scholarly journals Leak detection and localization in a pipeline system by application of statistical analysis techniques.

1985 ◽  
Vol 51 (468) ◽  
pp. 1976-1981
Author(s):  
Toshio FUKUDA ◽  
Toyokazu MITSUOKA
Keyword(s):  
Statistical Analysis ◽  
Leak Detection ◽  
Pipeline System ◽  
Analysis Techniques ◽  
Detection And Localization

Leak detection and localization for pipelines using multivariable fuzzy learning backstepping

2021 ◽  
pp. 1-12
Author(s):  
Farzin Piltan ◽  
Jong-Myon Kim
Keyword(s):  
Transmission Lines ◽  
Leak Detection ◽  
Support Vector ◽  
Robust Learning ◽  
Regression Techniques ◽  
Space Formulation ◽  
Points Of View ◽  
Detection And Localization ◽  
Fuzzy Learning ◽  
Backstepping Algorithm

Pipelines are a nonlinear and complex component to transfer fluid or gas from one place to another. From economic and environmental points of view, the safety of transmission lines is incredibly important. Furthermore, condition monitoring and effective data analysis are important to leak detection and localization in pipelines. Thus, an effective technique for leak detection and localization is presented in this study. The proposed scheme has four main steps. First, the learning autoregressive technique is selected to approximate the flow signal under normal conditions and extract the mathematical state-space formulation with uncertainty estimations using a combination of robust autoregressive and support vector regression techniques. In the next step, the intelligence-based learning observer is designed using a combination of the robust learning backstepping method and a fuzzy-based technique. The learning backstepping algorithm is the main part of the algorithm that determines the leak estimation. After estimating the signals, in the third step, their classification is performed by the support vector machine algorithm. Finally, to find the size and position of the leak, the multivariable backstepping algorithm is recommended. The effectiveness of the proposed learning control algorithm is analyzed using both experimental and simulation setups.

scholarly journals Analisis Karakter Kerja Keras Siswa Kelas VII C dan VII E SMPN 1 Kota Jambi (Analysis of Student's Hard Work Character at SMPN 1 Jambi City)

2019 ◽  
Vol 2 (1) ◽  
pp. 1
Author(s):  
Rusnaningsih Rusnaningsih ◽  
Sri Sukma Ajeng Ningtyas
Keyword(s):  
Statistical Analysis ◽  
Hard Work ◽  
Analysis Techniques ◽  
Descriptive Statistical Analysis

This study purposes to analyze the character of the hard work of students of class VIIC and class VII E SMP Negeri 1 Jambi City. This study uses descriptive quantitativeresearch methods. While the type of research used is observation with a test assessmentinstrument in the form of a questionnaire with hard working character variables.The subjects of this study were students of class VII C and VII E SMP Negeri 1 KotaJambi, with a total number of respondents as many as 61 respondents. The data analysistechnique used is descriptive statistical analysis techniques. The results of the studystated that the character questionnaire of hard work of students in class VII C on averagebelonged to the category "Good" with a percentage of 81.3% of statements answeredwell by students and 6.3% of statements answered badly by students. While the resultsof research in class VII E on average belong to the category "Good" with 65.6% of statementsanswered both by students and 3.1%, answered not well by students. Based onthe results of the questionnaire, it can be concluded that students of class VII C and classVII E in SMP Negeri 1 Kota Jambi have had the character of hard work in the learningprocess.

scholarly journals Analysis of chicken and turkey meat consumption by segmentation of Spanish consumers using food-related lifestyle

2021 ◽  
Vol 19 (1) ◽  
pp. e0101 ◽  
Author(s):  
Amparo Baviera-Puig ◽  
Luis Montero-Vicente ◽  
Carmen Escribá-Pérez ◽  
Juan Buitrago-Vera
Keyword(s):  
Statistical Analysis ◽  
Market Segmentation ◽  
Consumer Behaviour ◽  
Telephone Survey ◽  
Meat Consumption ◽  
Marketing Mix ◽  
Analysis Techniques ◽  
Turkey Meat ◽  
Segmentation Strategy ◽  
Shopping Location

Aim of study: Commercially, chicken meat has a similar positioning to turkey meat, as both are healthy and low-fat meats. For this reason, we proposed analysing consumer behaviour with respect to each of these meats based on market segmentation.Area of study: Spain.Material and methods: We carried out a telephone survey with an error of ± 4.0% at a confidence level of 95.5%, using the food-related lifestyle (FRL) instrument as part of the questionnaire. The statistical analysis techniques employed were different depending on the objective pursued: univariate, bivariate and multivariate analysis.Main results: Five segments were obtained: “Manager cook” (24.5%), “Healthy cook” (20.8%), “Concerned with food, but not cooks” (22%), “Total detachment” (11.9%) and “Rational shopper with little interest in cuisine” (20.8%). Notwithstanding the similar positioning of chicken and turkey meats, there are significant differences in purchasing and consumption habits between FRL segments. Specifically, there were significant differences in the frequency of purchase, the usual shopping location, purchasing criteria and preparation methods.Research highlights: Knowing the profile of these segments allows us to adapt the marketing mix (product, place, price and promotion) to each one. This is very useful for the companies due to the wide demand they face. First, they can choose the FRL segments to target and, second, they can define an appropriate marketing strategy according to these segments. In this way, market segmentation strategy based on food-related lifestyles may ensure companies a greater likelihood of success in the market.

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