Gyro-average method for global gyrokinetic particle simulation in realistic tokamak geometry

Gyro-average is a crucial operation to capture the essential finite Larmor radius effect (FLR) in gyrokinetic simulation. In order to simulate strongly shaped plasmas, an innovative multi-point average method based on non-orthogonal coordinates has been developed to improve the accuracy of the original multi-point average method in gyrokinetic particle simulation. This new gyro-average method has been implemented in the gyrokinetic toroidal code (GTC). Benchmarks have been carried out to prove the accuracy of this new method. In the limit of concircular tokamak, ion temperature gradient (ITG) instability is accurately recovered for this new method and consistency is achieved. The new gyro-average method is also used to solve the gyrokinetic Poisson equation, and its correctness has been confirmed in the long wavelength limit for realistic shaped plasmas. The improved GTC code with the new gyro-average method has been used to investigate the ITG instability with EAST magnetic geometry. The simulation results show that the correction induced by this new method in the linear growth rate is more significant for short wavelength modes where the finite Larmor radius (FLR) effect becomes important. Due to its simplicity and accuracy, this new gyro-average method can find broader applications in simulating the shaped plasmas in realistic tokamaks.

Front vehicle detection based on improved fusion method for lidar and visual image

In order to ensure the detection accuracy, an improved adaptive weighted (IAW) method is proposed in this paper to fuse the data of images and lidar sensors for the vehicle object’s detection. Firstly, the IAW method is proposed in this paper and the first simulation is conducted. The unification of two sensors’ time and space should be completed at first. The traditional adaptive weighted average method (AWA) will amplify the noise in the fusion process, so the data filtered with Kalman Filter (KF) algorithm instead of with the AWA method. The proposed IAW method is compared with the AWA method and the Distributed Weighted fusion KF algorithm in the data fusion simulation to verify the superiority of the proposed algorithm. Secondly, the second simulation is conducted to verify the robustness and accuracy of the IAW algorithm. In the two experimental scenarios of sparse and dense vehicles, the vehicle detection based on image and lidar is completed, respectively. The detection data is correlated and merged through the IAW method, and the results show that the IAW method can correctly associate and fuse the data of the two sensors. Finally, the real vehicle test of object vehicle detection in different environments is carried out. The IAW method, the KF algorithm, and the Distributed Weighted fusion KF algorithm are used to complete the target vehicle detection in the real vehicle, respectively. The advantages of the two sensors can give full play, and the misdetection of the target objects can be reduced with proposed method. It has great potential in the application of object acquisition.

Sistem Forecasting Keuangan Inventaris Sarana dan Prasarana dengan Metode Naive Approach pada Universitas CIC

University Catur Insan Cendekia (UCIC) is a university located at Kesambi street number 202 Cirebon city. As one of the new universities in Cirebon city of course, would need inventory records of facilities and infrastructure that’s what at the university. Additionally, records spending on facilities and infrastucture costs is important. To optimize that cost recording requires a system. To Improve management facilities and infrastructure requires data related to facilities conditions and infrastructure. Naïve’s own method was the result of his prediction of the previous year’s real data as a benchmark for forecasting the following year. The process of this method is to collect the data of the cost of facilities and infrastructure spending first, after which the system will predict the cost of facilities and infrastructure using the formula N= t-1, in addition to this web based research using the framework codeigniter. The forecast method conducted in the study using the naïve approach method, which is more effective than the moving average method. Naïve’s method was used to predict the cost data of facilities and infrastructure available at UCIC. The study also had the naïve approach prediction reached the following year’s prediction.

KOMPARASI METODE MOVING AVERAGE DAN TREND PROJECTION SEBAGAI ALAT UKUR PERENCANAAN PRODUKSI PADA UD. JAYA ABADI KABUPATEN PROBOLINGGO

The purpose of this research is to find out the comparison of forecasting calculations using the moving average and trend projection methods as a means measuring tool in production planning at UD. Jaya Abadi Probolinggo Regency. The type of research used is quantitative descriptive. Population and sample in this research is UD production data. Jaya Abadi Probolinggo Regerency from 2018 to March 2021. Data analysis using the moving average and trend projection methods which aim to predict future production or the next period. The results showed that the value of MAD (Mean Absolute Deviation) and the MSE (Mean Square Error) moving average values are higher than the MAD and the MSE trend projection, so the company you should use trend projection because when viewed from the results of the comparision of MAD and MSE, this method has a smaller error rate than the moving average method. So it can be concluded that the trend projection method can be used in planning bread production at UD. Jaya Abadi Probolinggo Regency

Hardware efficient circuit for low error logarithmic converter

The need to implement high-speed Signal processing applications in which multiplication and division play a vital role made logarithmic arithmetic a prominent contender over the traditional arithmetic operations in recent years. But the logarithm and antilogarithm converters are the bottlenecks. In order to reduce the logarithmic conversion complexity, several works have been introduced from time to time for correcting the error in Mitchell’s algorithm but at the cost of hardware. In this work, we propose a 32-bit binary to the binary logarithmic converter with a simple correction circuit compared with existing techniques. Unlike the current methods that use the linear piece-wise approximation in the mantissa, we propose a weighted average method to correct the error in Mitchell’s approximation. The maximum error percentage from the proposed work is 0.91%, which is 16.9% of Mitchell’s error percentage.

Analisis Penerapan Metode First In First Out ( Fifo ) Dan Average Untuk Penilaian Persediaan Kertas HVS Pada Muara Kaman Copy & Print Center Di Tenggarong

The purpose of this study was to compare the valuation of HVS paper inventories with the First In First Out (FIFO) method and the Average method in the Muara Kaman photocopy business in Tenggarong. The analytical tool used is descriptive analysis. The method of descriptive analysis is to describe the nature of something that has been going on at the time the research is being conducted and examines the causes of certain symptoms. Furthermore, this analysis uses the FIFO and Average methods in inventory valuation. The results of calculations using the average method produce cost of goods sold which is greater than the First In First Out (FIFO) method. On the other hand, the calculation using the First In First Out (FIFO) method will result in a higher ending inventory value than the average method. So if you want to report the value of current assets (especially inventory) is greater then you can use the FIFO method. Keywords: Inventory Valuation, FIFO, Average

Sistem Informasi Persediaan Barang Dengan Metode Weight Moving Average Berbasis Android Di Toko Awd Mranggen

The AWD Mranggen store is a store that is engaged in the sale of bags, belts, shoes with sales developments increasing from year to year, with fairly tight business competition, the AWD Mranggen store must be able to calculate the estimated number of items to be purchased based on previous sales data, the prediction is very influential on the decision to determine the number of items to be provided by the AWD Mranggen Store for the next sales period data. Inventory of goods that are not right cause some losses in terms of time and also costs, it is necessary to have a forecasting system. Forecasting is a technique to identify a model that can be used to predict conditions in the future. By using the weight moving average method, it can be seen that the error value is more than smaller than other methods and the estimated results can be more precise so that it can help owners make decisions in carrying out inventory.