In this paper, we account for this subject: how to de sign a pattern, it can track the state of the equipment of some organizations su ch as enterprise, organ, laboratory, school etc. We present an analysis pattern, w...In this paper, we account for this subject: how to de sign a pattern, it can track the state of the equipment of some organizations su ch as enterprise, organ, laboratory, school etc. We present an analysis pattern, which describes the whole procedure of managing the equipment and record the us ing of the equipment. It not only can track the quantity and location of the equ ipment of the whole organization, the more important is it can update the state of the equipment at real-time automatically. First,we design the static diagram(i.e. using UML class diagram to describe the basic state of the equipment). Then we consider its dynamic aspect, i.e., how th e state of the equipment to get changed according to the time. We use UML sequen ce diagram and state diagram to respectively describe the procedure of after pur chasing, transferring and discarding as useless of the equipment. Obviously, the manager can update the quantity and location of the equipment automatic ally. We character this pattern from the following five aspects: Problem: How the enterprise, organ, laboratory and school to track the quantity and location of the equipment. Circumstance: In some organizations, especially, in the manufactory or laborator y, when the number of the quantity and type is large or the distribution of the equipment is dispersed, they want to be able to track the quantity and location of the equipment. Forces: First, it is possible to the equipment be transferred or be discarded, n o matter when and where, the organization must be able to track the factual quan tity and location.Second, the solution must describe a basic semantic unit, that is, the solution must simple enough to apply it to various of circumstance, whi ch is the base of reusing. Third, the solution must include the interpret of the factual document. Solution: This part, we start with the basic demands, first using UML class diag ram to describe the basic pattern, which is an atomic pattern. Then using UML se quence diagram and state diagram to respectively describe the procedure of after purchasing, transferring and discarding as useless of the equipment and the rel evant change of the equipment in quantity and location. Consequence: Describing the effect of the pattern and how it supports the object . The pattern falls in the class which we call it semantic analysis patterns (SA P), it is a general model, which is abstract from the practical application. The case in fact is the minimum application which we can apply it to a certain fiel d, furthermore, we can implement the more particular demands or the similar appl ication by extending.展开更多
Blasting is one of the most important operations in the mining projects that has effective role in the whole operation physically and economically. Unsuitable blasting pattern may lead to unwanted events such as poor ...Blasting is one of the most important operations in the mining projects that has effective role in the whole operation physically and economically. Unsuitable blasting pattern may lead to unwanted events such as poor fragmentation, back break and fly rock. Multi attribute decision making(MADM) can be useful method for selecting the most appropriate blasting pattern among previously performed patterns. In this work, initially, from various already performed patterns, efficient and inefficient patterns are determined using data envelopment analysis(DEA). In the second step, after weighting impressive attributes using experts' opinion, elimination Et choice translating reality(ELECTRE) was used for ranking the efficient patterns and recognizing the most appropriate pattern in the Sungun Copper Mine, Iran. According to the obtained results, blasting pattern with the hole diameter of 15.24 cm, burden of 3 m, spacing of 4 m and stemming of 3.2 m has selected as the best pattern and has selected for future operation.展开更多
This paper focuses on the recognition rate comparison for competing recognition algorithms, which is a common problem of many pattern recognition research areas. The paper firstly reviews some traditional recognition ...This paper focuses on the recognition rate comparison for competing recognition algorithms, which is a common problem of many pattern recognition research areas. The paper firstly reviews some traditional recognition rate comparison procedures and discusses their limitations. A new method, the posterior probability calculation（PPC） procedure is then proposed based on Bayesian technique. The paper analyzes the basic principle, process steps and computational complexity of the PPC procedure. In the Bayesian view, the posterior probability represents the credible degree（equal to confidence level） of the comparison results. The posterior probability of correctly selecting or sorting the competing recognition algorithms is derived, and the minimum sample size requirement is also pre-estimated and given out by the form of tables. To further illustrate how to use our method, the PPC procedure is used to prove the rationality of the experiential choice in one application and then to calculate the confidence level with the fixed-size datasets in another application. These applications reveal the superiority of the PPC procedure, and the discussions about the stopping rule further explain the underlying statistical causes. Finally we conclude that the PPC procedure achieves all the expected functions and be superior to the traditional methods.展开更多
文摘In this paper, we account for this subject: how to de sign a pattern, it can track the state of the equipment of some organizations su ch as enterprise, organ, laboratory, school etc. We present an analysis pattern, which describes the whole procedure of managing the equipment and record the us ing of the equipment. It not only can track the quantity and location of the equ ipment of the whole organization, the more important is it can update the state of the equipment at real-time automatically. First,we design the static diagram(i.e. using UML class diagram to describe the basic state of the equipment). Then we consider its dynamic aspect, i.e., how th e state of the equipment to get changed according to the time. We use UML sequen ce diagram and state diagram to respectively describe the procedure of after pur chasing, transferring and discarding as useless of the equipment. Obviously, the manager can update the quantity and location of the equipment automatic ally. We character this pattern from the following five aspects: Problem: How the enterprise, organ, laboratory and school to track the quantity and location of the equipment. Circumstance: In some organizations, especially, in the manufactory or laborator y, when the number of the quantity and type is large or the distribution of the equipment is dispersed, they want to be able to track the quantity and location of the equipment. Forces: First, it is possible to the equipment be transferred or be discarded, n o matter when and where, the organization must be able to track the factual quan tity and location.Second, the solution must describe a basic semantic unit, that is, the solution must simple enough to apply it to various of circumstance, whi ch is the base of reusing. Third, the solution must include the interpret of the factual document. Solution: This part, we start with the basic demands, first using UML class diag ram to describe the basic pattern, which is an atomic pattern. Then using UML se quence diagram and state diagram to respectively describe the procedure of after purchasing, transferring and discarding as useless of the equipment and the rel evant change of the equipment in quantity and location. Consequence: Describing the effect of the pattern and how it supports the object . The pattern falls in the class which we call it semantic analysis patterns (SA P), it is a general model, which is abstract from the practical application. The case in fact is the minimum application which we can apply it to a certain fiel d, furthermore, we can implement the more particular demands or the similar appl ication by extending.
文摘Blasting is one of the most important operations in the mining projects that has effective role in the whole operation physically and economically. Unsuitable blasting pattern may lead to unwanted events such as poor fragmentation, back break and fly rock. Multi attribute decision making(MADM) can be useful method for selecting the most appropriate blasting pattern among previously performed patterns. In this work, initially, from various already performed patterns, efficient and inefficient patterns are determined using data envelopment analysis(DEA). In the second step, after weighting impressive attributes using experts' opinion, elimination Et choice translating reality(ELECTRE) was used for ranking the efficient patterns and recognizing the most appropriate pattern in the Sungun Copper Mine, Iran. According to the obtained results, blasting pattern with the hole diameter of 15.24 cm, burden of 3 m, spacing of 4 m and stemming of 3.2 m has selected as the best pattern and has selected for future operation.
基金supported by the National Natural Science Foundation of China(61101179)
文摘This paper focuses on the recognition rate comparison for competing recognition algorithms, which is a common problem of many pattern recognition research areas. The paper firstly reviews some traditional recognition rate comparison procedures and discusses their limitations. A new method, the posterior probability calculation（PPC） procedure is then proposed based on Bayesian technique. The paper analyzes the basic principle, process steps and computational complexity of the PPC procedure. In the Bayesian view, the posterior probability represents the credible degree（equal to confidence level） of the comparison results. The posterior probability of correctly selecting or sorting the competing recognition algorithms is derived, and the minimum sample size requirement is also pre-estimated and given out by the form of tables. To further illustrate how to use our method, the PPC procedure is used to prove the rationality of the experiential choice in one application and then to calculate the confidence level with the fixed-size datasets in another application. These applications reveal the superiority of the PPC procedure, and the discussions about the stopping rule further explain the underlying statistical causes. Finally we conclude that the PPC procedure achieves all the expected functions and be superior to the traditional methods.
