR (Signal-to-Generating Interference Ratio) based scheduling algorithms is a typical example. Unfortunately, the scheduling algorithms based on the interference caused by wireless sensors necessarily yield large scale exchange of information through backhaul which connects APs. Therefore, we, in this paper, propose a novel scheme which can dramatically reduce the amount of information which are exchanged through backhaul connection. Monte-Carlo simulation results show that the proposed scheme can reduce the amount of backhaul traffic by 27% without loss of data transmission rate.

• Journal of Korea Multimedia Society
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• v.14 no.1
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• pp.33-43
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• 2011

Routing technologies considering QoS-based hypermedia services have been seen as a crucial network property in next generation optical Internet (NGOI) networks based on IP/dense-wavelength division multiplexing (DWDM). The huge potential capacity of one single fiber. which is in Tb/s range, can be exploited by applying DWDM technology which transfers multiple data streams (classified and aggregated IP traffics) on multiple wavelengths (classified with QoS-based) simultaneously. So, DWDM-based optical networks have been a favorable approach for the next generation optical backbone networks. Finding a qualified path meeting the multiple constraints is a multi-constraint optimization problem, which has been proven to be NP-complete and cannot be solved by a simple algorithm. The majority of previous works in DWDM networks has viewed heuristic QoS routing algorithms (as an extension of the current Internet routing paradigm) which are very complex and cause the operational and implementation overheads. This aspect will be more pronounced when the network is unstable or when the size of network is large. In this paper, we propose a flooding-based unicast and multicast QoS routing methodologies(YS-QUR and YS-QMR) which incur much lower message overhead yet yields a good connection establishment success rate. The simulation results demonstrate that the YS-QUR and YS-QMR algorithms are superior to the previous routing algorithms.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.57 no.11
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• pp.2047-2053
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• 2008

Auto-ID industries and their services have been improved since decades ago, and radio frequency identification (RFID) has been contributing in many applications. Product management can be the foremost example. In our industrial experiences, RFID in ultra high frequency (UHF) band provides much longer interrogation ranges than that of 13.56MHz; many more applications exist thereby. There should be several interesting and useful ideas on UHF RFID; however, those ideas can be limited due to the inevitable environmental circumstances that restrict the interrogation range in shorten value. This paper discusses the propagation interference among different types of readers (e.g, mobile RFID readers in stationary reader zone) in dense-reader environment. In most cases, UHF RFIDs in Korea will be dependent on the UHF mobile RFIDs. In this sense, the UHF mobile users accidently move into the stationary reader's interrogation zone. This is serious problem. In this paper, we analyze propagation loss and propose the effective channel allocation scheme that can contribute developing less-invasive UHF RFID networks. The simulation and practical measurement process using the commercial CAD tools and measurement equipments are presented.

• ETRI Journal
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• v.37 no.6
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• pp.1065-1076
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• 2015

Network densification is regarded as the dominant driver for wireless evolution into the era of 5G. However, in this context, interference-limited dense small cell deployments are facing technical challenges in mobility management. The recently announced results from an LTE field test conducted in a dense urban area show a handover failure (HOF) rate of over 21%. A major cause of HOFs is the transmission failure of handover command (HO CMD) messages. In this paper, we propose two enhancements to HO performance in LTE networks - radio link failure-proactive HO, which helps with the reliable transmission of HO CMD messages while the user equipment is under a poor radio link condition, and Early Handover Preparation with Ping-Pong Avoidance (EHOPPPA) HO, which assures reliable transmission of HO CMD under a good radio link condition. We analyze the HO performance of EHOPPPA HO theoretically, and perform simulations to compare the performance of the proposed schemes with that of standard LTE HO. We show that they can decrease the HOF rate to nearly zero through an analysis, and based on the simulation results, by over 70%, without increasing the ping-pong probability.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.8 no.9
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• pp.2982-3003
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• 2014

With the explosive deployment of the wireless communications technology, the increased QoS requirement has sparked keen interest in network planning and optimization. As the major players in wireless network optimization, the BS's resource utilization and mobile user's QoS can be improved a lot by the load-balancing technology. In this paper, we propose a load-balancing strategy that uses Coordinated Multiple Points (CoMP) technology among the Base Stations (BS) to effectively extend network coverage and increase edge users signal quality. To use universally, different patterns of load-balancing based on CoMP are modeled and discussed. We define two QoS metrics to be guaranteed during CoMP load balancing: call blocking rate and efficient throughput. The closed-form expressions for these two QoS metrics are derived. The load-balancing capacity and QoS performances with different CoMP patterns are evaluated and analyzed in low-dense and high-dense traffic system. The numerical results present the reasonable CoMP load balancing pattern choice with guaranteed QoS in each system.

• International Journal of Computer Science & Network Security
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• v.21 no.11
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• pp.17-22
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• 2021

Recently, image super-resolution techniques used in convolutional neural networks (CNN) have led to remarkable performance in the research area of digital image processing applications and computer vision tasks. Convolutional layers stacked on top of each other can design a more complex network architecture, but they also use more memory in terms of the number of parameters and introduce the vanishing gradient problem during training. Furthermore, earlier approaches of single image super-resolution used interpolation technique as a pre-processing stage to upscale the low-resolution image into HR image. The design of these approaches is simple, but not effective and insert the newer unwanted pixels (noises) in the reconstructed HR image. In this paper, authors are propose a novel single image super-resolution architecture based on synchronized depthwise separable convolution with Dense Skip Connection Block (DSCB). In addition, unlike existing SR methods that only rely on single path, but our proposed method used the synchronizes path for generating the SISR image. Extensive quantitative and qualitative experiments show that our method (SDCN) achieves promising improvements than other state-of-the-art methods.

• International Journal of Computer Science & Network Security
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• v.21 no.7
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• pp.182-190
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• 2021

Deep learning is an advanced technology for large-scale data analysis, with numerous promising cases like image processing, object detection and significantly more. It becomes customarily to use transfer learning and fine-tune a pre-trained CNN model for most image recognition tasks. Having people taking photos and tag themselves provides a valuable resource of in-data. However, these tags and labels might be noisy as people who annotate these images might not be experts. This paper aims to explore the impact of noisy labels on fine-tuning pre-trained CNN models. Such effect is measured on a food recognition task using Food101 as a benchmark. Four pre-trained CNN models are included in this study: InceptionV3, VGG19, MobileNetV2 and DenseNet121. Symmetric label noise will be added with different ratios. In all cases, models based on DenseNet121 outperformed the other models. When noisy labels were introduced to the data, the performance of all models degraded almost linearly with the amount of added noise.

• The KIPS Transactions:PartC
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• v.12C no.4 s.100
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• pp.543-550
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• 2005

Many routing algorithms, proposed for ad-hoc wireless networks, we based on source routing scheme and shortest path route has short lifetime especially in highly dense ad-hoc wireless networks. So some routing protocols such as SSA and ABR are considering the link stability and try finding more stable route. In this paper we propose a new routing algorithm considering utilization metric based on SSA routing algerian in Ad-Hoc networks. To reduce the bottleneck by specific metric of SSA, proposed scheme makes load balancing in networks by distributing the connections to several routes. For the evaluation of the performance we compare our scheme with existent routing protocol AODV and SSA. And the results, obtained using the ns-2 network simulation platform, show good performance that reduced the number of reconstructions remarkably by distributing the whole traffic to several routes when there are several stable routes.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.36 no.8C
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• pp.489-496
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• 2011

Energy efficiency in wireless sensor networks is a principal issue to prolong applications to track the movement of the large-scale phenomena. It is a selective wakeup approach that is an effective way to save energy in the networks. However, most previous studies with the selective wakeup scheme are concentrated on individual objects such as intruders and tanks, and thus cannot be applied for tracking continuous objects such as wild fire and poison gas. This is because the continuous object is pretty flexible and volatile due to its sensitiveness to surrounding circumferences so that movable area cannot be estimated by the just spatiotemporal mechanism. Therefore, we propose a cluster-based algorithm for applying the efficient and more accurate technique to the continuous object tracking in enough dense sensor networks. Proposed algorithm wakes up the sensors in unit cluster where target objects may be diffused or shrunken. Moreover, our scheme is asynchronous because it does not need to calculate the next area at the same time.

• Smart Structures and Systems
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• v.18 no.5
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• pp.885-909
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• 2016

Advances in low-cost wireless sensing have made instrumentation of large civil infrastructure systems with dense arrays of wireless sensors possible. A critical issue with regard to effective use of the information harvested from these sensors is synchronized sensing. Although a number of synchronization methods have been developed, most provide only clock synchronization. Synchronized sensing requires not only clock synchronization among wireless nodes, but also synchronization of the data. Existing synchronization protocols are generally limited to networks of modest size in which all sensor nodes are within a limited distance from a central base station. The scale of civil infrastructure is often too large to be covered by a single wireless sensor network. Multiple independent networks have been installed, and post-facto synchronization schemes have been developed and applied with some success. In this paper, we present a new approach to achieving synchronized sensing among multiple networks using the Pulse-Per-Second signals from low-cost GPS receivers. The method is implemented and verified on the Imote2 sensor platform using TinyOS to achieve $50{\mu}s$ synchronization accuracy of the measured data for multiple networks. These results demonstrate that the proposed approach is highly-scalable, realizing precise synchronized sensing that is necessary for effective structural health monitoring.