Effect of Tool Rotational and Al<Subscript>2</Subscript>O<Subscript>3</Subscript> Powder in Electro Discharge Machining Characteristics of NiTi-60 Shape Memory Alloy

Nickel titanium is an intelligent alloy which are used in optical devices, thermal sensors, actuators, medical equipment and aerospace, because memory shape property, high strength, good creep and fatigue resistance. This alloy has features like the response to electrical stimulation, thermal, magnetic and mechanical stimulation. According to hardness and mechanical properties of this alloy, one of the ways it is used for machining, is EDM. EDM is one of the machining of precision and complex parts methods which material removal rate, tool wear rate, surface roughness and thickness of the recast layer one is very important in it. In this study the effect of current, voltage, pulse on time, pulse off time, tool rotational, Al₂O₃ powder, material removal rates, tool wear rate and surface roughness are examined. The results show that using Al₂O₃ powder and tool rotational along with increasing current intensity, pulse on time and voltage, increases the material removal rate. Rotation of the tool create a centrifugal force and Al₂O₃ powder increases the gap and the material removal rate. Rotation of the tool prevents spreading of the plasma channel and Al₂O₃ powder fills gap between tool and workpiece, decrease kinetic energy of ions and reduced tool wear rate. By adding powder Al₂O₃, rotation of the tool, reducing current intensity, voltage and time pulse, sparks get smaller and will have less penetration and surface roughness reduces.     

Thermal Characterization of Polycrystalline SiC

A study is made using fabricated thermal resistors in combination with two-dimensional (2D) electrothermal simulations to determine the thermal conductivity of polycrystalline SiC, single-crystalline SiC, and Si. The results show that the poly-SiC substrate has thermal conductivity of κ _poly-SiC = 2.7 W K^?1 cm^?1, which is significantly lower than that of single-crystalline SiC.     

Preconstruction solution for Groundwater rise in Sabkha

Sabkha deposits are formed under arid conditions and are considered as a common problematic soil along the coastal area of the Arabian Gulf. Saudi Arabia. One of the most serious problems associated with the coustruction on sabkha is the rise of groundwater level causing settlement and hence imposing additional stress on the structural elements. Groundwater rise in sabkha was attributed to numerous reasons; the interruption of the natural evaporation by construction is considered to the most prominent. The evaporation data along the Arabian Gulf coast had been analyzed and the possible rise in the groundwater level had been predicted using both the evaporation and soil porosity data. A horizontal drain is suggested to interrupt the capillarity in the soil and to drain the infiltrating water and hence stop the groundwater rise. A mathematical model for the optimum selection of the drain characteristics is presented. This model requires the knowledge of some site conditions such as the area to be drained, the thickness of the aquifer and the soil coefficient of permeability. Based on these values a design curve can be constructed to relate the horizontal drain characteristics such as the longitudinal transmissivity of the drain, its thickness and its slope. An example using the parameters of a specific site conditions along the Arabian Gulf coast is given to present the suggested design curve. The relative significance of these parameters on the drain characteristics and geometry is also discussed.     

Orthogonal Fuzzy Rule-Based Systems: Selection of Optimum Rules

In this paper, the concept of orthogonal fuzzy rule-based systems is introduced. Orthogonal rules are an extension to the definition of orthogonal vectors when the vectors are vectors of membership functions in the antecedent part of rules. The number and combination of rules in a fuzzy rule-based system will be optimised by applying orthogonal rules. The number of rules, and subsequently the complexity of the fuzzy rule-based systems, are directly associated with the number of input variables and distinguishable membership functions for each individual input variable. A subset of rules can be used if it is known which subset provides closer behaviour to the case when all rules are used. Orthogonal fuzzy rule-based systems are proposed as a judgment as to whether the optimal rules are selected. The application of orthogonal fuzzy rules becomes essential when fuzzy rule-based systems containing many inputs are used. An illustrative example is presented to create a model for the solder paste printing stage of surface mount tech-nology.     

Recognizing strong and weak congestion slack based in data envelopment analysis

The common concept of congestion is that a decrease (increase) in one or more inputs of a decision making unit (DMU) causes an increase (decrease) in one or more outputs (Cooper, Gu, & Li, 2001a). So far several congestion approaches have been proposed in DEA (data envelopment analysis) literature by many authors, such as Färe’s et al. (FGL), Brockett’s et al. (BCSW), and Tone and Sahoo’s congestion approaches (Färe et al., 1985, Färe et al., 1994, Brockett et al., 1998, Tone and Sahoo, 2004). Tone and Sahoo’s approach (Tone & Sahoo, 2004) is one of the most robust congestion approaches in DEA literature. Moreover, Tone and Sahoo’s approach has some advantages with respect to FGL and BSCW congestion approaches. However, the proposed approaches have many difficulties to treat congestion. For instance, in the presence of alternative optimal solutions, the approach proposed by Tone and Sahoo is unable to detect congestion (strong and weak). Moreover, in Tone and Sahoo’s approach, all inputs and outputs of decision making units (DMUs) have been considered positive, while in real world, data is often non-negative.In this research, a slack-based DEA approach is proposed to recognize congestion (strong and weak) for the target DMUs. One of the advantages of our proposed approach is capable of detecting congestion (strong and weak) for evaluating the DMUs in the presence of alternative optimal solutions. Other advantage of our research is capable of identifying congesting (strong and weak) DMUs with non-negative inputs and outputs. However in these situations, Tone and Sahoo’s congestion approach is incapable of identifying congestion. Lastly, we apply the approach to the data sets for making comparisons between the proposed approach and Tone and Sahoo’s approach then some conclusions are drawn and directions for future research are suggested.     

NODAR: mining globally distributed substructures from a single labeled graph

Data mining in structured and semi-structured data focuses on frequent data values. However, in graph data mining, the focus is on common specific topologies. Graph mining, although its ubiquity, is a difficult task since it requires subgraph isomorphism which is known to be NP-complete. In order to effectively prune the search space and thereby save computational time, a graph mining algorithm requires that the support measure of a pattern to be no greater than that of its subpatterns. This property of the support measure is referred to in the literature as the down-closure, anti-monotonicity or admissibility. Unfortunately, when mining a single labeled graph, simply counting the occurrences of a graph pattern may not have the down-closure property. For this, most existing approaches mine frequent substructures in a set of labeled graphs (called also the transactional setting) and few efforts have been devoted to mining frequent globally distributed substructures in a single labeled graph. In this paper, we propose a graph mining algorithm, called NODAR(Non-Overlapping embeDding based grAph mineR), for computing common and globally distributed substructures in a single labeled graph. NODAR adopts the Depth-First Search (DFS) strategy and is based on the SMNOES (Size of Maximum Non Overlapping Embedding Set) as support measure. The core idea of NODAR is to automatically extract frequent subpatterns; and thus without frequency computation thanks to the down-closure property of SMNOES. By adopting this strategy in the computation of frequent substructures, NODAR reduces the number of subgraph isomorphism tests needed to compute pattern frequencies. Experimental results on monograph and transactional graph databases; and comparison with well-known probabilistic and exact algorithms; prove the efficacy of NODAR.     

A Note on Z-numbers

Decisions are based on information. To be useful, information must be reliable. Basically, the concept of a Z-number relates to the issue of reliability of information. A Z-number, Z, has two components, Z = (A, B). The first component, A, is a restriction (constraint) on the values which a real-valued uncertain variable, X, is allowed to take. The second component, B, is a measure of reliability (certainty) of the first component. Typically, A and B are described in a natural language. Example: (about 45 min, very sure). An important issue relates to computation with Z-numbers. Examples: What is the sum of (about 45 min, very sure) and (about 30 min, sure)? What is the square root of (approximately 100, likely)? Computation with Z-numbers falls within the province of Computing with Words (CW or CWW). In this note, the concept of a Z-number is introduced and methods of computation with Z-numbers are outlined. The concept of a Z-number has a potential for many applications, especially in the realms of economics, decision analysis, risk assessment, prediction, anticipation and rule-based characterization of imprecise functions and relations.     

Generalized Euler-Lagrange equations for fractional variational problems with free boundary conditions

In this article we are going to present necessary conditions which must be satisfied to make the fractional variational problems (FVPs) with completely free boundary conditions have an extremum. The fractional derivatives are defined in the Caputo sense. First we present the necessary conditions for the problem with only one dependent variable, and then we generalize them to problems with multiple dependent variables. We also find the transversality conditions for when each end point lies on a given arbitrary curve in the case of a single variable or a surface in the case of multiple variables. It is also shown that in special cases such as those with specified and unspecified boundary conditions and problems with integer order derivatives, the new results reduce to the known necessary conditions. Some examples are presented to demonstrate the applicability of the new formulations.     

Some new efficient multipoint iterative methods for solving nonlinear systems of equations

It is attempted to put forward a new multipoint iterative method of sixth-order convergence for approximating solutions of nonlinear systems of equations. It requires the evaluation of two vector-function and two Jacobian matrices per iteration. Furthermore, we use it as a predictor to derive a general multipoint method. Convergence error analysis, estimating computational complexity, numerical implementation and comparisons are given to verify applicability and validity for the proposed methods.