• Journal of Internet of Things and Convergence
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• v.8 no.5
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• pp.77-83
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• 2022

Nand flash memory requires an Erase-Before-Write operation structurally. In order to solve this problem, it can be solved by classifying a page (hot data page) where data update operation occurs frequently and storing it in a separate block. The MHF (Multi Hash Function Framework) technique records the frequency of data update requests in the system memory, and when the recorded value exceeds a certain standard, the data update request is judged as hot data. However, the method of simply counting only the frequency of the data update request has a limit in judging it as accurate hot data. In addition, in the case of a technique that determines the persistence of a data update request, the fact of the update request is recorded sequentially based on a time interval and then judged as hot data. In the case of such a persistence-based method, its implementation and operation are complicated, and there is a problem of inaccurate judgment if frequency is not considered in the update request. This paper proposes a lightweight hot data determination technique that considers both frequency and persistence in data update requests.

• Journal of the Korea Society of Computer and Information
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• v.25 no.1
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• pp.87-92
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• 2020

Various devices, which are powerful computer and low-performance sensors, is connected to IoT network. Accordingly, applying mutual authentication for devices and data encryption method are essential since illegal attacks are existing on the network. But cryptographic methods such as symmetric key and public key algorithms, hash function are not appropriate to low-performance devices. Therefore, this paper proposes blockchain-based lightweight IoT mutual authentication protocol for the low-performance devices.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.25 no.4
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• pp.719-726
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• 2015

As big-data and cloud security technologies become popular, many researchers have recently been conducted on faster and lighter encryption. As a result, National Security Research Institute developed LEA which is lightweight and fast block cipher. To date, there have been various studies on lightweight encryption algorithm (LEA) for speeding up using GPU rather than conventional CPU. However, it is rather difficult to explore any guideline how to manipulate the GPU for the efficient usage of the LEA. Therefore, we introduce a guideline which explains how to implement and design the optimal LEA using GPU.

• Journal of the Korean Society of Safety
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• v.29 no.5
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• pp.7-14
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• 2014

This study aimed to develop members with the optimum impact characteristics to ensure a protected space for passengers in the case of automobile collisions. Accordingly, these members were fabricated to provide sufficient rigidity and safety to the passenger room structure and to absorb large amounts of energy during collision. In particular, CFRP members were fabricated with different section shapes such as square and single- and double-hat shapes. Next, their impact collapse characteristics and collapse modes were quantitatively analyzed according to the changes in section shapes and stacking angles. This analysis was performed to obtain design data that can be applied in the development of optimum lightweight members for automobiles.

• Smart Structures and Systems
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• v.13 no.1
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• pp.81-98
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• 2014

This paper presents the elastic buckling of smart lightweight column structures integrated with a pair of surface piezoelectric layers using artificial intelligence. The finite element modeling of Smart lightweight columns is found using $ANSYS^{(R)}$ software. Then, the first buckling load of the structure is calculated using eigenvalue buckling analysis. To determine the accuracy of the present finite element analysis, a compression study is carried out with literature. Later, parametric studies for length variations, width, and thickness of the elastic core and of the piezoelectric outer layers are performed and the associated buckling load data sets for artificial intelligence are gathered. Finally, the application of soft computing-based methods including artificial neural network (ANN), fuzzy inference system (FIS), and adaptive neuro fuzzy inference system (ANFIS) were carried out. A comparative study is then made between the mentioned soft computing methods and the performance of the models is evaluated using statistic measurements. The comparison of the results reveal that, the ANFIS model with Gaussian membership function provides high accuracy on the prediction of the buckling load in smart lightweight columns, providing better predictions compared to other methods. However, the results obtained from the ANN model using the feed-forward algorithm are also accurate and reliable.

• Convergence Security Journal
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• v.5 no.3
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• pp.23-32
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• 2005

This paper presents a 128-bit Reversible Cellular Automata (RCA) based lightweight block cipher for Ubiquitous computing security. To satisfy resource-constraints for Ubiquitous computing, it is designed as block architecture based on Cellular Automata with high pseudo-randomness. Our implementation requires 704 clock cycles and consumes 2,874 gates for encryption of a 128-bit data block. In conclusion, the processing time outperformed that of AES and NTRU by 31%, and the number of gate was saved by 20%. We evaluate robustness of our implementation against both Differential Cryptanalysis and Strict Avalanche Criterion.

• Proceedings of the Korean Society For Composite Materials Conference
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• 2004.10a
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• pp.286-289
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• 2004

This paper presents the fatigue characteristics of LIPCA (LIghtweight Piezo-Composite Actuator) device system. The LIPCA device system is composed of a piezoelectric ceramic layer and fiber reinforced lightweight composite layers. Typically a PZT ceramic layer is sandwiched by a top fiber layer with low CTE (coefficient of thermal expansion) and base layers with high CTE. The advantages of the LIPCA design are weight reduction by using the lightweight fiber reinforced plastic layers without compromising the generation of high force and large displacement and design flexibility by selecting the fiber direction and the size of prepreg layers. To predict the degradation of actuation performance of LIPCA due to fatigue, the cyclic electric loading tests using PZT specimens were performed and the strain for a given excitation voltage was measured during the test. The results from the PZT fatigue test were implemented into CLPT (Classical Laminated Plate Theory) model to predict the degradation of LIPCA's actuation displacement. The fatigue characteristic of PZT was measured using a test system composed of a supporting jig, a high voltage power supplier, data acquisition board, PC, and evaluated.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.5 no.3
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• pp.560-574
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• 2011

In this paper, we propose a hybrid method of Machine Learning (ML) algorithm and a rule-based algorithm to implement a lightweight Named Entity (NE) extraction system for Korean SMS text. NE extraction from Korean SMS text is a challenging theme due to the resource limitation on a mobile phone, corruptions in input text, need for extension to include personal information stored in a mobile phone, and sparsity of training data. The proposed hybrid method retaining the advantages of statistical ML and rule-based algorithms provides fully-automated procedures for the combination of ML approaches and their correction rules using a threshold-based soft decision function. The proposed method is applied to Korean SMS texts to extract person's names as well as location names which are key information in personal appointment management system. Our proposed system achieved 80.53% in F-measure in this domain, superior to those of the conventional ML approaches.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.14 no.10
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• pp.4080-4097
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• 2020

In recent years, convolutional neural network (CNN) has become the primary method for face detection. But its shortcomings are obvious, such as expensive calculation, heavy model, etc. This makes CNN difficult to use on the mobile devices which have limited computing and storage capabilities. Therefore, the design of lightweight CNN for face detection is becoming more and more important with the popularity of smartphones and mobile Internet. Based on the CPU real-time face detector FaceBoxes, we propose a multi-task lightweight face detector, which has low computing cost and higher detection precision. First, to improve the detection capability, the squeeze and excitation modules are used to extract attention between channels. Then, the textual and semantic information are extracted by shallow networks and deep networks respectively to get rich features. Finally, the landmark detection module is used to improve the detection performance for small faces and provide landmark data for face alignment. Experiments on AFW, FDDB, PASCAL, and WIDER FACE datasets show that our algorithm has achieved significant improvement in the mean average precision. Especially, on the WIDER FACE hard validation set, our algorithm outperforms the mean average precision of FaceBoxes by 7.2%. For VGA-resolution images, the running speed of our algorithm can reach 23FPS on a CPU device.

• Journal of the Korean Recycled Construction Resources Institute
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• v.4 no.2
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• pp.118-124
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• 2016

The purpose of this study is to analyze the rheology characteristics of insulating concrete for each type of insulation performance improvement material and utilize the result as preliminary data for optimal flow designing and pumping analysis. As a result, when lightweight aggregate was mixed, the yield stress decreased significantly, and in case of type 2, the combination of micro form cell admixture (MFA) and calcined diatomite powder (DM) showed the most ideal flow characteristics. In case of type 3, the combination of micro form cell admixture (MFA), calcined diatomite powder (DM) and lightweight aggregate (L) showed the best flow characteristics.