• The Journal of the Korea institute of electronic communication sciences
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• v.14 no.4
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• pp.787-796
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• 2019

In this paper, we propose the design and test measure of Ringer injection IoT system for controling the ringer injection status and notifying the server system of the collected status informations such as the completion of injection, the remaining liquid, the injection status, and the emergency alarming of the urgent patients. We design the circuit diagrams composed of linger injection sensors, switches, status indicators, wireless communication functionalities, and propose the controlling and monitoring algorithms for sensing the linger injection status and notifying the collected status informations to a server system. Furthermore, we derive the testing criteria, such as linger liquid sensing time, sensing distance, operating temperature, input power, power consumption, and wireless communication speed, and analyze the test results.

• Journal of IKEEE
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• v.23 no.2
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• pp.388-394
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• 2019

This paper describes a design of security system-on-chip (SoC) that integrates a Cortex-M0 CPU with an AAW (ARIA-AES- Whirlpool) crypto-core which implements two block cipher algorithms of ARIA and AES and a hash function Whirlpool into an unified hardware architecture. The AAW crypto-core was implemented in a small area through hardware sharing based on algorithmic characteristics of ARIA, AES and Whirlpool, and it supports key sizes of 128-bit and 256-bit. The designed security SoC was implemented on FPGA device and verified by hardware-software co-operation. The AAW crypto-core occupied 5,911 slices, and the AHB_Slave including the AAW crypto-core was implemented with 6,366 slices. The maximum clock frequency of the AHB_Slave was estimated at 36 MHz, the estimated throughputs of the ARIA-128 and the AES-128 was 83 Mbps and 78 Mbps respectively, and the throughput of the Whirlpool hash function of 512-bit block was 156 Mbps.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.23 no.9
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• pp.1146-1151
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• 2019

Histogram H is an x-monotone rectilinear polygon with a horizontal edge, called by a base, connecting the leftmost vertical edge and the rightmost vertical edge. Here the rectilinear polygon is a polygon with only horizontal and vertical edges and the x- monotone polygon P is a polygon in which every line orthogonal to the x-axis intersects P at most twice. Walking counterclockwise on the boundary of a histogram H yields a sequence of left turns and right turns at its vertices. Conversely, a given sequence of the turns at the vertices can be realized by a histogram. In this paper, we consider the problem of finding a histogram to realize a given turn sequence. Particularly, we will find the histograms to minimize its area and its bounding box. It will be shown that both of the problems can be solved by linear time algorithms.

• KIPS Transactions on Software and Data Engineering
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• v.8 no.3
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• pp.129-136
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• 2019

There are a variety of entities in natural language such as people, organizations, places, and products. These entities can have many various meanings. The ambiguity of entity is a very challenging task in the field of natural language processing. Entity Linking(EL) is the task of linking the entity in the text to the appropriate entity in the knowledge base. Pairwise based approach, which is a representative method for solving the EL, is a method of solving the EL by using the association between two entities in a sentence. This method considers only the interdependence between entities appearing in the same sentence, and thus has a limitation of global interdependence. In this paper, we developed an Entity2vec model that uses Word2vec based on knowledge base of RDF type in order to solve the EL. And we applied the algorithms using the generated model and ranked each entity. In this paper, to overcome the limitations of a pairwise approach, we devised a pairwise approach based on comprehensive interdependency and compared it.

• KIPS Transactions on Software and Data Engineering
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• v.9 no.12
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• pp.411-418
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• 2020

In the field of information security, IDS(Intrusion Detection System) is normally classified in two different categories: signature-based IDS and anomaly-based IDS. Many studies in anomaly-based IDS have been conducted that analyze network traffic data generated in cyberspace by machine learning algorithms. In this paper, we studied pre-processing methods to overcome performance degradation problems cashed by rare classes. We experimented classification performance of a Machine Learning algorithm by reconstructing data set based on rare classes and semi rare classes. After reconstructing data into three different sets, wrapper and filter feature selection methods are applied continuously. Each data set is regularized by a quantile scaler. Depp neural network model is used for learning and validation. The evaluation results are compared by true positive values and false negative values. We acquired improved classification performances on all of three data sets.

• KIPS Transactions on Software and Data Engineering
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• v.10 no.2
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• pp.65-72
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• 2021

Recently, attacks on the network environment have been rapidly escalating and intelligent. Thus, the signature-based network intrusion detection system is becoming clear about its limitations. To solve these problems, research on machine learning-based intrusion detection systems is being conducted in many ways, but two problems are encountered to use machine learning for intrusion detection. The first is to find important features associated with learning for real-time detection, and the second is the imbalance of data used in learning. This problem is fatal because the performance of machine learning algorithms is data-dependent. In this paper, we propose the HSF-DNN, a network intrusion detection model based on a deep neural network to solve the problems presented above. The proposed HFS-DNN was learned through the NSL-KDD data set and performs performance comparisons with existing classification models. Experiments have confirmed that the proposed Hybrid Feature Selection algorithm does not degrade performance, and in an experiment between learning models that solved the imbalance problem, the model proposed in this paper showed the best performance.

• Journal of the Korea Society of Computer and Information
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• v.26 no.1
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• pp.69-76
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• 2021

Recentlly neural network approach for solving a singular perturbed integro-differential boundary value problem have been researched. Especially the model of the feed-forward neural network to be trained by the back propagation algorithm with various learning algorithms were theoretically substantiated, and neural network models such as deep learning, transfer learning, federated learning are very rapidly evolving. The purpose of this paper is to study the approaching method for developing a neural network model with high accuracy and speed for solving singular perturbed problem along with asymptotic methods. In this paper, we propose a method that the simulation for the difference between result value of singular perturbed problem and unperturbed problem by using neural network approach equation. Also, we showed the efficiency of the neural network approach. As a result, the contribution of this paper is to show the possibility of simple neural network approach for singular perturbed problem solution efficiently.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.24 no.2
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• pp.244-251
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• 2020

This paper presents a design of the Meta-Class Repository (MCR) which maintain syntactically analyzed and structured meta-class information from UML diagrams, and then proposes 'meta-class,' also known as super-class, to construct structured information analyzed syntactically. The MCR is a collection of these meta-classes which contains the information extracted from diagrams. This paper also presents a design of the Code Generation Engine (CGE) which roles generating codes corresponding classes from UML diagrams based on the MCR maintaining a collection of meta-classes which is syntactically-analyzed and constructed in previous process. The logics of CGE are designed to generate codes collaborated with MCR and CGE with integration. The logics of CGE mechanism is presented with the form of finite state machine to present the algorithms of code generation formally and have the advantages of simplicity and easiness in development.

• Journal of Ocean Engineering and Technology
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• v.34 no.6
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• pp.394-405
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• 2020

To assess the station-keeping performance of floating structures in the Arctic region, the ice load should be considered along with other environmental loads induced by waves, wind, and currents. However, present methods for performance evaluation in the time domain are not effective in terms of time and cost. An ice load generation module is proposed based on the experimental data measured at the KRISO ice model basin. The developed module was applied to a time domain simulation. Using the results of a captive model test conducted in multiple directions, the statistical characteristics of ice loads were analyzed and processed so that an ice load corresponding to an arbitrary angle of the structure could be generated. The developed module is connected to commercial dynamic analysis software (OrcaFlex) as an external force input. Station-keeping simulation in the time domain was conducted for the same floating structure used in the model test. The mooring system was modeled and included to reflect the designed operation scenario. Simulation results show the effectiveness of the proposed ice generation module and its application to station-keeping performance evaluation. Considering the generated ice load, the designed structure can maintain a heading angle relative to ice up to 4°. Station-keeping performance is enhanced as the heading angle conforms to the drift direction. It is expected that the developed module will be used as a platform to verify station-keeping algorithms for Arctic floating structures with a dynamic positioning system.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.23 no.12
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• pp.1624-1630
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• 2019

With the increase in there are smart devices penetration around the world, services related to exercise checks are attracting attention. However, there is existing exercise amount measurement service does not use the altitude information, or because the use of an algorithm that does not corrected the GPS altitude error is not accurate movement distance provided have a problem. Therefore, in this paper, to improve the existing problems, Kalman-filter-based user movement distance measurement algorithm is designed and implementation of improved by using the Kalman-filter based GPS and barometric altimeter sensor fusion algorithm to improve the altitude value the accuracy and of calculate the coordinate plane distance. As a result of comparing the designed and implementation of algorithm with the existing algorithms, it is confirmed that the proposed algorithm improves the accuracy by about 2.17%.