• Journal of KIISE:Computing Practices and Letters
• /
• v.8 no.5
• /
• pp.583-589
• /
• 2002

The Internet is absolutely contributed to information telecommunication revolution nowadays. Realizing local network at the various type of buildings such as a company and a university, ethernet is used for subnet and FDDI, ATM are used for backbone mainly in order to get internet services. Processing TCP/IP protocol suite and analyzing the protocol exactly is essential to detecting the problem occurring in the network and developing communication equipment. This paper presents implementation of ethernet LAN protocol analyser which monitors and simulates ICP/IP protocol suite carrying the Internet and non-Internet protocol such as Netware and NetBIOS. MS window98 and visual C are used for development environment and application program operates on the NDIS firmware. The performance analysis on the proposed system is carried out as monitoring and simulating the traffic over LAN of a university. In the result of monitoring the system, the processing time of a packet captured over the LAN is about 1.5ms. In case of simulating the system, the processing time to be taken carrying out TCP connection and disconnection once is packet is about 8.6ms. The performance analysis of monitoring and simulation results satisfies with 10 Mbps ethernet LAN environment.

• Journal of KIISE:Information Networking
• /
• v.30 no.5
• /
• pp.656-667
• /
• 2003

Congestion control is a key task in reliable multicast along with error control. However, existing tree-based congestion control schemes such as MTCP and TRAMCC are designed for one-to-many reliable multicast and have some drawbacks when they are used for many-to-many reliable multicast. We propose an efficient congestion control mechanism, TMRCC, for tree-based many-to-many reliable multicast protocols. The proposed scheme is based on the congestion windowing mechanism and a rate controller is used in addition. The feedback for error recovery is exploited for congestion control as well to minimize the overhead at the receivers. The ACK timer and the NACK timers are set dynamically reflecting the network condition changes. The rate regulation algorithm in the proposed scheme is designed to help the flows sharing the same link to achieve the fair share quickly The performance of the proposed scheme is evaluated using ns-2. The simulation results show that the proposed scheme outperforms TRAMCC in terms of intra- session fairness and shows good level of responsiveness, TCP-friendliness, and scalability. In addition, we implemented the proposed scheme by integrating with GAM that is one of many-to-many reliable multicast protocols and evaluated the performance in a laboratory-wide testbed.

• The KIPS Transactions:PartC
• /
• v.13C no.4 s.107
• /
• pp.501-510
• /
• 2006

Software streaming allows the execution of stream-enabled software on desktop or portable computing devices like PC, PDA, laptop, cellular phone, etc., even while the transmission/streaming from the server may still be in progress. In this paper, we present an efficient streaming system called Software On-Demand(SOD) streaming system to transmit stream-enabled applications in addition to automatic installation of program registry, environment variables, configuration files, and related components. In particular, we design and implement a SOD system in Linux to provide the user with the instant look-and-click software execution environment such that software download and installation are internally proceeded in a completely user-transparent way. Therefore, the SOD system relieves the user from the tricky, failure-prone installation business. In addition, the software developer now obtains a new, powerful means to advertise and propagate their software products since the user can use software packages via user-friendly UI window or web browser by look-and-click interactive operation. In the paper, we also make a couple of SOD streaming experiments using a spectrum of popular softwares. Based on the analysis of the experiment results, we also propose two performance improvement schemes.

• Applied Chemistry for Engineering
• /
• v.16 no.6
• /
• pp.772-777
• /
• 2005

Porous hydrated lime and limestone filters were prepared by foaming and gelcasting method, and their physical properties were evaluated. Through these analyses, it has been found that with the increased porosity and pore size of the filters, majority of pores in the filters were inter-connected by windows. Also, $SO_2$ removal efficiency for the filters was investigated. As the porosity and the reaction temperature increased, $SO_2$ removal efficiency also increased. Especially, unlike the variation of entrance concentration, the entrance flow rate had great influence on the removal efficiency. In case of the filters with an equal porosity, the hydrated lime filter had superior removal efficiency compared to the limestone filter. From these results, it was shown that the high conversion ratio to CaO from the hydrated lime filter was a result of facilitated formation of $CaSO_4$ by $SO_2$.

• Journal of Biomedical Engineering Research
• /
• v.24 no.6 s.81
• /
• pp.533-541
• /
• 2003

In the paper. the health card system to integrate several cards into one card for protecting patient's privacy and security problems is proposed. Firstly, it is defined the minimal data set for integrating several patient cards into one card using IC card, and developed the issuing system to issue the integrated patient IC card. In order to secure and certificate a patient's personal information. the integrated patient IC card has applied 3-DES and the PKI certificate authority based Windows 2000 is established. The receipt and reservation system for taking care of a healthcare has developed to cooperate with the existing hospital computer system. The integrating patient IC card system proposed in this paper is implemented to 11 hospitals and used for 1.000 patients. On the result of the simulation. the proposed system can receive or reserve for a patient to take care of healthcare in the simulated hospitals and also establish the basis of the mechanism to share a medical information.

• Journal of KIISE:Databases
• /
• v.37 no.4
• /
• pp.177-184
• /
• 2010

In these day, many data including sensor, delivery, credit and stock data are generated continuously in massive quantity. It is difficult to learn from these data because they are large in volume and changing fast in their concepts. To handle these problems, learning methods based in sliding window methods over time have been used. But these approaches have a problem of rebuilding models every time new data arrive, which requires a lot of time and cost. Therefore we need very simple incremental learning methods. Bayesian method is an example of these methods but it has a disadvantage which it requries the prior knowledge(probabiltiy) of data. In this study, we propose a learning method based on attribute values. In the proposed method, even though we don't know the prior knowledge(probability) of data, we can apply our new method to data. The main concept of this method is that each attribute value is regarded as an expert learner, summing up the expert learners lead to better results. Experimental results show our learning method learns from data very fast and performs well when compared to current learning methods(decision tree and bayesian).

• KIPS Transactions on Computer and Communication Systems
• /
• v.3 no.10
• /
• pp.311-322
• /
• 2014

IoT(Internet of Things) is a concept of connected internet pursuing direct access to devices or sensors in fused environment of personal, industrial and public area. In IoT environment, it is possible to access realtime data, and the data format and topology of devices are diverse. Also, there are bidirectional communications between users and devices to control actuators in IoT. In this point, IoT is different from the conventional internet in which data are produced by human desktops and gathered in server systems by way of one-sided simple internet communications. For the cloud or portal service of IoT, there should be a file management framework supporting systematic naming service and unified data access interface encompassing the variety of IoT things. This paper implements a DB-based virtual file system maintaining attributes of IoT things in a UNIX-styled file system view. Users who logged in the virtual shell are able to explore IoT things by navigating the virtual file system, and able to access IoT things directly via UNIX-styled file I O APIs. The implemented virtual file system is lightweight and flexible because it maintains only directory structure and descriptors for the distributed IoT things. The result of a test for the virtual shell primitives such as mkdir() or chdir() shows the smooth functionality of the virtual file system, Also, the exploring performance of the file system is better than that of Window file system in case of adopting a simple directory cache mechanism.

• Journal of the Institute of Electronics and Information Engineers
• /
• v.52 no.4
• /
• pp.80-87
• /
• 2015

Memristor is a new kind of memory device whose resistance varies depending upon applied charge and whose previous resistance state is preserved even when its power is off. Ordinary memristor has a nonlinear programming characteristics about time when a constant voltage is applied. For the easiness of programming, it is desirable that resistance is programmed linearly about time. We had proposed previously a memristor bridge configuration with which weight can be programmed nicely in positive, negative or zero. In memristor bridge circuit, two memristors are connected in series with different polarity. Memristors are complementary each other and it follows that the memristance variation is linear with respect to time. In this paper, the linearization effect of weight programming of memristor bridge synapse is investigated and verified about both $TiO_2$ memristor from HP and a nonlinear memristor with a window function. Memristor bridge circuit would be helpful to conduct synaptic weight programming.

• Journal of the Korean Society of Radiology
• /
• v.15 no.7
• /
• pp.935-942
• /
• 2021

Involuntary movement of internal organs by respiration is a factor that greatly affects the results of radiotherapy and diagnosis. In this study, a moving phantom was fabricated to simulate the movement of an organ or a tumor according to respiration, and ¹⁸F-FDG PET/CT scan images were acquired under various respiratory simulating conditions to analyze the movement range of the tumor movement by respiration, the level of artifacts according to the size of the tumor and the maximum standardized uptake value (SUVmax). Based on Windows CE 6.0 as the operating system, using electric actuator, electric actuator positioning driver, and programmable logic controller (PLC), the position and speed control module was operated normally at a moving distance of 0-5 cm and 10, 15, and 20 reciprocations. For sphere diameters of 10, 13, 17, 22, 28, and 37 mm at a delay time of 100 minutes, 80.4%, 99.5%, 107.9%, 113.1%, 128.0%, and 124.8%, respectively were measured. When the moving distance was the same, the difference according to the respiratory rate was insignificant. When the number of breaths is 20 and the moving distance is 1 cm, 2 cm, 3 cm, and 5 cm, as the moving distance increased at the sphere diameters of 10, 13, 17, 22, 28, and 37 mm, the ability to distinguish images from smaller spheres deteriorated. When the moving distance is 5 cm compared to the still image, the maximum values of the standard intake coefficient were 18.0%, 23.7%, 29.3%, 38.4%, 49.0%, and 67.4% for sphere diameters of 10, 13, 17, 22, 28, and 37 mm, respectively.

• Journal of the Korea Academia-Industrial cooperation Society
• /
• v.19 no.11
• /
• pp.310-318
• /
• 2018

Recently, the importance of big data analysis is increasing as a large amount of data is generated by various devices connected to the Internet with the advent of Internet of Things (IoT). Especially, it is necessary to analyze various large-scale IoT streaming sensor data generated in real time and provide various services through new meaningful prediction. This paper proposes a real-time indoor PM10 concentration prediction LSTM model based on streaming data generated from IoT sensor using AWS. We also construct a real-time indoor PM10 concentration prediction service based on the proposed model. Data used in the paper is streaming data collected from the PM10 IoT sensor for 24 hours. This time series data is converted into sequence data consisting of 30 consecutive values from time series data for use as input data of LSTM. The LSTM model is learned through a sliding window process of moving to the immediately adjacent dataset. In order to improve the performance of the model, incremental learning method is applied to the streaming data collected every 24 hours. The linear regression and recurrent neural networks (RNN) models are compared to evaluate the performance of LSTM model. Experimental results show that the proposed LSTM prediction model has 700% improvement over linear regression and 140% improvement over RNN model for its performance level.