A Systematic Review of PCTRAN-Based Pressurized Water Reactor Transient Analysis

The impact of nuclear accidents has been a topic of debate since the construction of the first nuclear reactor, and still stands as a key issue of public concern. Several codes and simulators have been used to study the transient progression in pressurized water reactors, and to evaluate the technical measures adopted to scale down the risk of accidents. However, some of these codes are not suitable for multipurpose research and training as they require significant user expertise, leading to analysis uncertainties largely from the code user effect. This paper presents a bird-eye view of one of the most widely used nuclear reactor transient analyzer — the Personal Computer Transient Analyzer (PCTRAN). This paper discusses the comparative advantages of the simulator from the users’ perspective, with specific attention to its utilization both for research and training. The paper also demonstrates the ease of usage by simulating common transient in a pressurized water reactor. Finally, observations and possible improvements to the code to increase its usability in research, education and training are discussed. This work aims to evaluate the robustness of the simulator towards better utilization for research and training, especially in nuclear newcomer countries.

Prediction of E-Commerce Product Ratings Based on Similar Users

Together with the fast advancement of continuous expansion and the Internet of E-commerce scope, product quantity, as well as assortment, boost fast. Merchants offer many goods via going shopping customers and websites generally consider a huge amount of moment to discover the products of theirs.Within e-commerce sites, the item rating is among the primary key ingredients of an excellent pc user expertise. Many methods are working with whose users to consider the goods they wish. A comparable item suggestion is among the favorite modes working with whose customers look for items in line with the item scores. In general, the suggestions aren't personalized to a particular pc user. Exploring a great deal of solutions tends to make customers runoff as a result of the info clog but not offering proper reviews for solutions.Traditional algorithms has data sparsity and cold start issues. To overcome these problems we use cosine similarity method to identify the similarity between those vectors. The nearest similar vector ratings will be used during the estimation of the unknown ratings.The proposed methodology records ratings of each product from users and those are represented by a vector, and the cosine similarity is used a measure to identify the similarity between those vectors. The nearest similar vector ratings will be used during the estimation of the unknown ratings.Hence, By using the above approach it can overcome the above problems and also it can achieve high efficiency and accuracy in a simple manner.

Optimal multistage relaxation with automatic parameter selection

This research developed a numerical method that solves complicated fluid flow problems without requiring end-user expertise with the solver. This method is capable of obtaining a spatially accurate solution in the same time or better as a skilled user with a conventional solver. An explicit preconditioned multigrid solver was used in this research with a multistage relaxation method. The prosposed method utilizies a database with optimized relaxation method parameters for different local flow and mesh conditions. The parameters are optimized for the relaxation such that the error modes in a complex Fourier series expansion of the residual can be quickly reduced. The convergence time and iteration count of this method was compared against the same solver using default input values, as well as a pre-optimized solver, to simulate a skilled user for various geometries. Improvements in both comparisons were demonstrated.

Optimal multistage relaxation with automatic parameter selection

This research developed a numerical method that solves complicated fluid flow problems without requiring end-user expertise with the solver. This method is capable of obtaining a spatially accurate solution in the same time or better as a skilled user with a conventional solver. An explicit preconditioned multigrid solver was used in this research with a multistage relaxation method. The prosposed method utilizies a database with optimized relaxation method parameters for different local flow and mesh conditions. The parameters are optimized for the relaxation such that the error modes in a complex Fourier series expansion of the residual can be quickly reduced. The convergence time and iteration count of this method was compared against the same solver using default input values, as well as a pre-optimized solver, to simulate a skilled user for various geometries. Improvements in both comparisons were demonstrated.

PENGARUH TEKNOLOGI INFORMASI, KEAHLIAN PEMAKAI DAN INTENSITAS PEMAKAIAN TERHADAP KUALITAS INFORMASI AKUNTANSI PADA PT. BANK RAKYAT INDONESIA (PERSERO), TBK MAKASSAR

This research is using quantitative study aimed to see the influence of information technologi use, user expertise, and the intensity of usage on the quality of accounting information. The population of this study was PT Bank Rakyat Indonesia (Persero), Tbk, Makassar Branch. The selection of the sample with total sampling methods. The data used in this study of primary data. Data analysis techniques using multiple regression analysis. The results of this study indicate that information technologi use, user expertise, and the intensity of usage have a positive effect and significant on quality of accounting information. Keyword: Information Technologi Use, User Expertise, The Intensity Of Usage, and Quality Of Accounting Information

Machine Learning Based Surface Velocimetry

<p>Streamflow measurement is of great importance in hydrological research, water management and water infrastructure design. Traditional measurement methods typically employ intrusive techniques, and under certain conditions, obtaining accurate streamflow data with these techniques can be challenging because of safety concerns, especially in some critical circumstances, such as during flood flows. The advent of new instrumentation and technologies, and in particular advances in digital imagery, has led to the emergence of non-intrusive novel image-based technologies that can be used to estimate surface velocity, which in turn can be used to estimate streamflow. Image based technologies, most of which are based on correlation between consecutive images, have the potential for remote and on demand measurements and can provide data when the application of other traditional methods are not possible, reliable or safe. In this study, we present a novel machine learning based optical flow algorithm for streamflow surface velocimetry estimation. The developed algorithm is tested in different flow conditions and using drone and fixed photogrammetry. This method appears to outperform all the other available image-based surface velocimetry approaches (i.e. correlation based and classical optical flow methods). Moreover, this method requires the least user involvement for velocity estimation and thus reduces the impact or arbitrary choices linked to user expertise.</p>