• IEMEK Journal of Embedded Systems and Applications
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• v.19 no.3
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• pp.151-158
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• 2024

Although on-device artificial intelligence (AI) has gained attention to diagnosing machine faults in real time, most previous studies did not consider the model retraining and redeployment processes that must be performed in real-world industrial environments. Our study addresses this challenge by proposing an on-device AI-based real-time machine fault diagnosis system that utilizes continual learning. Our proposed system includes a lightweight convolutional neural network (CNN) model, a continual learning algorithm, and a real-time monitoring service. First, we developed a lightweight 1D CNN model to reduce the cost of model deployment and enable real-time inference on the target edge device with limited computing resources. We then compared the performance of five continual learning algorithms with three public bearing fault datasets and selected the most effective algorithm for our system. Finally, we implemented a real-time monitoring service using an open-source data visualization framework. In the performance comparison results between continual learning algorithms, we found that the replay-based algorithms outperformed the regularization-based algorithms, and the experience replay (ER) algorithm had the best diagnostic accuracy. We further tuned the number and length of data samples used for a memory buffer of the ER algorithm to maximize its performance. We confirmed that the performance of the ER algorithm becomes higher when a longer data length is used. Consequently, the proposed system showed an accuracy of 98.7%, while only 16.5% of the previous data was stored in memory buffer. Our lightweight CNN model was also able to diagnose a fault type of one data sample within 3.76 ms on the Raspberry Pi 4B device.

• Proceedings of the Korea Concrete Institute Conference
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• 2002.05a
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• pp.631-636
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• 2002

This study shows basic data for using as the structural lightweight aggregate. This will be the procedural method of recycling environmental close waste PET bottle lightweight aggregate(PBLA) that is rapidly increased the amount of production of waste PET bottle recently, the quality of developed PBLA and the fundamental properties by analyzing of mortar containing with PBLA. After experiment, the result shows the PBLA quality that have oven dry specific gravity of 1.39, unit volume weight of 844 kg/m$^3$ and absorption rate of 0% is satisfied with qualify regulation of lightweight aggregate. The flowability of mortar containing PBLA is increased maximum 16% with increasing mixing ratio of PBLA, however the compressive strength of mortar is decreased maximum 35% with increasing mixing ratio of PBLA.

• Korean Journal of Computational Design and Engineering
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• v.16 no.5
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• pp.344-350
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• 2011

In injection molding industries, CAE analyses are generally used to find out problems predicted during the process of manufacturing. The results of CAE analyses consist of much in formation such as meshes and stress, so that the size of data is pretty large. To reduce the size of the data and to make it easy to share, the CAE result to JT translator is proposed in this paper. The translator consists of three modules to translate CAE result to JT format; Extracting module gets ASCII data of product shape and the result values of CAE analysis. Sorting module and mapping module make an element data set and JT file with the data extracted from Extracting module respectively. To the JT files, engineers are able to append product properties and their comments, so that they can share the whole history of the analysis process. In addition, our case study shows that the size of JT format is reduced by almost 90% of its original data format.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.12 no.7
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• pp.3421-3437
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• 2018

With the enlargement of wireless technology, vehicular ad-hoc networks (VANETs) are rising as a hopeful way to realize smart cities and address a lot of vital transportation problems such as road security, convenience, and efficiency. To achieve data confidentiality, integrity and authentication applying lightweight cryptosystems is widely recognized as a rather efficient approach for the VANETs. The Khudra cipher is such a lightweight cryptosystem with a typical Generalized Feistel Network, and supports 80-bit secret key. Up to now, little research of fault analysis has been devoted to attacking Khudra. On the basis of the single nibble-oriented fault model, we propose a differential fault analysis on Khudra. The attack can recover its 80-bit secret key by introducing only 2 faults. The results in this study will provides vital references for the security evaluations of other lightweight ciphers in the VANETs.

• Proceedings of the Korean Institute of Building Construction Conference
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• 2019.11a
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• pp.10-11
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• 2019

The purpose of this study is to validate the environmental performance of the 'eco-friendly lightweight form' in the construction process. Unlike existing euro form and aluminum form, the proposed form does not require form oil during the process of concrete casting and is lightweight because it is made of engineering plastic. Therefore, eco-friendly lightweight form will reduce the $CO_2$ emissions in the construction process. To verify the hypothesis, the study compared existing forms and eco-friendly light weight form's $CO_2$ emissions in each stage in construction process when using 1,000 forms and 100 times from the LCI(Life Cycle Inventory) data. The total $CO_2$ emissions of the eco-friendly light weight form were 30,487kg $CO_2$, which equated to about 58% and 20% less emissions than the euroform and aluminum form. The result of the study verified that the eco-friendly lightweight form was effectively reduced $CO_2$ emission in the construction process.

• Journal of the Korea Institute of Building Construction
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• v.18 no.3
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• pp.211-218
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• 2018

This study examined the reliability and revision necessity of concrete standard specifications based on the comparisons with test data obtained by using domestic artificial lightweight aggregates and the contents specified in different foreign specifications including ACI 211.2, ACI 213, ACI 301, JASS 5 and CEB-FIP. To achieve the continuous particle distribution of domestic fine lightweight aggregates, the partial addition of natural sand with the maximum size of 2.5mm was required. To control the segregation and excessive bleeding in the fresh lightweight concrete, the current limitations on the water-to-binder ratio and unit water content need to be modified using lower values. In particular, a rational mixture proportion approach of lightweight concrete needs to be established for the targeted requirements of initial slump, 28-day compressive strength, air content and dry unit weight. Ultimately, significant revision of the concrete standard specifications is required considering the characteristics of domestic artificial lightweight aggregates.

• Computers and Concrete
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• v.12 no.2
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• pp.151-167
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• 2013

Prediction of concrete properties is an important issue for structural engineers and different methods are developed for this purpose. Most of these methods are based on experimental data and use measured data for parameter estimation. Three typical methods of output estimation are Categorized Linear Regression (CLR), Multiple Linear Regression (MLR) and Artificial Neural Networks (ANN). In this paper a statistical cleansing method based on CLR is introduced. Afterwards, MLR and ANN approaches are also employed to predict the compressive strength of structural lightweight aggregate concrete. The valid input domain is briefly discussed. Finally the results of three prediction methods are compared to determine the most efficient method. The results indicate that despite higher accuracy of ANN, there are some limitations for the method. These limitations include high sensitivity of method to its valid input domain and selection criteria for determining the most efficient network.

• Journal of Digital Convergence
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• v.14 no.3
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• pp.251-260
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• 2016

Knowledge map is widely used to represent knowledge in many domains. This paper presents a method of integrating the national R&D data and assists of users to navigate the integrated data via using a knowledge map service. The knowledge map service is built by using a lightweight ontology modeling method. The national R&D data is integrated with the research project as its center, i.e., the other R&D data such as research papers, patent, and project reports are connected with the research project as its outputs. The lightweight ontology is used to represent the simple relationships between the integrated data such as project-outputs relationships, document-author relationships, and document-topic relationships. Knowledge map enables us to infer the further relationships such as co-author and co-topic relationships. To extract the relationships between the integrated data, a RDB-to-Triples transformer is implemented. Lastly, we show an experiment on R&D data integration using the lightweight ontology, triples generation, and visualization and navigation of the knowledge map.

• Journal of Intelligence and Information Systems
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• v.21 no.4
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• pp.79-92
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• 2015

Knowledge map is widely used to represent knowledge in many domains. This paper presents a method of integrating the national R&D data and assists of users to navigate the integrated data via using a knowledge map service. The knowledge map service is built by using a lightweight ontology and a topic modeling method. The national R&D data is integrated with the research project as its center, i.e., the other R&D data such as research papers, patents, and reports are connected with the research project as its outputs. The lightweight ontology is used to represent the simple relationships between the integrated data such as project-outputs relationships, document-author relationships, and document-topic relationships. Knowledge map enables us to infer further relationships such as co-author and co-topic relationships. To extract the relationships between the integrated data, a Relational Data-to-Triples transformer is implemented. Also, a topic modeling approach is introduced to extract the document-topic relationships. A triple store is used to manage and process the ontology data while preserving the network characteristics of knowledge map service. Knowledge map can be divided into two types: one is a knowledge map used in the area of knowledge management to store, manage and process the organizations' data as knowledge, the other is a knowledge map for analyzing and representing knowledge extracted from the science & technology documents. This research focuses on the latter one. In this research, a knowledge map service is introduced for integrating the national R&D data obtained from National Digital Science Library (NDSL) and National Science & Technology Information Service (NTIS), which are two major repository and service of national R&D data servicing in Korea. A lightweight ontology is used to design and build a knowledge map. Using the lightweight ontology enables us to represent and process knowledge as a simple network and it fits in with the knowledge navigation and visualization characteristics of the knowledge map. The lightweight ontology is used to represent the entities and their relationships in the knowledge maps, and an ontology repository is created to store and process the ontology. In the ontologies, researchers are implicitly connected by the national R&D data as the author relationships and the performer relationships. A knowledge map for displaying researchers' network is created, and the researchers' network is created by the co-authoring relationships of the national R&D documents and the co-participation relationships of the national R&D projects. To sum up, a knowledge map-service system based on topic modeling and ontology is introduced for processing knowledge about the national R&D data such as research projects, papers, patent, project reports, and Global Trends Briefing (GTB) data. The system has goals 1) to integrate the national R&D data obtained from NDSL and NTIS, 2) to provide a semantic & topic based information search on the integrated data, and 3) to provide a knowledge map services based on the semantic analysis and knowledge processing. The S&T information such as research papers, research reports, patents and GTB are daily updated from NDSL, and the R&D projects information including their participants and output information are updated from the NTIS. The S&T information and the national R&D information are obtained and integrated to the integrated database. Knowledge base is constructed by transforming the relational data into triples referencing R&D ontology. In addition, a topic modeling method is employed to extract the relationships between the S&T documents and topic keyword/s representing the documents. The topic modeling approach enables us to extract the relationships and topic keyword/s based on the semantics, not based on the simple keyword/s. Lastly, we show an experiment on the construction of the integrated knowledge base using the lightweight ontology and topic modeling, and the knowledge map services created based on the knowledge base are also introduced.

• Journal of the Korea Society for Simulation
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• v.29 no.2
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• pp.95-103
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• 2020

The structural connection design for lightweight structure application is presented in this paper. Modeling of the welding zone and the bolted connection are suggested. For reliability verification of the established models, nonlinear analysis is performed and comparisons are made with the experimental data showing good agreement. Through comparison study, suitable welding method for structure materials is investigated. Also, stability analysis is performed by fracture load simulation for different number and position of bolts. Finally, based on the structural connection models, the lightweight structure is modeled and structural analysis was performed. Stability analysis of structural connection for lightweight structure design, through combination of welding and bolting process, showed a 31.4% decrease in the maximum stress compared to the structure without the structural connections. Importance of structural connection design is highlighted for lightweight structure stability analysis.