China 
Africa 
Explore chapters and articles related to this topic
Intelligent Set-Up Planning Systems for Parts Production in Manufacturing Systems
Published in Cornelius Leondes, Computer-Integrated Manufacturing, 2019
Dimensions and tolerances [ANSI, 1982] of a part are specified by a designer with regard to the functions of the part. The process planners and fixture designers have to follow the dimensional and geometrical tolerances of a part closely during the planning process. Machining difficulty depends on the specified tolerances, and closely toleranced features have to be machined in one set-up. The systems reported by Boerma and Kals [1988, 1989]; Boerma [1990], and Delbressine, deGroot, and van der Wolf [1993] considered the tolerance specifications of a part as the main criterion in set-up planning. Boerma and Kals proposed a tolerance conversion scheme [1990] to convert each tolerance specification to a tolerance factor. In each case, features with the most critical tolerances will be machined last. Delbressine represented these tolerance factors using a tolerance graph.
Regional phase angle, not whole-body, is augmented in response to pre-season in professional soccer players
Published in Research in Sports Medicine, 2022
Renêe de Caldas Honorato, Alex Soares Marreiros Ferraz, Witalo Kassiano, Priscila Custódio Martins, Diego Augusto Santos Silva, Vânia Marilande Ceccatto
BIVA analysis. From the values of BIVA, BIVA confidence and BIVA tolerance were created. The BIVA confidence comprises the 95% confidence ellipses for the vector means that are found by averaging the components of the relationship between R and Xc by height (metres) measured in a group of individuals. The sample mean is presented as an estimate of the results that would be obtained if the total population was studied. Confidence intervals are used to check whether a mean is significantly different from a hypothetical value or a comparison population (Piccoli & Pastori, 2002). BIVA tolerance is the graphical analysis of the individual or of the three ellipses: the median, the third quartile, and the 95th percentile, which are regions that include 50%, 75%, and 95% of the individual points, respectively. In this way, the tolerance graph allows a more detailed classification of the vector position of the individual impedance (a point) in the R/Xc graph, through its distance concerning the mean vector of the reference population (Piccoli & Pastori, 2002) and with a population of university soccer athletes (Martins et al., 2021). In vector BIVA, standardization of Z by the conductor length allows a consistent evaluation of Z-body and Z-leg with the same electric unit in ohms per metre.
On m-Polar Interval-valued Fuzzy Graph and its Application
Published in Fuzzy Information and Engineering, 2020
Sanchari Bera, Madhumangal Pal
IVFG was defined by Hongmei and Lianhua [10] in 2009 and some operations on this were studied by Akram and Dudek [11] in 2011. Complete fuzzy graph was defined by Hawary [12]. He also studied three new operations on it. Nagoorgani and Malarvizhu [13, 14] studied isomorphic properties on fuzzy graphs and also defined the self-complementary fuzzy graphs. The extension of bipolar fuzzy set and the idea of -polar fuzzy sets (-PFS) were introduced by Chen et al. [15] in 2014. Samanta and Pal [16–19] investigated on fuzzy tolerance graph, fuzzy threshold graph, fuzzy -competition graphs, -competition fuzzy graphs and also fuzzy planar graphs. Some properties of isomorphism and complement on IVFG were studied by Talebi and Rashmanlou [20]. Later, Ghorai and Pal [21, 22] described various properties on -PFGs. They examined isomorphic properties on -PFG. Different types of research on generalized fuzzy graphs were discussed on [23–31]. The main contribution of this study is as follows: Concept of -PIVFGs and complement of -PIVFGs are introduced with examples.The definitions of classic and non-classic -PIVFG related to complement of that are also discussed.Definition of isomorphic, weak isomorphic and co-weak isomorphic -PIVFG are explained.Results based on isomorphic properties of -PFGs are discussed.A case study based on -PIVFG is explained.
Hesitant Fuzzy Graphs and Their Products
Published in Fuzzy Information and Engineering, 2020
Muhammad Javaid, Agha Kashif, Tabasam Rashid
Concept of graph theory have applications in many areas of computer science, including data mining, image segmentation, clustering, image capturing, networking, etc. Classical graph theory is based on classical propositional logic. In many cases, human judgment and preference are ambiguous, vague and cannot be estimated with exact numeric value under many conditions, so the classical logic is not suitable to model real world situations. To solve the ambiguity and vagueness in information from human judgement and preference, classical logic is extended to fuzzy logic by Zadeh in 1965 [1]. It is obvious that much knowledge in real world situations is fuzzy rather than precise. Fuzzy logic was the base of several extensions of fuzzy set theory and it is successfully used in many discipline of theoretical and practical background [2–4]. For the basics of fuzzy logic several texts are available but here we recommend [5]. In 1975, Rosenfeld [6] discussed the concept of fuzzy graph whose basic idea was introduced by Kauffman [7] in 1973. The fuzzy relations between fuzzy sets were also considered by Rosenfeld and he developed the structure of fuzzy graphs, obtained analogs of several graphs theoretical concepts. The popularity and applicability of fuzzy logic attracted several researchers, resulting its various extensions and generalisations. Hesitant fuzzy set (HFS) is one such important extension and generalisation of fuzzy set theory [8]. It received lot of attention in clustering, optimisation, convexity, decision making, preference relations, data mining and aggregation operators. The fuzzy sets give the degree of membership, while HFSs give all the possible degrees of membership, which are independent from each other. A different perspective than the current one, of HFS in graph theory and decision making is presented in [9–13]. In this paper, the notion of hesitant fuzzy graphs (HFG) is discussed in general and broader prospective. We define some operations on HFG namely Cartesian product, tensor product, normal product and composition. Furthermore, studied about the degree of the vertex in HFG, which is obtained from two HFGs and using the operations Cartesian product, composition, tensor product and normal product. Real life application of these products are the great motivation of our work. After Rosenfeld [6] the fuzzy graph theory increases with its various types of branches, such as arcs in fuzzy graph [14], fuzzy tolerance graph [15], fuzzy threshold graphs [16], bipolar fuzzy graphs [17], highly irregular interval valued fuzzy graphs [18, 19], balanced interval valued fuzzy graphs [20], fuzzy competition graphs and competition fuzzy graphs [21], step fuzzy compitition graphs [22], etc. A new concept of fuzzy colouring of fuzzy graph is given [23]. Ghorai and Pal introduced operations on polar fuzzy graphs [24], polar fuzzy planar graphs [25]. Nayeem and Pal introduced shortest path problem on a network with imprecise edge weight [26].