Money and banking Essay Example | Topics and Well Written Essays - 500 words - 2

Money and banking - Essay Example Jefferson argues that since no mention of any mandate was present, Congress had no such right. Hamilton dismissed Jefferson’s arguments by citing that Congress has â€Å"necessary and proper powers† to implement the nation’s fiscal and monetary policy. He added that a central bank fits perfectly into this scheme, by making it easier for Congress to do the job. If there were one central bank coordinating all banks, Congress could easily hold one accountable. Eventually, Hamilton’s arguments won, and this would set the practice of establishing central banks for the years to come, beginning with the First Bank of the United States of America. (Johnson 7) This should be viewed actually as the triumph of the power of money over democracy. Money could be represented by paper marked by the government as legal tender. In itself, it is harmless to democracy. But left to the hands of unscrupulous individuals and bankers, money can be used to damage democracy as can be seen in the succeeding events. During the term of James Madison, the bill seeking to renew the First Bank’s Charter was defeated by a narrow margin. Madison liked the outcome, but chaos ensued. The War of 1812 made the US Government to focus its effort in surviving against England. As a result, state-chartered banks began issuing different fiat currencies with little value. Proponents of central banking then blamed Madison for such troubles. Near the end of his term, Madison was forced to sign the charter of the Second Bank of America, as this was the popular clamor of Representatives. (Johnson 9) Thus, although there were hopes that democracy will prevail over the system of credit, central banking won. This episode illustrates clearly the fact that because of money, efforts to implement what is good for the general public can be undermined. Fast forward to 1907,

Law of contract Case Study Example | Topics and Well Written Essays - 2000 words

Law of contract - Case Study Example In this scenario,there are two questions which arise.First,is the price of 100 listed in the newspaper advertisement binding on Wedding Heaven in the event that they sell the dress.Secondly,does the delay of John cause him in law to have accepted the contract offer of the lower amount of 150In order to give effective analysis to this question it is important to look at relevant Irish case law on this issue in order to determine whether or not such actions constitute a binding contract enforceable in law. There are a number of leading cases in both the Irish jurisdiction and other common law jurisdictions, notably England, which need to be assessed in order to consider this question.This essay shall first analyse the formative components which are necessary for the formation of a contract. Secondly, after assessing the relevant law, these principles will be applied to the current scenario above. Finally, and in conclusion, this paper shall decide whether or not a claim exists in contr act law in the scenario again either Wedding Heaven, or John the DJ. We now turn to the basic contract law principles which currently exist in Ireland.First, we must look at the relevant contract law principles on order to ascertain the current state of the law in Ireland. There are a number of requirements necessary for the formation of a valid contract. This includes offer and acceptance, an intention to create legal relations; and finally consideration. It is the first two elements which this paper shall concentrate on. Offer It is important at the outset to distinguish between and offer and a mere invitation to treat. An offer is when the seller sets out in certain terms what they propose to sell to the potential buyer. In essence, it is the final set of terms which, if accepted by the buyer, would create a valid contract. However, an invitation to treat is not a formal offer, but rather an indication of intent to enter negotiations. It is not possible to accept a mere invitation to treat in order to create a binding contract. Therefore it is important to ascertain the exact intent of any representation as to whether it is a formal offer or simply a declaration of intent. Such declarations may be considered as offers under statute1 or common law2. In general, advertisements are considered to be an invitation to treat. In the English case of C.A. Norgren Co. v Tech-nomarketing,3 Walton J refused a committal order against one of the defendants for allegedly breaching an undertaking given to the High Court that the defendants would not "make, offer for sale, sell or distribute" items that were subject to copyright.4 The defendants distributed a price list and brochure, including an item covered by the undertaking. Walton J. upheld the contention of the defendant that, generally, the distribution of advertising material constituted an invitation to treat and was therefore not an offer. In order to gauge the intention of the seller, this can either be express by way of direct words, or implied by his actions. It has previously been held in case law that a personal quotation of the price of goods was merely an invitation to treat.5 Further, it has also been held that a display of goods for sale with the price labels attached is in all probability only an invitation to treat, whether the products are in a shop window, on a store shelf or indeed in a self-service store6. One of the leading cases is that of Fisher v Bell7 where a shopkeeper displayed in a knife with a price ticket in his shop window. He was charged with offering a flick knife for sale in contravention of the Restriction of Offensive Weapons Act 1959 s1. It was however held that the shopkeeper was not guilty because displaying the knife in the shop window amounted merely to an invitation to treat. Accordingly, the shopkeeper had not offered the knife for sale within the 1959 Act. Further, In the leading English case of Pharmaceutical Society of Great Britain

The Classic Transportation Problem Computer Science Essay

The Classic Transportation Problem Computer Science Essay Classic Transportation Problem is a significant research issue in spatial data analysis and Network analysis in GIS; it helps to answer problems which relate in matching the supply and demand via set of objectives and constraints. The objective is to determine a set of origins and destinations for the supply so as to minimize the total cost. Geographic Information System (GIS) is an intelligent tool which combines characteristic data and spatial features and deal with the relationship connecting them. Although GIS application is extensively utilized in numerous activities, but in transportation its application is still rare. Basically, GIS is an information system which focusing on few factors which included the input, management, analysis and reporting of geographic (spatially related) information. Between all the prospective applications that GIS can be use for, issues on transportation have gained a lot of interest. An exact division of GIS related to issues on transportation has surfaced, which labelled as GIS-T. The Hitchcock transportation dilemma is conceivably one of the most solved linear programming problems in existence (Saul I. Gass, 1990). The addition of GIS into transportation (GIS-T) suggests that it is possible to integrate transportation data into GIS. Many research scholars have discussed computational considerations for solving the Classic Transportation problem (CTP): Shafaat and Goyal developed a procedure for ensuring an improved solution for a problem with a single degenerate basic feasible solution; Ramakrishnan described a variation of Vogels approximation method (VAM) for finding a first feasible solution to the CTP; and Arsham and Kahn described a new algorithm for solving the CTP. According to Brandley, Brown and Craves, 2004, practically the CTP is integrated in all texts on management science or operations management. In classic problem relating to transportation, particular objective for instance minimum cost or maximum profit will be the focus to integrate the GIS and the transportation data available. For example, (Jaryaraman and Prikul, 2001), (Jaryaraman and Ross, 2003), (Yan et al., 2003), (Syam, 2002), (Syarif et al., 2002), (Amiri, 2004), (Gen and Syarif, 2005), and (Trouong and Azadivar, 2005) had consider total cost of supply chain as an objective function in their studies. Nevertheless, there are no design tasks that are single objective problems. In this chapter, we present an in-depth computational comparison of the basic solution algorithms for solving the CTP. We will describe what we know with respect to solving CTPs in practice and offer comments on various aspects of CTP methodologies and on the reporting of computational results. In order to describe the core elements of the GIS transport model that is used to gain the solution to the CTP, it is essential to go over the different types of transportation models briefly, and elaborate on the application and issues of GIS in transportation. The chapter concludes with some final remarks. The Classic Transportation Problem (CTP) The Classic Transportation Problem (CTP) refers to a special class of linear programming. It has been recognized as a fundamental network problem. The Classic transportation problem of linear programming has an early history that can be traced to the work of Kantorovich, Hitchcock, Koopmans and Dantzig. By applying directly the simplex method to the standard linear-programming problem, it actually helps to solve it. Still, because of its very unique mathematical structure, it was acknowledged early that the simplex method applied to the CTP can be quite efficient on how to estimate the needed simplex-method information variable to enter the basis, variable to leave the basis and optimality conditions. Many practical transportation and distribution problems such as the fixed cost transportation, the minimum with fixed charge in logistics can be formulated as CTP. Mathematical formulation of the CTP There have been numerous studies conducted that focusing on new models or methods to verify the transportation or the logistics activities that can offer the least cost (Gen and Chen, 1997). Generally, logistics was defined as the quality of a flow of materials, such as the frequency of departure (number per unit time, adherence to the transportation time schedule and so on (Tilaus et al, 1997). Products can be assemble and sent to the allocation centres, vendors or plants. Hitchcock, 1941 has initiated the earliest formulation of a planar transportation model, which used to find an approach to transport homogeneous products from several resources to several locations so that the total cost can be minimized. According to Jung-Bok Jo, Byung -Ki Kim and Ryul Kim, 2008, the development of a variety of deterministic and / or stochastic models have been increased throughout the past several decades. The basic problem sometimes called the general or Hitchcock transportation problem can be known in a mathematic way as follows: Where m is the number of supply centres and n is the number of demand points. This is subjected to: Without loss of generality, it is assumed that, the problem is balanced, i.e. Total Demand = Total Supply Where; ai, bj, cij, xij à ¢Ã¢â‚¬ °Ã‚ ¥ 0 (non negativity constants) à ¢Ã¢â€š ¬Ã‚ ¦2.4 All the parameters are free to take non negative real values. The ais are called supplies and the bis are called demands. For our discussion here, we also assume that the costs cij à ¢Ã¢â‚¬ °Ã‚ ¥ 0. A number of heuristic methods to solve the classic transportation problem have been proposed. (Gottieb et el., 1998; Sun et al., 1998; Adlakha and Kowalski, 2003; Ida et al., 2004). According to Chan and Chung, 2004, in order to distribute problem in a demand driven SCN, they have suggested a multi- objective genetic optimization. They also measured minimization of total cost of the system, total delivery days and the equity of the capacity utilization ratio for manufacturers as objectives. Meanwhile, Erol and Ferrel, 2004, have recommended a model that assigned suppliers to warehouses and warehouses to customers. In addition, the SCN design problem was formulated as a multi- objective stochastic mixed inter linear programming model, which then was resolved by a control method, and branch and bound techniques (Guillen et al., 2005). Chan et al., 2004, stated that objectives were SC profit over the time horizon and customer satisfaction level and they also developed a hybrid approach regarding to genetic algorithm and Analytical Hierarch Process (AHP) for production and distribution problems in multi-factory supply chain models. Jung-Bok Jo, Byung -Ki Kim and Ryul Kim, 2008, has measured few objectives in their research namely; operation cost, service level, and resources utilization. In this project, it has been considered about the integration of the CTP into the GIS environment, which little or no research has been done into this line of study. Our formulation will be particularly concentrated on the use of several GIS software and procedures to see how the CTP problem can be solved in the GIS environment. In that note and as already stated in chapter one, in trying to integrate CTP into the GIS environment, two of the algorithm explained in this literature review will be used to solved the CTP problem to get the initial basic feasible solutions and one optimal solution method will be used to get the optimal solution that will be integrated into the GIS software environment to solve the CTP problem. 2.4 Methods of solving Transportation problems The practical importance of determining the efficiency of alternative ways for solving transportation problems is affirmed not only because of the sizeable fraction of the linear programming literature has been dedicated to these problems, but also by the fact that an even larger allocation of the concrete industrial and military appliances of linear programming deal with transportation problem. Transportation problems often occur as sub-problems in a bigger problem. Moreover, industrial applications of transportation problems often contain thousands of variables, and hence a streamlined algorithm is not computationally worthwhile but a practical necessity. In addition, many of linear programs that occurred can nevertheless be given a transportation problem formulation and it is also possible to approximate certain additional linear programming problems by such a formulation. Efficient algorithms existed for the solution of transportation. A computational study done by Glover et al. suggested that the fastest method for solving Classic transportation problems is a specialization of the primal simplex method due to Glover et al. Using data structured due to M.A. Forbes, J.N. Holt, A.M Watts, 1994. An implementation of this approached, is capable of handling the general transshipment problem. The method is particularly suitable for large, spares problems where the number of arcs is a small multiple of the number of nodes. Even for dense problems the method is considered to be competitive with other algorithms (M.A. Forbes, J.N. Holt, A.M Watts, 1994). Another consideration of the CTP model is the formulation made by Dantzigs, which is adaptation of the simplex method to the CTP as the primal simplex transportation method (PSTM). This method is known as the method-modified distribution method (MODI); it has also been acknowledged as the row-column sum method (A.Charnes and W. W. Cooper, 1954). Subsequently, another method calledthe stepping-stone method (SSM) has been developed by Charnes and Cooper which gives an option of determining the simplex-method information. According to the paper written by Charnes and Cooper which is entitled The stepping stone method of explaining linear programming calculations in transportation problems. The SSM is a very nice way of demonstrating why the simplex method works without remedy to its terminology or methods although Charnes and Cooper describe how the SSM and PSTM are related. Charnes and Cooper note that the SSM is relatively easy to explain, but Dantzigs PSTM has certain advantages for large-scale hand calculations (Saul I. Gass, 1990) However, the SSM, contrary to the impression one gets from some texts and from the paper by Arsham and Kahn, is not the method of choice for those who are serious about solving the CTP-such as an analyst who is concerned with solving quite large problems and may have to solve such problems repetitively, e.g. where m = 100 origins and n = 200 destinations, leading to a mathematical problem of 299 independent constraints and 20,000 variables (Saul I. Gass, 1990). In addition to the PSTM and the SSM, a number of methods have been proposed to solve the CTP. They include (amongst others) the following: the dual method of Ford and Fulkerson, the primal partitioning method of Grigoriadis and Walker, the dualplex partitioning method of Gass, the Hungarian method adaptation by Munkres, the shortest path approach of Hoffman and Markowitz and its extension by Lageman, the decomposition approach of Williams, the primal Hungarian method of Balinski and Gomory, and, more recently, the tableau-dual method proposed by Arsham and Kahn. (The early solution attempts of Kantorovich, Hitchcock and Koopmans are excluded as they did not lead to general computational methods.) (Saul I. Gass, 1990). The first papers that dealt with machine-based computational issues for solving the TP are Suzuki, Dennis and Ford and Fulkerson. Implementations of CTP algorithms were quite common on the wide range of 1950s and 1960s computers-a listing is given in Gass. CTP computer-based procedures at that time included Charnes and Coopers SSM, the flow (Hungarian) method of Ford and Fulkerson, Munkres Hungarian method, the modified simplex method of Suzuki, Dantzigs PSTM and Dennis implementation of the PSTM. The developers of these early computer codes investigated procedures for finding first feasible solutions such as VAM, the north-west corner method (NWCM), and variations of minimum-cost allocation procedures (Saul I. Gass, 1990). They also investigated various criteria for selecting a variable to enter the basis. Problems of realistic size could be solved, e.g. m + n The work of Glover et al. represents a landmark in the development of a TP computer-based algorithm and in computational testing. Their code is a PSTM that uses special list structures for maintaining and changing bases and updating prices. Glover et al. tested various first-basis finding procedures and selection rules for determining the variable to enter the new basis. They concluded that the best way to determine a first feasible solution is a modified row-minimum rule, in which the rows are cycled through in order, each time selecting a single cell with the minimum cost to enter the basis. The cycling continues until all row supplies are exhausted. This differs from the standard row-minimum rule, in which the minimum cost cells are selected in each row, starting with the first row, until the current row supply is exhausted. The modified row minimum rule was tested against the NWCM, the VAM, a row-minimum rule and a row-column minimum rule in which a row is scanned first for a min imum cell and then a column is scanned, depending on whether the supply or demand is exhausted (Saul I. Gass, 1990). Although VAM tended to decrease the number of basis changes to find the optimal solution, it takes an inordinate amount of time to find an initial solution, especially when compared to the time to perform a basis change (100 changes for 100 x 100 problem in 0.5 s on a CDC 6400 computer). We feel VAM should be relegated to hand computations, if that. Glover et al. tested a number of rules for determining the variable to enter the basis, including the standard most negative evaluator rule. Their computational results demonstrated that a modified row-first negative evaluator rule was computationally most efficient. This rule scans the rows of the transportation cost tableau until it encounters the first row containing a candidate cell, and then selects the cell in this row which violates dual feasibility by the largest amount. They also compared their method to the main competitive algorithms in vogue at that time, i.e. the minimum-cost network out-of-kilter method adapted to solve the TP, the standard simplex method for solving the general linear-programming problem and a dual simplex method for solving a CTP. The results of the comparison showed that the Glover et al. method was six times faster than the best of the competitive methods (Saul I. Gass, 1990). . A summary of computational times for their method showed that the median solution time for solving 1000 x 1000 TPs on a CDC 6000 computer was 17 s, with a range of 14-22 s. As the TP is a special case of a minimum-cost network problem (transhipment problem), methods for solving the latter-type problem (such as the out-of-kilter method) are readily adaptable for solving CTPs. Bradley et al. developed a primal method for solving large-scale trans- shipment problems that utilizes special data structures for basis representation, basis manipulation and pricing. Their code, GNET, has also been specialized to a code (called TNET) for solving capacitated TPs. Various pricing rules for selecting the incoming variable were tested, and a representative 250 x 4750 problem was solved in 135 s on an IBM/360/67 using TNET, with the number of pivots and total time being a function of the pricing rule. The GNET procedure has also been embedded into the MPSIII computer-based system for solving linear-programming problems developed by Ketron Management Science Inc.24 It is called WHIZNET and is designed to solve capacitated trans-shipment problems, of which the TP is a special case. A typical trans-shipment problem with 5000 nodes and 23,000 arcs was solved in 37.5 s on an IBM 3033/N computer (L. Collatz and W. Wetterling, 1975). Another general network problem-solver, called PNET, is a primal simplex method for solving capacitated and uncapacitated transhipment and TPs. It solved a TP with 2500 origins and 2500 destinations in under 4 min of CPU time on a UNIVAC 1108. It uses augmented thread index lists for the bases and dual variables. (Saul I. G ass, 1990). From the above, we see that the present day state-of-the-art for solving TPs on mainframe computers is quite advanced. With the advent of PCs, we find that a number of researchers and software houses have developed PC-based codes for solving TPs. Many of the codes were developed for the classroom and are capable of solving only small, textbook-size problems. For example, the TP procedure in Erikson and Hall (Saul I. Gass, 1990) is able to solve problems of the order of 20 x 20. A typical commercial TP program is that of Eastern Softwares TSP88 which can solve TPs with up to 510 origins and/or destinations. It is unclear as to what algorithms are used in the PC TP codes, but we hazard a guess that they are a version of either PSTM or SSM (Saul I. Gass, 1990). 2.5 Degeneracy in the Classic transportation problem Degeneracy can occur when the initial feasible solution has a cell with zero allocation or when, as a result of real reallocation, more than one previously allocated cell has a new zero allocation. Whenever we are solving a CTP by the PSTM or the SSM, we must determine a set of non-negative values of the variables that not only satisfies the origin and destination constraints, but also corresponds to a basic feasible solution with m + n -1 variables (Saul I. Gass, 1990). . For computational efficiency, all basic cells are kept in a list, with those cells forming the loop being ordered at the top of the list and with the entering cell being first in the list. The remaining cells in the loop are sequenced such that proceeding through them follows the loop. The use of the allocated cells easily handles degeneracy. The PSTM and the SSM do not use a representation of the basis inverse, as does the general simplex method. Instead, these methods take advantage of the fact that any basis to the TP corresponds to a spanning tree of the bipartite network that describes the flows from the origin nodes to the destination nodes (G.B. Dantzig, 1963). Thus, if one is given a basic feasible solution to a CTP which can be readily generated by, say, the NWCM and that solution is degenerate, then one must determine which of the arcs with zero flow should be selected to complete the tree. Having the tree that corresponds to the current basic feasible solution enables us t o determine if the current solution is optimal and, if it is not, to determine the entering and leaving variables and the values of the variables in the new solution (Saul I. Gass, 1990). The problem of selecting a tree for a degenerate basic feasible solution to a CTP was recognized early by Dantzig (G.B. Dantzig, 1963) who described a simple perturbation procedure that caused all basic feasible solutions to be non-degenerate. From our literature gathered from above, the computer-based CTP solution methods described above, degeneracy does not appear to be of concern. We gather that most computer- based methods for solving CTPs invoke some type of perturbation procedure to complete the tree. We note that the problem of selecting a tree for a degenerate basic feasible solution is really only a minor problem if the first basic feasible solution is degenerate. For this case, a perturbation scheme or a simple selection rule that selects a variable or variables with zero value to complete the tree can be applied. (L. Collatz and W. Wetterling, 1975) and (G. Hadley, 1962). As the selection of appropriate zero-valued variables is usually not unique, a simple decision rule is used to make a choice, e.g. to select those variables that have the smallest costs. Once a tree has been established for the first basic feasible solution, the SSM and PSTM prescriptions for changing bases will always yield a new basic feasible solution and corresponding tree, no matter how many degenerate basic feasible variables there are. Subsequent degenerate basic feasible solutions can be generated if there are ties in the selection of a variable to leave the basis. Dropping one and keeping those that were tied at zero level will always yield a tree. Again, a simple decision rule is used to determine which one is dropped from the basis (Saul I. Gass, 1990). Degeneracy can be of concern in that it could cause a series of new bases to be generated without decreasing the value of the objective function-a phenomenon termed stalling. In their paper, Gavish et al. (B. Gavish, P. Schweitzer and E. Shlifer, 1977) study the zero pivot phenomenon in the CTP and assignment problem (AP) and develop rules for reducing stalling, i.e. reducing the number of zero pivots (Saul I. Gass, 1990). For various size (randomly generated) problems, they show that for the CTP the average percentage of zero pivots to total pivots can be quite high, ranging from 8% for 5 x 5 problems to 89% for 250 x 250 problems which are started with the modified row-minimum rule for selecting the first basic feasible solution. They also show that the percentage of zero pivots is not sensitive to the range of values of the cost coefficients, but is sensitive to the range of values of the ais and bjs, with a higher percentage of zero pivots occurring when the latter range is tight. For the m x m AP, which will always have (m 1) basic variables that are zero, the average percentage of zero pivots ranged from 66% for 5 x 5 problems to 95% for 250 x 250 problems. Their rules for selecting a first basic feasible solution, the variable to enter the basis and the variable to leave the basis cause a significant reduction in total computational time (Saul I. Gass, 1990). In their paper, Shafaat and Goyal (A. Shafatt and A.B. Goyal, 1988) develop a procedure for selecting a basic feasible solution with a single degeneracy such that the next solution will improve the objective function value. There procedure forces the entering variable to have an exchange loop that does not involve the degenerate position with a negative increment (Saul I. Gass, 1990). The efficiency of their procedure in terms of computer time versus the small amount of computer time required to perform a number of basis changes (as noted above) is unclear. For large-scale CTPs, we conjecture that a single degenerate basic feasible solution will not cause much stalling, as the chances are that the entering variable will not be on an exchange loop that contains the degenerate variable. We note that a CTP or a linear-programming problem in general, with single degenerate basic feasible solutions will not cycle (Saul I. Gass, 1990). 2.6 Method of finding Initial Basic Feasible Solutions A basic solution is any collection of (n + m 1) cells that does not include a dependent subset. The basic solution is the assignment of flows to the basic cells that satisfies the supply and demand constraints. The solution is feasible if all the flows are non negative. From the theory of linear programming we know that there is an optimal solution that is a feasible solution. The CTP has n+ m constraints with one redundant constraint. A basic solution for this problem is determined by selection (n + m 1) independent variables. The basic variable assumes values to satisfy the supplies and demands, while the non basic values are zero. Thus the m + n equations are linearly dependent. As we will see, the CTP algorithm exploits this redundancy. There are five methods used to determine the initial basic feasible solutions of the classic transportation problem (CTP): these are listed below. The least cost method The northwest corner method The Vogels approximation method Row minimum method Column minimum method The five methods normally differ in the quality of the starting basic solution they produce and better starting solutions yields a smaller objective value. Some heuristics give better performance than the given common methods. The NWCM gives a solution very far from optimal solution. The least cost method finds a better starting solution by concentrating on the cheapest route. The Vogels Approximation method (VAM) is an improved version of the least cost method that generally produces better starting solutions. The row minimum method starts with first row and chooses the lowest cost cell of first row so that either the capacity of the first supply is exhausted or the demand at jth distribution centre is satisfied or both. The column minimum method starts with first column and chooses the lowest cost cell of first column so that either the demand of the first distribution centre is satisfied or the capacity of the ith supply is exhausted or both. However, among the five methods listed above, the North West Corner Method (NWCM), the Lowest Cost Method (LCM), and the Vogels Approximation method are the most commonly used methods used in finding the initial basic feasible solutions of the CTP. The NWCM gives a solution very far from optimal solution and Vogels Approximation method and LCM tries to give result that are often optimal or near to optimal solution. In a real-time application, Vogels Approximation Method (VAM) will yield a considerable savings over a period of time. On the other hand, if ease of programming and memory space are major considerations, the NWCM is still acceptable for reasonable matrix sizes (up to 50 X 50). However, the difference in times between the two loading techniques increases exponentially. (Totschek and Wood,2004). Another work presents an alternative of Vogels Approximation Method for TP and this method is more efficient than traditional Vogels Approximation Method (Mathirajan, Meenakshi, 2004). In this project however, we are making use of the Northwest Corner method (NWCM) and the Least Cost Method (LCM) to find the initial basic feasible solutions to the CTP. These solutions will then be used further to get optimal solutions to the CTP by using the Stepping Stone Method (SSM). The final answers will then be compared with the solutions procedures obtained from the GIS software environment to solve the CTP in a method other than the sophisticated mathematical solutions already explained in this literature. Methods of finding Optimal Solution of the CTP Basically two universal methods are used for finding optimal solutions. These are the Stepping Stone method and the Modified Distribution Method (MODI) method. Some heuristics are generated to getting better performance. Different methods are compared for speed factor. Transportation Simplex Method and Genetic Algorithms are compared in terms of accuracy and speed when a large-scale problem is being solved. Genetic Algorithms prove to be more efficient as the size of the problem becomes greater (Kumar and Schilling, 2004). Proposed digital computer technique for solving the CTP is by the stepping stone method. The average time required to perform an iteration using the method described here depends linearly on the size of the problem, m + n. (Dennis). The solution of a real world problem to efficiently transport multiple commodities from multiple sources to multiple different destinations using a finite fleet of heterogeneous vehicles in the smallest number of discrete time periods g ives improvement by backward decomposition (Poh, Choo and Wong, 2005).The most efficient method for solving CTP arises by coupling a primal transportation algorithm with a modified row minimum start rule and a modified row first negative evaluator rule. (Glover, Karney, Kligman, Napier, 1974) this has already been explained above. Application Software Geographic Information Systems (GIS) is a field of with an exponential growth that has a pervasive reach into everyday life. Basically, GIS provides a mean to convert data from tables with topological information into maps. Subsequently GIS tools are capable of not only solving a wide range of spatially related problems, but also performing simulations to help expert users organized their work in many areas, including public administration, transportation networks, transportation networks and environmental applications. Below gives some of the software that has been used by many researchers in transportation modeling. Much software have been used to solve the CTP problem for example, the MODI Algorithm was coded in FORTRAN V, and further substantial time reductions may result by a professional coding of the algorithm in Assembler language. Zimmer reported that a 20-to-1 time reduction was possible by using Assembler rather than FORTRAN in coding minimum path algorithms. (Srinivasan and Thompson, 1973).One work investigated generalized network problems in which flow conservation is not maintained because of cash management, fuel management, capacity expansion etc (Gottlieb,2002). Optimal solution to the pure problem could be used to solve the generalized network problem. One work introduces a generalized formulation that addresses the divide between spatially aggregate and disaggregate location modelling (Horner and OKelly, 2005). In this research we are making use of ArcGIS Network analyst, together with ArcMap, ArcCatalog, VBA, Python, PuLP, GLPK (GNU Linear Programming Kit) and ArcObject software to design our model to solve the CTP problem. A detail solution algorithm is explained in chapter 4. The GLPK (GNU Linear Programming Kit) is an open source software package intended for solving large scale linear programming (LP), mixed integer programming (MIP), and other related problems. It is a set of routine written in ANSI C and organized in the form a callable library. The GLPK package includes the following main components: Primal and dal simplex methods Primal-dual interior- point method Branch and- cut method Application program interface (API) Translator for GNU Math Program Stand-alone LP/MIP solver PuLP is a LP modeller written in Python. PuLP can generate LP and MPS files and call GLPK, to solve linear problems. PuLP provides a nice syntax for creation of linear problems, and a simple way to call the solvers to perform the optimization. ArcGIS Network Analyst is still relatively new software, so there are not much published materials concerning its application on transportation problems. Only few researchers during the last years have reported the use of the ArcGIS Network Analyst extension in order to solve some transportation problems. ArcGIS Network Analyst (ArcGIS NA) is a powerful tool of ArcGIS desktop 9.3 that provides network- based spatial analysis including routing, travel directions, closest facility, and service area analysis. ArcGIS NA enables users to dynamically model realistic network con

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ETRUSCAN MONARCHS   Ã‚  Ã‚  Ã‚  Ã‚  The Etruscans were a very sophisticated people who controlled land roughly from Cumae (on the northern end of the Bay of Naples) to the Po River. They had great artistic skills and were skilled traders. Eventually, the Etruscans expanded their influence southward and conquered the Romans.   Ã‚  Ã‚  Ã‚  Ã‚  The first Etruscan king of Rome was L. Tarquinius Priscus (616-579 BCE). Priscus chose and cleared the site for the great temple JUPITER OPTIMUS MAXIMUS (meaning â€Å"Jupiter best and greatest†), which would be located on CAPITOLINE, on one of the Seven Hills of Rome. In its later years, the civilization of Rome focused itself on CAPITOLINE. This was the temple dedicated to Jupiter who was the father of the gods and therefore most powerful. Priscus also allegedly built the CLOACA MAXIMA, or great sewer.   Ã‚  Ã‚  Ã‚  Ã‚  The 2nd Etruscan king, Servius Tullius (579-534 BCE), was said to have carried on the program of urban renewal begun by his predecessor.   Ã‚  Ã‚  Ã‚  Ã‚  The final Etruscan monarch, Tarquin the Proud, was ejected by means of popular rebellion in 509 BCE. It began because his son Sextus rapped a chaste aristocrat named Lucretia who later committed suicide because of it.   Ã‚  Ã‚  Ã‚  Ã‚  With the final king gone, the way was paved for the formation of the democratic republic. The Etruscan military power fell and those who lived near Rome were absorbed into the new republic. CONSULS OF THE ROMAN REPUBLIC   Ã‚  Ã‚  Ã‚  Ã‚  After the removal of the final Etruscan monarch, two men from the senate were elected by the members of the COMITIA CENTURIA to take the position as consuls; the chief Magistrates of the Roman state who were elected annually. One colleague could veto (meaning forbid) the decision of the other thereby acting as a safe guard against abuse of power. GACCHUS BROTHERS   Ã‚  Ã‚  Ã‚  Ã‚  Tiberius Gracchus was elected to tribune of the people in 133 BCE. He believed he could solve the problems of the poor by redistributing the land. He set up a land commission to distribute ten-hectare plots. He misused his authority when he announced that he would seek re-election as tribune. Such an act was unheard of in this time. This action in sighted a riot within the already angry land owning senators in Rome. 3000 people were killed, amongst them was Tiberius himself. Regardless, the land commission continued and some 80 000 people were resettled.   Ã‚  Ã‚  Ã‚  Ã‚   Gaius Gracchus was elected tribune in 123 BCE. He was an enthusiastic reformer who believed he had the answer to the conflicting interests of the population.

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English in your country to study English in other country, but in general there are more differences. Both options can be beneficial when you decide study English. In this essay will be discuss all the similarities and differences between learn English in Mexico to learn English in Australia, mention the class structure, teachers and the environment outside class. Paragraph 2: Sub topic 1 – Compare (class Structure') To begin with classes with 15-20 students in a classroom, this can be change all the time is not exactly always but it is the common number of students.Secondly, the teachers teach grammar, speaking, writing, listening and reading. There are exams or tests every week and it is important to pass them. Thirdly, everyone can learn English in a private school or in English courses. You need to take a course to present the TOEFL or EELS. Paragraph 3: Sub topic 1 – Contrast To begin with Mexico, there are only 3 levels of English: basic, intermediate and advance. However, is not to common to teach pronunciation. Studying in your country is cheaper than studying in overseas. The classes during about one or two and half hours.Instead, in Australia are more levels for English, also academic English. You can decide to do a Bachelor or study the University. Although, is more expensive and the classes are full time.. If you study in Mexico, depend the course that you want to take, maybe for 6 months or a couple of weeks. You know that the English School is near your house or you only need to drive. But if you decide to study in Australia you need to stay in that country no less than 4 months and can decide to stay more than 1 year with the possibility to extend more.Paragraph 4: Sub topic 2 – Compare (environment outside class') In Mexico like in Australia moreover, you can meet new people , and a great point is that all those people take the course for learn a new language, English. It is a good way to open more your ideas about learning English because every different person that you meet have different ways or manners and you can learn about all these stuff too. Paragraph 5: Sub topic 2 – Contrast In Mexico, after English classes you still speak your own language (Spanish).As well, you are near you family and friends, with all the things that you know. For example, food, public transport, the City, etc. However can be a slow process for learn English. On the other hand, in Australia you speak English all the time, in school, in the street, in the place that you live. Every time. Although, study English in Mexico has less possibilities to meet people from others parts of the world, it is more common to meet new people from Mexico, but if you decide to learn English in Australia you meet people from over the world.Paragraph 6: Sub topic 3 – Compare (teachers') First in Mexico and in Australia the English teachers speak very well English. They have a certificate or accreditation to confirm that they can teach this language. In lasses there is only one teacher to teach everything. Such as, grammar, speaking, reading, writing, listening, everything. And the same teacher does the tests or exam for the students. There are many kinds of teachers. For example, funny, strict, serious, easy going, difficult, and every teacher has their different way to teach English.Paragraph 7: Sub topic 3 – Contrast On the contrary, in Mexico the teachers are from the same country, they need to learn English before teach to students. Sometimes or in general it is more common to communicate in a formal way or depend the teachers but this happened more hen you study the high school. In Australia whereas, great point is that the teachers are natives they talk naturally English, and a better point is that can be teachers from others apart of the world. For example: England, from America, New Zealand, etc.There are more easy going and it is good for the person who start to learn English because their listen accent, pronunciation, the native language Paragraph 8: Conclusion In conclusion, It is important to mention that everyone to choose study English must to study hard and be concentrating all the time. Nevertheless, there are people homo get quickly English because is easier for others. Study English for first time could be difficult, because it is a new and different language.A good point is that all the people that you can meet have similar purpose and you cannot feel bad for known English or for learn slowly. Additionally, you need to know that Australia is totally opposite from Mexico it is so far. And for a long time you will live far from your country, family and friends, and maybe you can have ‘homesick for a short period or always. But the experience that you can have when you learn English in Australia is en of the biggest goals. For instance, you meet people from over around the world, but sometimes you only meet people to come to study English not native peopl e.For example, you have many new friends from Thailand, Korea, and Brazil but maybe you don't know anybody from Australia. Further to this, study in other country has more extra qualities, for example: you can mention in your resume that you learn English in Australia and has experience in different things. And all this can help you to find a better Job. Study English can open more doors in different ways, whatever you iced if study in Mexico or in Australia, but choose study in Australia can change the way that you see the live in many amazing ways.

Effects of Aerobic Exercise on Heart Rate Essay

Introduction: Our bodies need to be in balance in order to function properly, and there are many ways the body maintains balance, or homeostasis. Homeostasis is the maintenance of nearly constant conditions in the internal environment. Our normal heart rate is an example of our body in homeostasis and any sort of change, or stimulus, can alter it. Exercise, adrenaline in the blood, and a low blood pH are all stimuli that increase the heart rate. Exercise, for example, stimulates stretch receptors in the muscles. These receptors then send a signal to a part of the brain called the medulla oblongata that receives the sensory input. It then in turn sends nerve impulses to the sinoatrial node in the heart. This node generates an impulse and initiates contraction of the heart at a quicker pace. Thus, the heart beats faster, which equals an increased heart rate. This is an example of a homeostasis imbalance. The heart reaches homeostasis again when exercise ceases and the heart rate drops down to its basal rate, or its rate at rest. This whole process is an example of a negative feedback cycle: a stimulus (increased heart rate) sends receptors to the control center (medulla oblongata), which then sends effectors (impulses by the vagus nerve, or the efferent pathway) to the heart to slow the heart contractions, thus reducing the heart rate and bringing it back to its basal rate. In our experiment we studied heart rate before and after a brief exercise session. Our hypothesis is exercise will increase the heart rate, and a negative feedback mechanism will occur to restore the heart rate back to its normal basal rate. Materials: Stop watch, metronome, stairs Methods: †¢Eight subjects took their own resting, or basal, heart rate for 15 seconds while standing up. Some subjects chose to take their heart rate at their carotid artery, and some took their pulse using their radial artery. This number was multiplied by 4 to get beats per minute. This is how all heart rate measurements were taken throughout the experiment. †¢Subjects did exercise session. They walked down 57 stairs and then back up those same 57 stairs for a total of 104 stair steps. This was done at a pace of 85 beats per minute. The whole session took 1 minute 45 seconds. †¢Subjects immediately took their heart rate after they completed the exercise. †¢After 1 minute of completing the exercise, subjects measured their heart rate again. This was done at 1 minute intervals for a total of 5 heart rate measurements after completing the exercise. †¢All together, subjects took 6 heart rate measurements: 1 before the exercise, and then 5 after the exercise. Data/Results: See attached graph and table. Conclusion/Discussion: The data shows that heart rate increases during and after exercise and begins to drop back down close to the basal rate after rest. The heart progressively decreases after each minute of rest. Our results show a negative feedback mechanism was used to control the heart rate after exercise. The increased heart rate stimulated the medulla oblongata which sent impulses to the sinoatrial node of the heart to slow down contractions and decrease the heart rate. Different subjects had differences in the time it took for their heart rate to drop after the exercise, but heart rate decreased nonetheless. Overall, our hypothesis was shown to be correct from the experiment. We chose the heart rate as our variable because it is easy to measure and gives clear results. We predicted that the heart would increase after a brief exercise session, and our results matched that prediction. As for other experiments, we could perform different activities or tasks and measure our hear t rate after those. We could even hold a serious/heated discussion and see if heart rate is affected in an intense conversation. There are many different things you could do to test heart rate, as exercise is just one example. Data: Each subject and their heart rate at certain time interval: SubjectBefore exercise0 minutes rest1 min. rest2 min. rest3 min. rest4 min. rest 1100 BPM120 BPM104 BPM104 BPM104 BPM104 BPM 2120160156156152148 37210076807672 47212080727272 596136124120100100 66812072727680 76011664646464 86816084888084 Summary statement: Heart rate increases during and after exercise and begins to drop back down close to the basal rate after rest. Citations Heart Rate Regulation in Humans. (2010, January 23). The Student Room. Retrieved August 24, 2013, from http://www.thestudentroom.co.uk/showthread.php%3Ft%3D1059551%26page%3D45&q=&esrc=s&ei=EEIuUtiHKMKUiQL86YDQDQ&usg=AFQjCNGj9jN4mV3pDlB7dF1yuUm0gn81gA