• Journal of Internet Computing and Services
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• v.23 no.3
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• pp.97-110
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• 2022

Federated learning is a learning method capable of performing model learning without transmitting learning data. The IoT or healthcare field is sensitive to information leakage as it deals with users' personal information, so a lot of attention should be paid to system design, but when using federated-learning, data does not move from devices where data is collected. Accordingly, many federated-learning implementations have been developed, but detailed research on system design for the development and operation of systems using federated learning is insufficient. This study shows that measures for the life cycle, code version management, model serving, and device monitoring of federated learning are needed to be applied to actual projects and distributed to IoT devices, and we propose a design for a development environment that complements these points. The system proposed in this paper considered uninterrupted model-serving and includes source code and model version management, device state monitoring, and server-client learning schedule management.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.22 no.4
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• pp.73-79
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• 2022

The Python language widely used in artificial intelligence (AI) projects is an interpreter language, and errors occur at runtime. In order to prevent project failure due to errors, it is necessary to handle exceptions in code that can cause exceptional situations in advance. In particular, in AI projects that require a lot of resources, exceptions that occur after long execution lead to a large waste of resources. However, since exception handling depends on the developer's experience, developers have difficulty determining the appropriate exception to catch. To solve this need, we propose an approach that recommends exceptions to catch to developers during development by learning the existing exception handling statements. The proposed method receives the source code of the try block as input and recommends exceptions to be handled in the except block. We evaluate our approach for a large project consisting of two frameworks. According to our evaluation results, the average AUPRC is 0.92 or higher when performing exception recommendation. The study results show that the proposed method can support the developer's exception handling with exception recommendation performance that outperforms the comparative models.

• KIPS Transactions on Computer and Communication Systems
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• v.10 no.11
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• pp.305-310
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• 2021

Artificial intelligence technology in the medical field initially focused on analysis and algorithm development, but it is gradually changing to web application development for service as a product. This paper describes a Urinary Stone segmentation model in abdominal CT images and an artificial intelligence web application based on it. To implement this, a model was developed using U-Net, a fully-convolutional network-based model of the end-to-end method proposed for the purpose of image segmentation in the medical imaging field. And for web service development, it was developed based on AWS cloud using a Python-based micro web framework called Flask. Finally, the result predicted by the urolithiasis segmentation model by model serving is shown as the result of performing the AI web application service. We expect that our proposed AI web application service will be utilized for screening test.

• Journal of Aerospace System Engineering
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• v.17 no.1
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• pp.59-67
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• 2023

Recently, interest in flight simulators based on HMD and mixed reality is increasing. However, they have limitations in providing various interactions and a sense of presence to pilot wearing HMD. To overcome these limitations, a mixed reality image corresponding to the interaction under the actual cockpit environment must be generated in real time and provided to the pilot. For this purpose, we proposed a mixed reality image generation method, in which the cockpit area including the pilot's body could be extracted from real image obtained from the camera attached to the HMD and then composed with virtual image to generate a high-resolution mixed reality image. Simulation results showed that the proposed method could provide mixed reality images to HMD at 30 Hz frame rate with 99% image composition accuracy.

• Journal of Korea Society of Industrial Information Systems
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• v.28 no.4
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• pp.11-19
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• 2023

The paper proposes a smart mirror system that recommends fragrances based on user emotion analysis. This paper combines natural language processing techniques such as embedding techniques (CounterVectorizer and TF-IDF) and machine learning classification models (DecisionTree, SVM, RandomForest, SGD Classifier) to build a model and compares the results. After the comparison, the paper constructs a personal emotion-based fragrance recommendation mirror model based on the SVM and word embedding pipeline-based emotion classifier model with the highest performance. The proposed system implements a personalized fragrance recommendation mirror based on emotion analysis, providing web services using the Flask web framework. This paper uses the Google Speech Cloud API to recognize users' voices and use speech-to-text (STT) to convert voice-transcribed text data. The proposed system provides users with information about weather, humidity, location, quotes, time, and schedule management.

• Journal of Korea Port Economic Association
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• v.39 no.1
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• pp.17-34
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• 2023

The maritime industry is undergoing significant changes due to digitalization and decarbonization, collectively known as "2D." This study investigates how these transformations are impacting the industry's business models. Since the changes are still ongoing, a cognitive approach was used to derive business models, rather than relying on actual case studies. The study presents experimental maritime business models that correspond to the four types of business model frameworks (or archetypes), along with recent trends for each model. The research results show that new business models are emerging in various areas, including the commercial and technical fields of the maritime industry. This thought-provoking study is significant as a pioneering investigation that will stimulate subsequent case-based research in academia and provide strategic guidance to market participants or policy makers in the maritime industry.

• Asia-pacific Journal of Multimedia Services Convergent with Art, Humanities, and Sociology
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• v.6 no.3
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• pp.461-470
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• 2016

As IoT is broadly used in many fields, the security of IoT is becoming especially important and critical issues. Security and privacy are the key issues for IoT applications, and still faced with some enormous challenges. Sensor has limited resources such as computing power, memory, battery. By means of deeply analyzing the security architecture and features in security framework. While a number of researchers have explored such security challenges and open problems in IoT, there is an unfortunate lack of a systematic study of the security challenges in the IoT landscape. This special issue features recent and emerging advances IoT architecture, protocols, services and applications. The alternative method is IoT security gateway. In this paper, we surveyed the demands and requirements. By means of deeply analyzing the security architecture and features, we analyzed the demands and requirements for security based on gateway application.

• Convergence Security Journal
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• v.22 no.3
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• pp.33-39
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• 2022

Recently, cyberattacks on infrastructure have been continuously occurring with the starting of neutralizing the user authentication function of information systems. Accordingly, the vulnerabilities of system are increasing day by day, such as the increase in the vulnerabilities of the encryption system. In this paper, an alternative technique for the symmetric key algorithm has been developed in order to build the encryption algorithm that is not easy for beginners to understand and apply. Vigenere Cipher is a method of encrypting alphabetic text and it uses a simple form of polyalphabetic substitution. The encryption application system proposed in this study uses the simple form of polyalphabetic substitution method to present an application model that integrates the three steps of encryption table creation, encryption and decryption as a framework. The encryption of the original text is done using the Vigenère square or Vigenère table. When applying to the automatic generation of secret keys on the information system this model is expected that integrated authentication work, and analysis will be possible on target system. ubstitution alphabets[3].

• Journal of Korean Society of Archives and Records Management
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• v.23 no.4
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• pp.159-178
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• 2023

A digital archive is an online platform for preserving and utilizing digital records worthy of continued preservation. However, there are no shared standards for functionality, metadata, or data technical principles across digital archives in Korea. These issues create challenges in linking distributed digital records. This study proposes a common vocabulary for digital archives to enhance the interoperability of digital records and evaluates the interoperability of the digital archive built with the common vocabulary. We collect and analyze data from the digital archive on the Korean financial crisis of 1997 to construct a knowledge graph and compare its interoperability with the knowledge graph built with RiC-O. The archive and the knowledge graph underwent evaluation using the FAIR data principles evaluation framework. The constructed knowledge graph links various objects in the archive and provides contextual information to aid in understanding the archive. The results demonstrate that a knowledge graph built with a common vocabulary significantly improves the linkage, search, and interoperability of digital records compared to a traditional archive.

• Journal of the Computational Structural Engineering Institute of Korea
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• v.37 no.3
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• pp.187-195
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• 2024

This paper presents two-dimensional boundary value problems of the stress-based gradient elasticity within the smoothed finite element method (S-FEM) framework. Gradient elasticity is introduced to address the limitations of classical elasticity, particularly its struggle to capture size-dependent mechanical behavior at the micro/nano scale. The Ru-Aifantis theorem is employed to overcome the challenges of high-order differential equations in gradient elasticity. This theorem effectively splits the original equation into two solvable second-order differential equations, enabling its incorporation into the S-FEM framework. The present method utilizes a staggered scheme to solve the boundary value problems. This approach efficiently separates the calculation of the local displacement field (obtained over each smoothing domain) from the non-local stress field (computed element-wise). A series of numerical tests are conducted to investigate the influence of the internal length scale, a key parameter in gradient elasticity. The results demonstrate the effectiveness of the proposed approach in smoothing stress concentrations typically observed at crack tips and dislocation lines.