scholarly journals Enhanced Temperature Control Method Using ANFIS with FPGA

2014 ◽  
Vol 2014 ◽  
pp. 1-8 ◽  
Author(s):  
Chiung-Wei Huang ◽  
Shing-Tai Pan ◽  
Jun-Tin Zhou ◽  
Cheng-Yuan Chang
Keyword(s):  
Temperature Control ◽  
Inductively Coupled Plasma ◽  
Fuzzy Inference ◽  
Control Method ◽  
Etching Process ◽  
Inference System ◽  
Inductively Coupled ◽  
Field Programmable ◽  
Medium Vacuum

Temperature control in etching process is important for semiconductor manufacturing technology. However, pressure variations in vacuum chamber results in a change in temperature, worsening the accuracy of the temperature of the wafer and the speed and quality of the etching process. This work develops an adaptive network-based fuzzy inference system (ANFIS) using a field-programmable gate array (FPGA) to improve the effectiveness. The proposed method adjusts every membership function to keep the temperature in the chamber stable. The improvement of the proposed algorithm is confirmed using a medium vacuum (MV) inductively-coupled plasma- (ICP-) type etcher.

scholarly journals A Soft Computing Approach to Crack Detection and Impact Source Identification with Field-Programmable Gate Array Implementation

2013 ◽  
Vol 2013 ◽  
pp. 1-12 ◽  
Author(s):  
Arati M. Dixit ◽  
Harpreet Singh
Keyword(s):  
Fuzzy Logic ◽  
Soft Computing ◽  
Fuzzy Inference System ◽  
Source Identification ◽  
Field Programmable Gate Array ◽  
Crack Detection ◽  
Fuzzy Inference ◽  
Inference System ◽  
Field Programmable ◽  
Computing Approach

The real-time nondestructive testing (NDT) for crack detection and impact source identification (CDISI) has attracted the researchers from diverse areas. This is apparent from the current work in the literature. CDISI has usually been performed by visual assessment of waveforms generated by a standard data acquisition system. In this paper we suggest an automation of CDISI for metal armor plates using a soft computing approach by developing a fuzzy inference system to effectively deal with this problem. It is also advantageous to develop a chip that can contribute towards real time CDISI. The objective of this paper is to report on efforts to develop an automated CDISI procedure and to formulate a technique such that the proposed method can be easily implemented on a chip. The CDISI fuzzy inference system is developed using MATLAB’s fuzzy logic toolbox. A VLSI circuit for CDISI is developed on basis of fuzzy logic model using Verilog, a hardware description language (HDL). The Xilinx ISE WebPACK9.1i is used for design, synthesis, implementation, and verification. The CDISI field-programmable gate array (FPGA) implementation is done using Xilinx’s Spartan 3 FPGA. SynaptiCAD’s Verilog Simulators—VeriLogger PRO and ModelSim—are used as the software simulation and debug environment.

scholarly journals Nutritional Evaluation and Risk Assessment of the Exposure to Essential and Toxic Elements in Dogs and Cats through the Consumption of Pelleted Dry Food: How Important Is the Quality of the Feed?

Toxics ◽  
2021 ◽  
Vol 9 (6) ◽  
pp. 133
Author(s):  
Ana Macías-Montes ◽  
Manuel Zumbado ◽  
Octavio P. Luzardo ◽  
Ángel Rodríguez-Hernández ◽  
Andrea Acosta-Dacal ◽  
...  
Keyword(s):  
Risk Assessment ◽  
Inductively Coupled Plasma ◽  
Reference Value ◽  
Inorganic Elements ◽  
Inductively Coupled ◽  
Icp Ms ◽  
Plasma Mass Spectrometry ◽  
Dry Food ◽  
Hazard Indexes

Dry feed for pets lacks specific legislation regarding maximum residue limits for inorganic elements. The aim of the present study was to determine the content of 43 inorganic elements in dog and cat feed, studying whether there were differences according to the supposed quality of the food and performing the risk assessment for health. Thirty-one and thirty packages of pelleted dry food for cats and dogs, respectively, were analyzed. After acidic microwave-assisted digestion, elements were detected and quantified by Inductively Coupled Plasma-Mass Spectrometry (ICP-MS). In general, we did not observe important differences in the content of elements according to the supposed quality of the brand. Among trace elements, selenium and manganese are above the dietary reference value. Arsenic and mercury showed the highest acute hazard indexes, which make them risk factors for the health of dogs and cats. Aluminum, uranium, antimony and vanadium contents were above the toxic reference value and showed the highest acute hazard indexes. It is necessary to improve the legislation regarding the food safety of pets, for their health and to protect the rights of consumers.

scholarly journals Aplikasi Pengambilan Keputusan dengan Metode Tsukamoto pada Penentuan Tingkat Kepuasan pelanggan

CAUCHY ◽  
2015 ◽  
Vol 4 (1) ◽  
pp. 10 ◽  
Author(s):  
Venny Riana Riana Agustin ◽  
Wahyu Henky Irawan
Keyword(s):  
Decision Making ◽  
Fuzzy Logic ◽  
Fuzzy Inference ◽  
Weighted Average ◽  
Fuzzy Rules ◽  
Quality Of Services ◽  
Inference System ◽  
A Value ◽  
Fuzzy Logic Analysis

Tsukamoto method is one method of fuzzy inference system on fuzzy logic for decision making. Steps of the decision making in this method, namely fuzzyfication (process changing the input into kabur), the establishment of fuzzy rules, fuzzy logic analysis, defuzzyfication (affirmation), as well as the conclusion and interpretation of the results. The results from this research are steps of the decision making in Tsukamoto method, namely fuzzyfication (process changing the input into kabur), the establishment of fuzzy rules by the general form IF a is A THEN B is B, fuzzy logic analysis to get alpha in every rule, defuzzyfication (affirmation) by weighted average method, as well as the conclusion and interpretation of the results. On customers at the case, in value of 16 the quality of services, the value of 17 the quality of goods, and value of 16 a price, a value of the results is 45,29063 and the level is low satisfaction

scholarly journals Economic Security Threat Modelling of a Commercial Bank in a Globalized Economy

2020 ◽  
pp. 142-151
Author(s):  
О.V. Dymchenko ◽  
О.О. Rudachenko ◽  
P. Gazzola
Keyword(s):  
Commercial Bank ◽  
Fuzzy Inference ◽  
A Priori ◽  
Economic Security ◽  
Security Threat ◽  
Research Information ◽  
Inference System ◽  
Security Research ◽  
Threat Modelling

In the paper, one develops a set of models for diagnosing threats to the economic security of a commercial bank, which allows improving the quality of decisions forming and making on managing the safe functioning and development of the bank. The bank's economic security research system has been developed, it includes 3 main blocks: research information space creation; assessment and analysis of the security of a commercial bank; generalization, and formation of decisions on the economic security of a commercial bank. The research made it possible to draw an inference of a theoretical, methodological, and applied nature that reflects the solution of the tasks set following the purpose of the study. A set of models has been built with modern tools of economic and mathematical modelling to improve the quality of decisions made to manage the bank's security and reduce the risks of threats. A model for calculating the bank's economic security indicator has been developed, which includes the following main stages: the construction of a structural scheme taking into account the rules of the theory of banking functioning security, then the terms and their membership functions are set for each input and output variable of the fuzzy inference system under consideration. Results of the response surface for the model are shown in the figure on the graphs of the dependence of the bank's economic security indicator on various input components. The paper requires that it is convenient to diagnose the state of economic security of a bank using fuzzy logic, this allows getting a clear quantitative representation of economic security state of the bank, as the indicators used for diagnostics may be indistinct and approximate and this a priori cannot give an adequate result when accurately calculated.

Embracing Macro-, Meso-, and Micro-Levels of Analysis of FIS-Based LMS Users' Quality of Interaction

2015 ◽  
pp. 355-387
Keyword(s):  
Online Education ◽  
Fuzzy Inference ◽  
Systemic Approach ◽  
Levels Of Analysis ◽  
Independent Group ◽  
Inference System ◽  
Time Period ◽  
Objective Interpretation ◽  
Learning Functions

An essential factor in determining the efficiency of the online education is the users' quality of interaction (QoI) with LMSs. In this chapter, the macro-meso-micro structure analysis is adopted, to examine the Fuzzy Inference System (FIS)-based approach of QoI, taking into account the LMS users' (professors' and students') interactions within a b-learning environment, in order to quantitatively estimate a normalized index of their QoI, accordingly. Additionally, for capturing the dynamics of the users interacting with the LMS, the data corresponding to a 51-week LMS Moodle usage time-period of two consequent academic years (2009/2010 and 2010/2011) at a HEI were analyzed. Finally, based on a systemic approach of the derived QoI, user-dependent/independent (group-like) (dis)similarities in LMS interaction trends, correlations, distributions and dependencies with the time-period of the LMS use are analyzed, towards an effort to contribute to a more objective interpretation of the way LMS Moodle-based b-learning functions within the HEIs.

scholarly journals A novel vertical handover algorithm based on Adap-tive Neuro-Fuzzy Inference System (ANFIS)

2018 ◽  
Vol 7 (1) ◽  
pp. 74 ◽  
Author(s):  
Eman Zakaria ◽  
Amr A.Awamry ◽  
Abdelkerim Taman ◽  
Abdelhalim Zekry
Keyword(s):  
Fuzzy Inference ◽  
Heterogeneous Wireless Networks ◽  
Access Network ◽  
Signal Strength ◽  
Vertical Handover ◽  
Inference System ◽  
Internet Connection ◽  
Neuro Fuzzy ◽  
Always Best Connected

Nowadays, there is an increased demand on an Internet connection anywhere at any time. Therefore, one has to exploit all available heterogeneous wireless networks where the target is achieving the Always Best Connected (ABC) among the different networks like UMTS, WiMAX, and WLAN. So, vertical handover techniques are used to ensure the best connectivity anywhere at any time. In this paper, novel ANFIS-based vertical handover is presented and compared with TOPSIS algorithm and other algorithms as a representative of Multi-criteria decision making (MCDM) algorithm's family. The simulation results show that the proposed handover technique provided better performance in terms of minimizing the time delay and improving the quality of service (QOS). This is because ANFIS requires iterations only in training phase otherwise, it has a much faster response. Our simulations considered the effect of many practical parameters on handover, such as subscriber speed, jitter, initial delay, bandwidth and received signal strength (RSS).According to these parameters, output values produced, which is utilized to choose the best candidate access network.

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