• Journal of the Korea Institute of Information Security & Cryptology
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• v.13 no.1
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• pp.115-129
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• 2003

This paper presents a semi-automated formal verification method based on the famous SVO logic, and discusses its experimental results. We discuss several problems on automating the SVO logic and design its derivative, ASVO logic for automation. Also the proposed method is implemented by the Isabelle/Isar system. As a result, we verified the well-known weakness of the NSSK protocol that is vulnerable to the Denning-Sacco attack, using our Isabelle/ASVO system. Finally, we refined the protocol by following the logical consequence of the ASVO verification.

• Journal of KIBIM
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• v.10 no.3
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• pp.22-32
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• 2020

Apartment building site planning is one of time consuming and labor-intensive tasks in architectural design field, due to its complexity in zoning regulations, building codes, local restrictions, and site-specific conditions. In other words, the process can be seen as a very complicated mathematical function with layers of variables and parameters, which ironically can be automated using computational methods on parametric tools. In this paper, a practical method of automating site planning of an apartment complex has been proposed by utilizing parametric approaches in Rhino 3D and Grasshopper. Two primary parameters, building heights and positions, determine the efficacy of building layouts under all regulatory standards, thus testing out numerous combinations of the two will produce some successful layout alternatives. For this, equation solver has been used for iterating the parametric model to sort out meaningful results among others. It also has been proven that the proposed process significantly reduced the time in site planning down to less than an hour on most cases, and many successful alternatives could be obtained by using multiple computers. Post evaluation processes such as day light and view shed analysis helped sort out the best performing ones out of functioning alternatives.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.16 no.4
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• pp.1166-1186
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• 2022

Artistic font design has become an integral part of visual media. However, without prior knowledge of the font domain, it is difficult to create distinct font styles. When the number of characters is limited, this task becomes easier (e.g., only Latin characters). However, designing CJK (Chinese, Japanese, and Korean) characters presents a challenge due to the large number of character sets and complexity of the glyph components in these languages. Numerous studies have been conducted on automating the font design process using generative adversarial networks (GANs). Existing methods rely heavily on reference fonts and perform font style conversions between different fonts. Additionally, rather than capturing style information for a target font via multiple style images, most methods do so via a single font image. In this paper, we propose a network architecture for generating multilingual font sets that makes use of geometric structures as content. Additionally, to acquire sufficient style information, we employ multiple style images belonging to a single font style simultaneously to extract global font style-specific information. By utilizing the geometric structural information of content and a few stylized images, our model can generate an entire font set while maintaining the style. Extensive experiments were conducted to demonstrate the proposed model's superiority over several baseline methods. Additionally, we conducted ablation studies to validate our proposed network architecture.

• Nuclear Engineering and Technology
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• v.53 no.7
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• pp.2151-2161
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• 2021

Nuclear data (ND) sensitivity and uncertainty (S/U) quantification in shielding applications is performed using deterministic and probabilistic approaches. In this paper the validation of the newly developed deterministic program package ASUSD (ADVANTG + SUSD3D) is presented. ASUSD was developed with the aim of automating the process of ND S/U while retaining the computational efficiency of the deterministic approach to ND S/U analysis. The paper includes a detailed description of each of the programs contained within ASUSD, the computational workflow and validation results. ASUSD was validated on two shielding benchmark experiments from the Shielding Integral Benchmark Archive and Database (SINBAD) - the fission relevant ASPIS Iron 88 experiment and the fusion relevant Frascati Neutron Generator (FNG) Helium Cooled Pebble Bed (HCPB) Test Blanket Module (TBM) mock-up experiment. The validation process was performed in two stages. Firstly, the Denovo discrete ordinates transport solver was validated as a standalone solver. Secondly, the ASUSD program package as a whole was validated as a ND S/U analysis tool. Both stages of the validation process yielded excellent results, with a maximum difference of 17% in final uncertainties due to ND between ASUSD and the stochastic ND S/U approach. Based on these results, ASUSD has proven to be a user friendly and computationally efficient tool for deterministic ND S/U analysis of shielding geometries.

• Design & Manufacturing
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• v.16 no.1
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• pp.21-26
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• 2022

In the CNC machining process, problems such as lowering of machine operation rate, setting errors, and machining precision occur due to the increase in setting time and preparation time. These machining errors cause delays in delivery and increase in cost due to an increase in the number of mounting and dismounting of the workpiece, an increase in measurement and reprocessing time, and an increase in the finishing time in the assembly process. Therefore, in this study, by automating the setting of the work piece using OMV (On Machine Verification), which is a meteorological measurement system, the preparation time for machining the work piece and the setting accuracy were improved, the rework rate was reduced, and the mold manufacturing process was shortened. Through the advancement, standardzation, and automation of the mold part manufacturing process, we have improved productivity by minimizing low-value-added repetitive tasks. In addition, the measurement time was reduced by more than 50% and the machining measurement rate was improved by more than 20%, eliminating repetitive work for correcting machining defects, and reducing the work preparation time by more than 15% through automatic setting.

• Design & Manufacturing
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• v.16 no.3
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• pp.16-21
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• 2022

In order to reduce the weight of parts and materials for the development of high-efficiency engines in accordance with the strengthening of automobile fuel efficiency regulations, the existing casting material is changed to a iron plate material, and plastic processing and turning operations are performed to lighten the weight and reduce the manufacturing cost. Among the pulley components applied to the damper pulley, the HUB product was manufactured by plastic machining instead of the existing casting process, and the inspection standardized for automating the inner diameter and parallelism measurement of the turning result of the new hub part with improved quality, and the inspection system for this Development of design and operation software to automate the inspection of the inner diameter and parallelism of the hub was described. The representative specifications of the development equipment are a hub inner diameter 22mm inspection system, a three-point inspection system with a parallelism of 0.15mm on the top.

• International Journal of Computer Science & Network Security
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• v.22 no.11
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• pp.33-42
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• 2022

One of the most pressing socioeconomic problems confronting humanity on a worldwide scale is food security, particularly in light of the expanding population and declining land productivity. These causes have increased the number of people in the world who are at risk of starving and have caused the natural ecosystems to degrade at previously unheard-of speeds. Happily, the Internet of Things (IoT) development provides a glimmer of light for those worried about food security through smart agriculture-a development that is particularly relevant to automating food production operations in order to reduce labor expenses. When compared to conventional farming techniques, smart agriculture has the benefit of maximizing resource use through precise chemical input application and regulation of environmental factors like temperature and humidity. Farmers may make data-driven choices about the possibility of insect invasion, natural disasters, anticipated yields, and even prospective market shifts with the use of smart farming tools. The technical foundation of smart agriculture serves as a potential response to worries about food security. It is made up of wireless sensor networks and integrated cloud computing modules inside IoT.

• International Journal of Computer Science & Network Security
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• v.23 no.9
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• pp.37-46
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• 2023

The main aim of the article is to solve the problem of automating price monitoring using marketing forecasting methods and Excel functionality under martial law. The study used the method of algorithms, trend analysis, correlation and regression analysis, ANOVA, extrapolation, index method, etc. The importance of monitoring consumer price developments in market pricing at the macro and micro levels is proved. The introduction of a Dummy variable to account for the influence of martial law in market pricing is proposed, both in linear multiple regression modelling and in forecasting the components of the Consumer Price Index. Experimentally, the high reliability of forecasting based on a five-factor linear regression model with a Dummy variable was proved in comparison with a linear trend equation and a four-factor linear regression model. Pessimistic, realistic and optimistic scenarios were developed for forecasting the Consumer Price Index for the situation of the end of the Russian-Ukrainian war until the end of 2023 and separately until the end of 2024.

• International conference on construction engineering and project management
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• 2005.10a
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• pp.569-574
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• 2005

This paper presents the core technology of Construction Business Process Automation to model and automate construction business processes. Business Process Reengineering (BPR) and Automation (BPA) have been recognized as one of the important aspects in construction business management. However, BPR requires a lot of efforts to identify, document, implement, execute, maintain, and keep track thousands of business processes to deliver a project. Moreover, existing BPA technologies used in existing Enterprise Resource Planning (ERP) systems do not lend themselves to effective scalability for construction business process management. Application of Workflow and Object Technologies would be quite effective in implementing a scalable enterprise application for construction community. This paper present the technologies and methodologies for automating construction business processes by addressing how: 1) Automated construction management tasks are developed as software components, 2) The process modeling is facilitated by dragging-and dropping task components in a network, 3) Raising business requests and instantiating corresponding process instances are delivered, and 4) Business process instances are executed by using workflow technology based on real-time simulation engine. This paper presents how the construction business process automation is achieved by using equipment reservation and cancellation processes simplified intentionally.

• Nuclear Engineering and Technology
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• v.55 no.9
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• pp.3277-3290
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• 2023

Nuclear power plant (NPP) operations with multiple objectives and devices are still performed manually by operators despite the potential for human error. These operations could be automated to reduce the burden on operators; however, classical approaches may not be suitable for these multi-objective tasks. An alternative approach is deep reinforcement learning (DRL), which has been successful in automating various complex tasks and has been applied in automation of certain operations in NPPs. But despite the recent progress, previous studies using DRL for NPP operations have limitations to handle complex multi-objective operations with multiple devices efficiently. This study proposes a novel DRL-based approach that addresses these limitations by employing a continuous action space and straightforward binary rewards supported by the adoption of a soft actor-critic and hindsight experience replay. The feasibility of the proposed approach was evaluated for controlling the pressure and volume of the reactor coolant while heating the coolant during NPP startup. The results show that the proposed approach can train the agent with a proper strategy for effectively achieving multiple objectives through the control of multiple devices. Moreover, hands-on testing results demonstrate that the trained agent is capable of handling untrained objectives, such as cooldown, with substantial success.