• Journal of the Korea Society of Computer and Information
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• v.6 no.2
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• pp.1-7
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• 2001

The database development is in need or transaction management composed of operations about data, efficiency database management and security of information data in necessity of as well as the new thinking about data security. When users approach data, transaction concurrency is controlled by the users security authentication and security level of data. So, existing secure algorithm occurred the problems which don't satisfy serializability of high level transaction which is delayed high level transaction repeatedly by the low level transaction, because existing secure algorithm is focused on the part which removes the security channel. Therefore this proposed algorithm which prevents waste of resource from the high level transaction reexecution and delay by stopping serializability offense problem by the increase of efficiency of concurrency control.

• Journal of Korea Society of Digital Industry and Information Management
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• v.14 no.4
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• pp.69-77
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• 2018

The malignant melanoma accounts for about 1 to 3% of the total malignant tumor in the West, especially in the US, it is a disease that causes more than 9,000 deaths each year. Generally, skin lesions are difficult to detect the features through photography. In this paper, we propose a computer-aided diagnosis algorithm based on deep learning for classification of malignant melanoma and benign skin tumor in RGB channel skin images. The proposed deep learning model configures the tumor lesion segmentation model and a classification model of malignant melanoma. First, U-Net was used to segment a skin lesion area in the dermoscopic image. We could implement algorithms to classify malignant melanoma and benign tumor using skin lesion image and results of expert's labeling in ResNet. The U-Net model obtained a dice similarity coefficient of 83.45% compared with results of expert's labeling. The classification accuracy of malignant melanoma obtained the 83.06%. As the result, it is expected that the proposed artificial intelligence algorithm will utilize as a computer-aided diagnosis algorithm and help to detect malignant melanoma at an early stage.

• Journal of Korea Society of Digital Industry and Information Management
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• v.6 no.3
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• pp.37-47
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• 2010

In this paper, we propose an UCC broadcasting system in P2P based IPTV environments. Proposed system applies P2P based multiple chain architecture. UCC broadcasting system transfers data from not ISP server but UCC server peer that is included in DSLAM to joined peers. Therefore an algorithm to manage join and departure of peers have to modified. In this paper we propose an algorithm that does not increase an uplink bandwidth of DSLAM that include UCC server when peer joins to the UCC channel. We will show the improved performance of proposed scheme rather than general method with respect to the uplink bandwidth of DSLAM that include UCC server.

• 한국정보통신설비학회:학술대회논문집
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• 2008.08a
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• pp.372-375
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• 2008

IEEE 802.11e standardized the EDCA mechanism to support the priority based QoS. And the virtual collision handler schedules the transmission time of each MAC frame using the internal back-off window according to the access category(AC). This can provides the differentiated QoS to real-time services at the medium traffic load condition. However, the transmission delay of MAC frame for real-time services may be increased as the traffic load of best effort service increases. It becomes more critical when the real-time service uses a compressed mode video codec such as moving picture experts group(MPEG) 4 codec. That is because each frame has the different importance. That is, the I-frame has more information as compared with the P- and the B-frame. In this paper, we proposed a buffer management algorithm based on the frame importance and the delay bound. The proposed algorithm is consisted of the traffic regulator based on the dual token bucket algorithm and the active queue management algorithm. The traffic regulator reduces the transmission rate of lower AC until that the virtual collision handler can transmit an I-frame. And the active queue management discards frame based on the importance of each frame and the delay bound of head of line(HoL) frame when the channel resource is insufficient.

• Journal of Information Processing Systems
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• v.15 no.3
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• pp.593-603
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• 2019

In wearable healthcare systems, sensor devices can be deployed in places around the human body such as the stomach, back, arms, and legs. The sensors use tiny batteries, which have limited resources, and old sensor batteries must be replaced with new batteries. It is difficult to deploy sensor devices directly into the human body. Therefore, instead of replacing sensor batteries, increasing the lifetime of sensor devices is more efficient. A transmission power control (TPC) algorithm is a representative technique to increase the lifetime of sensor devices. Sensor devices using a TPC algorithm control their transmission power level (TPL) to reduce battery energy consumption. The TPC algorithm operates on a closed-loop mechanism that consists of two parts, such as sensor and sink devices. Most previous research considered only the sink part of devices in the closed-loop. If we consider both the sensor and sink parts of a closed-loop mechanism, sensor devices reduce energy consumption more than previous systems that only consider the sensor part. In this paper, we propose a new approach to consider both the sensor and sink as part of a closed-loop mechanism for efficient energy management of sensor devices. Our proposed approach judges the current channel condition based on the values of various body sensors. If the current channel is not optimal, sensor devices maintain their current TPL without communication to save the sensor's batteries. Otherwise, they find an optimal TPL. To compare performance with other TPC algorithms, we implemented a TPC algorithm and embedded it into sensor devices. Our experimental results show that our new algorithm is better than other TPC algorithms, such as linear, binary, hybrid, and ATPC.

• The Journal of the Korea Contents Association
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• v.10 no.3
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• pp.80-91
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• 2010

Due to the convergence of broadcasting and communications, IPTV services are spotlighted as the that next-generation multimedia services. IPTV services should have functionality such as unlimited channel capacity, extension of media, QoS awareness and are required increasing traffic and quality control technology to adapt the attributes of IPTV service. Consequently, flow based quality control techniques are needed. Therefore, many studies for providing Internet QoS are performed at IETF (Internet Engineering Task Force). As the buffer management mechanism among IP QoS methods, active queue management method such as RED(Random Early Detection) and modified RED algorithms have proposed. However, these algorithms have difficulties to satisfy the requirements of various Internet user QoS. Therefore, in this paper we propose the Flow based AQM(Active Queue Management) algorithm for the multimedia services that request various QoS requirements. The proposed algorithm can converge the packet loss ratio to the target packet loss ratio of required QoS requirements. And we present a performance evaluation by the simulations using the ns-2.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.31 no.2A
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• pp.168-175
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• 2006

To cope with channel variation, wireless networks such as IEEE 802.11 WLAN provide multiple transmission rates by employing different channel modulation and coding schemes. However, the coexistence of different transmission rates degrades the total system performance of the network. In order to eliminate this performance abnormality and improve protocol capacity, we propose a new Packet transmission algorithm, the RAT(Rate-Adapted Transmission) scheme. The RAT scheme distributes the wireless channel fairly based on the channel occupancy time. Moreover, it efficiently transmits packets even in a single station using rate-based queue management. Therefore, the RAT scheme obtains not only the inter-rate contention gain among stations but also the intra-rate contention gain among connections in a single station.

• Journal of Digital Convergence
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• v.10 no.7
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• pp.161-166
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• 2012

When a car accident happened on a highway, the accident vehicle should broadcast a safe message to its neighbors in order to prevent a chain-reaction collision. Also, there is a problem that the estimation accuracy is low because of the memory limit from increasing the sampling count. In this paper, we proposes a HVC systems using a back-off algorithm applied to a gaussian model. And we proposes a MAC protocol preventing the communication delay by separating the neighbor count collection channel, data channel, and RSU communication channel. As a result, we show the frame reception success rate of our protocol improved about 10% than the previous protocol.

• Journal of Positioning, Navigation, and Timing
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• v.11 no.4
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• pp.361-368
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• 2022

An indoor navigation system that utilizes long-term evolution (LTE) signals has the benefit of no additional infrastructure installation expenses and low base station database management costs. Among the LTE signal measurements, received signal strength (RSS) is particularly appealing because it can be easily obtained with mobile devices. Propagation channel models can be used to estimate the position of mobile devices with RSS. However, conventional channel models have a shortcoming in that they do not discriminate between line-of-sight (LOS) and non-line-of-sight (NLOS) conditions of the received signal. Accordingly, a previous study has suggested separated LOS and NLOS channel models. However, a method for determining LOS and NLOS conditions was not devised. In this study, a machine learning-based LOS/NLOS classification method using RSS measurements is developed. We suggest several machine-learning features and evaluate various machine-learning algorithms. As an indoor experimental result, up to 87.5% classification accuracy was achieved with an ensemble algorithm. Furthermore, the range estimation accuracy with an average error of 13.54 m was demonstrated, which is a 25.3% improvement over the conventional channel model.

• Journal of Digital Convergence
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• v.14 no.7
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• pp.331-337
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• 2016

The purpose of this study is to provide a method to visualize the sound data to the three-dimensional image. The visualization of the sound data is performed according to the algorithm set after production of the text-based script that form the channel range of the sound data. The algorithm consists of a total of five levels, including setting sound channel range, setting picture frame for sound visualization, setting 3D image unit's property, extracting channel range of sound data and sound visualization, 3D visualization is performed with at least an operation signal input by the input device such as a mouse. With the sound files with the amount an animator can not finish in the normal way, 3D visualization method proposed in this study was highlighted that the low-cost, highly efficient way to produce creative artistic image by comparing the working time the animator with a study presented method and time for work. Future research will be the real-time visualization method of the sound data in a way that is going through a rendering process in the game engine.