Efficiently detecting the nearest navigational dangers in Electronic Chart Display and Information Systems (ECDIS) remains pivotal for maritime safety. However, the software implementation of ADMAR(Automatic Distance measurement and Ranging) functionality faced challenges, necessitating extensive computations across ENC cells and impacting real-time performance. To address this, we present a novel method employing dynamic programming. Our proposed algorithm strategically organizes nodes into a tree structure, optimizing the search process towards nodes likely to contain navigational hazards. Implementation of this method resulted in a notable sevenfold reduction in computation time compared to the conventional Brute Force approach. Our study established a direct correlation between the ADMAR functionality and node count, achieving error margins deemed acceptable for practical navigation scenarios. Despite this theoretical progress, minor errors in results prompt further refinement. Consequently, future iterations will explore varying values for N, considering hierarchy and cell sizes to enhance algorithmic precision. This research signifies a potential advancement in optimizing navigational danger detection within ECDIS, offering a promising avenue for improved efficiency. By introducing a dynamic programming-based approach, we have streamlined the detection process while acknowledging the scope for algorithmic refinement in subsequent studies. Our findings underline the feasibility of employing dynamic programming to enhance navigational danger detection, emphasizing its potential in ensuring maritime safety. This work lays a foundation for future research endeavors, aiming to fine-tune algorithms and advance navigational safety measures in ECDIS.

In nuclear power plant environments, the analysis of gamma-emitting waste materials with complex shapes can be challenging. ISOCS (In-Situ Objective Counting System) is employed to measure the gamma-emitting radionuclide concentrations. However, it is crucial to validate the accuracy of ISOCS measurements. This study aims to validate the accuracy of ISOCS measurement results for spent filters. The ISOCS measurement process begins with modeling and efficiency calculations of the target spent filters using ISOCS software. ISOCS offers the advantage of direct measurement assessment by incorporating shielding materials and collimators into the detector efficiency calculation during the modeling process, without the need for separate efficiency correction sources. To validate the accuracy of ISOCS measurement results, the measured radioactivity values were used as input data for the MicroShield computer code to derive dose rates. These dose rates were then compared to the dose rates measured on-site, confirming the reliability of ISOCS measurements. In the field, ISOCS gamma measurements and surface dose rates were measured for three Cavity filters and four RCP Seal Injection filters. The measured dose rate for the Cavity filters was around 270 Svhr, and the computed values using MicroShield showed an error of approximately 12%. Despite modeling and calculation errors in computer analysis and potential uncertainties in the measurement environment and instrument, the computed values closely matched the measured values. However, the measured dose rate for the RCP Seal Injection filters ranged 2.9~8 Svhr, which is very low and close to background levels. When compared to the results of computer analysis, an error ranging from 27% to 97% was observed. It is concluded that validating the accuracy in the low dose rate range close to background levels is challenging through a comparison of calculated and measured dose rates.

Currently, in domestic nuclear power plants (NPP), the spent filters (SFs) used for the purpose of reducing and purifying the radiation of the primary cooling water system are temporarily stored in an untreated state. In order to dispose of SFs, radioactive nuclide analysis (RNA) of SFs is required to be conducted. As segmented gamma scanner (SGS) is already being used in Kori NPP, utilizing SGS for RNA of SFs would be practical and economical. In this paper, factors required to be considered to improve accuracy of SGSs for RNA of SFs are studied. The analysis of the nuclide inventory of the packaging drum for radioactive waste should be performed by the indirect drum nuclide analysis method. The material of the SFs is iron (SS304) on the outside, and paper on the inside. In addition, to meet disposal acceptance criteria, radioactive waste drums are packaged in thick grouting or shielding drums. Therefore, it is necessary to derive an appropriate correction method for high inhomogeneity and thick media. Considering these factors, evaluating radionuclides inventory plans to measure gamma rays in SGS mode. Correct the gamma ray measurement by examining the medium attenuation factor and error factors. In this way, the inventory of gamma nuclides is calculated, and the specific radioactivity of beta ray and alpha particle emitting nuclides other than gamma rays is planned to be calculated by applying scaling factors.