scholarly journals Influence of process variables on quality attributes of jaggery prepared by vacuum pan evaporation technology

2020 ◽  
Vol 13 (2) ◽  
pp. 188-194
Author(s):  
Eresh Kumar Kuruba ◽  
P.V.K. Jagannadha Rao ◽  
D. Khokhar ◽  
S. Patel
Keyword(s):  
Fuzzy Logic ◽  
Moisture Content ◽  
Variable Temperature ◽  
Quality Attributes ◽  
Cane Sugar ◽  
Sugarcane Juice ◽  
Vacuum Pressure ◽  
Pan Evaporation ◽  
Process Variables ◽  
Fuzzy Logic Method

Jaggery is a solid unrefined, non- centrifugal cane sugar (NCS) with unique colour, flavor and aroma obtained from crushing of cane and evaporating of sugarcane juice. In this paper vacuum pan evaporation method were used sugarcane juice boiling at vacuum pressure (Vp : 500-700 mm of Hg), time (t:60-90 min) and temperature (T:100-1200 C). The quality attributes of jaggery developed from vacuum pan evaporator were investigated at different process variables. The developed jaggery were analyzed for physiochemical. Results showed that TSS (0 Brix) and Hardness (Hd) increased with increase in vacuum pressure and time, whereas moisture content percentage (%) and water activity (aw) decreased with increase in vacuum pressure and time at variable temperature of 1100 C. Fuzzy logic method was used to evaluate the sensory characteristic of prepared jaggery.

Pengembangan Aplikasi Pendukung Keputusan Pemilihan Program Studi dengan Metode Fuzzy Logic (Studi Kasus: Universitas Multimedia Nusantara)

2016 ◽  
Vol 7 (1) ◽  
pp. 12-18
Author(s):  
Joko Haryanto ◽  
Seng Hansun
Keyword(s):  
Decision Making ◽  
Fuzzy Logic ◽  
Decision Support ◽  
Decision Support System ◽  
Support System ◽  
System Application ◽  
Prospective Students ◽  
Fuzzy Logic Method ◽  
Index Terms ◽  
Selection Of

This paper describes the development of decision support system application to assist students who want to enter college so that no one choose the majors incorrectly. This application uses fuzzy logic method because fuzzy logic is very flexible in data which are vague and can be represented as a linguistic variable. The purpose of this application is to assist students to choose available majors at University Multimedia Nusantara which are appropriate with his/her capabilities. This application accepts five kinds of input values i.e. Mathematics, Indonesian, English, Physics, and TIK. Received input will be processed by the calculation of the system for decision-making and the application will generate output that shows how great a match for each majors. With this application, prospective students can find out where the majors that match his/her capabilities. This application has ninety nine percentage of match result accuracy. Index Terms—fuzzy logic, decision support system, UMN, selection of major

The Integrated Control of Semi-Active Suspension and Electronic Stability Program Based on Fuzzy Logic Method

2010 ◽  
Vol 29-32 ◽  
pp. 2059-2064
Author(s):  
Jian Hua Guo ◽  
Liang Chu ◽  
Xiao Bing Zhang ◽  
Fei Kun Zhou
Keyword(s):  
Fuzzy Logic ◽  
Integrated Control ◽  
Integrated System ◽  
Ride Quality ◽  
Electronic Stability Program ◽  
Vehicle Handling ◽  
Logic Control ◽  
Fuzzy Logic Method ◽  
The Individual ◽  
Integrated Control System

In this paper, an integrated system of SAS/ESP is proposed to improve vehicle handling performance and stability. The 15DOF vehicle model which describes the dynamics of the integrated system is established. A fuzzy logic control strategy is presented to control the integrated system. The simulation results show that the integrated control system can obviously improve vehicle maneuverability and ride quality much more than the individual control.

Prediction of State of Charge (SOC) of Battery Electric Vehicle

2021 ◽  
Vol 104 ◽  
pp. 65-71
Author(s):  
Illa Rizianiza ◽  
Dian Mart Shoodiqin
Keyword(s):  
Fuzzy Logic ◽  
Maximum Energy ◽  
State Of Charge ◽  
Battery Management ◽  
Charge Condition ◽  
Available Energy ◽  
Energy Needs ◽  
Fuzzy Logic Method ◽  
Input Variables ◽  
Charging And Discharging Processes

Batteries have an important thing in development of energy needs. A good performance battery, will support the device it supports. The energy that can save a battery is limited, so the battery will increase its charge and discharge cycles. Incorrect charging and discharging processes can cause battery performance to decrease. Therefore battery management is needed so that the battery can reach the maximum. One aspect of battery management is setting the state which is the ratio of available energy capacitance to maximum energy capacity. One method for estimating load states is the fuzzy logic method, namely by assessing the input and output systems of prediction. Predictor of State of Charge use Mamdani Fuzzy Logic that have temperature and voltage as input variables and State of Charge as output variable. A result of prediction State of Charge battery is represented by the number of Root Mean Square Error. Battery in charge condition has 2.7 for RMSE and level of accuracy 81.5%. Whereas Battery in discharge condition has RMSE 1.5 and level of accuracy 84.7%.

scholarly journals Using WSR-88D Polarimetric Data to Identify Bird-Contaminated Doppler Velocities

2013 ◽  
Vol 2013 ◽  
pp. 1-13 ◽  
Author(s):  
Yuan Jiang ◽  
Qin Xu ◽  
Pengfei Zhang ◽  
Kang Nai ◽  
Liping Liu
Keyword(s):  
Fuzzy Logic ◽  
Real Data ◽  
Radar Data ◽  
Second Step ◽  
Doppler Velocity ◽  
Data Quality Control ◽  
Fuzzy Logic Method ◽  
Automated Technique ◽  
Migrating Birds ◽  
Logic Method

As an important part of Doppler velocity data quality control for radar data assimilation and other quantitative applications, an automated technique is developed to identify and remove contaminated velocities by birds, especially migrating birds. This technique builds upon the existing hydrometeor classification algorithm (HCA) for dual-polarimetric WSR-88D radars developed at the National Severe Storms Laboratory, and it performs two steps. In the first step, the fuzzy-logic method in the HCA is simplified and used to identify biological echoes (mainly from birds and insects). In the second step, another simple fuzzy logic method is developed to detect bird echoes among the biological echoes identified in the first step and thus remove bird-contaminated velocities. The membership functions used by the fuzzy logic method in the second step are extracted from normalized histograms of differential reflectivity and differential phase for birds and insects, respectively, while the normalized histograms are constructed by polarimetric data collected during the 2012 fall migrating season and sorted for bird and insects, respectively. The performance and effectiveness of the technique are demonstrated by real-data examples.

scholarly journals Feature Extraction in Six Blocks to Detect and Recognize English Numbers

2021 ◽  
pp. 3790-3803
Author(s):  
Heba Kh. Abbas ◽  
Haidar J. Mohamad
Keyword(s):  
Fuzzy Logic ◽  
Feature Extraction ◽  
Computational Cost ◽  
Absolute Error ◽  
Suggested Method ◽  
Support Vector ◽  
Horizontal Line ◽  
Svm Algorithm ◽  
Fuzzy Logic Method ◽  
Logic Method

    The Fuzzy Logic method was implemented to detect and recognize English numbers in this paper. The extracted features within this method make the detection easy and accurate. These features depend on the crossing point of two vertical lines with one horizontal line to be used from the Fuzzy logic method, as shown by the Matlab code in this study. The font types are Times New Roman, Arial, Calabria, Arabic, and Andalus with different font sizes of 10, 16, 22, 28, 36, 42, 50 and 72. These numbers are isolated automatically with the designed algorithm, for which the code is also presented. The number’s image is tested with the Fuzzy algorithm depending on six-block properties only. Groups of regions (High, Medium, and Low) for each number showed unique behavior to recognize any number. Normalized Absolute Error (NAE) equation was used to evaluate the error percentage for the suggested algorithm. The lowest error was 0.001% compared with the real number. The data were checked by the support vector machine (SVM) algorithm to confirm the quality and the efficiency of the suggested method, where the matching was found to be 100% between the data of the suggested method and SVM. The six properties offer a new method to build a rule-based feature extraction technique in different applications and detect any text recognition with a low computational cost.

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