We embarked on this open-source project in 2010, twenty-one years after the publication of the 2nd edition of Applied **Discrete** **Structures** for Computer Science in 1989. We had signed a contract for the second edition with Science Research Associates in 1988 but by the time the book was ready to print, SRA had been sold to MacMillan. Soon after, the rights had been passed on to Pearson Education, Inc. In 2010, the long-term future of printed textbooks is uncertain. In the meantime, textbook prices (both printed and e-books) had increased and a growing open source textbook movement had started. One of our objectives in revisiting this text is to make it available to our students in an affordable format. In its original form, the text was peer-reviewed and was adopted for use at several universities throughout the country. For this reason, we see Applied **Discrete** **Structures** as not only an inexpensive alternative, but a high quality alternative.

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We embarked on this open-source project in 2010, twenty-one years after the publication of the 2nd edition of Applied **Discrete** **Structures** for Computer Science in 1989. We had signed a contract for the second edition with Science Research Associates in 1988 but by the time the book was ready to print, SRA had been sold to MacMillan. Soon after, the rights had been passed on to Pearson Education, Inc. In 2010, the long-term future of printed textbooks was uncertain. In the meantime, textbook prices (both printed and e-books) had increased and a growing open source textbook movement had started. One of our objectives in revisiting this text is to make it available to our students in an affordable format. In its original form, the text was peer-reviewed and was adopted for use at several universities throughout the country. For this reason, we see Applied **Discrete** **Structures** as not only an inexpensive alternative, but a high quality alternative.

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over 5 million sub-**structures**. The method requires search for the 1,000 most probable derivations un- der this grammar, using beam search, presumably a challenging computational task given the size of the grammar. In spite of these problems, (Bod 2001) gives excellent results for the method on parsing Wall Street Journal text. The algorithms in this paper have a different flavor, avoiding the need to explic- itly deal with feature vectors that track all subtrees, and also avoiding the need to sum over an exponen- tial number of derivations underlying a given tree.

Computing Curricula 2001 reflects a change in perspective from Computing Curricula 1991, including a significant decrease in coverage of some subject areas, an expansion of other areas, and the addition of new areas. Although such adjustments may fit some types of schools, the reduction in hours from CC 1991 to CC 2001 in the areas of algorithms and complexity, theory of computation, and programming languages is inconsistent with the liberal arts perspective. Also, while CC 2001 recommends only one course in **discrete** **structures** and theory, many liberal arts CS faculty now believe that students require at least two semesters to appropriately master this material. Altogether, the change in emphasis in CC 2001 raises important questions regarding the content covered in a liberal arts curriculum.

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(E) Combinatorics: Combinatorics studies the way in which **discrete** **structures** can be combined or arranged. Enumerative combinatorics concentrates on counting the number of certain combinatorial objects - e.g. the twelvefold way provides a unified framework for counting permutations, combinations and partitions. Analytic combinatorics concerns the enumeration (i.e., determining the number) of combinatorial **structures** using tools from complex analysis and probability theory. In contrast with enumerative combinatorics which uses explicit combinatorial formulae and generating functions to describe the results, analytic combinatorics aims at obtaining asymptotic formulae. Design theory is a study of combinatorial designs, which are collections of subsets with certain intersection properties. Partition theory studies various enumeration and asymptotic problems related to integer partitions, and is closely related to q-series, special functions and orthogonal polynomials. Originally a part of number theory and analysis, partition theory is now considered a part of combinatorics or an independent field. Order theory is the study of partially ordered sets, both finite and infinite[6].

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Abstract The Lie group structure of crystals which have uniform continuous distributions of dislocations allows one to construct associated **discrete** struc- tures – these are **discrete** subgroups of the corresponding Lie group, just as the perfect lattices of crystallography are **discrete** subgroups of R 3 , with addi- tion as group operation. We consider whether or not the symmetries of these **discrete** subgroups extend to symmetries of (particular) ambient Lie groups. It turns out that those symmetries which correspond to automorphisms of the **discrete** **structures** do extend to (continuous) symmetries of the ambient Lie group (just as the symmetries of a perfect lattice may be embedded in ‘homo- geneous elastic’ deformations). Other types of symmetry must be regarded as ‘inelastic’. We show, following Kamber and Tondeur, that the corresponding continuous automorphisms preserve the Cartan torsion, and we characterize the **discrete** automorphisms by a commutativity condition, (6.14), that relates (via the matrix exponential) to the dislocation density tensor. This shows that periodicity properties of corresponding energy densities are determined by the dislocation density.

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Abstract- It is well-established fact that shear walls are quite effective in lateral load resistance of low-rise to medium-rise reinforced concrete buildings. Restriction in the architectural design by the presence of the shear walls may contribute to discourage the engineers from adopting the shear walls. Due to this a new concept of providing storey deep and bay wide **discrete** staggered shear wall panels have been introduced.

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In order to evaluate the eﬀect of the modeled structure thickness, the loss function of trilayer graphene is compared to that of the two pentagon cone (Fig. 5). Even though both **structures** are of equal thickness (i.e. three layers), the loss probability is signicantly increased for the cone below the p peak energy. The agreement between the experimental and the modeled dielectric response for the cone is excellent however, and it is thus concluded that the increased intensity at the 1.5 eV (Fig. 3(d)) loss peak is solely a result of local topology induced by the presence of pentagonal defects at the cone apex. Indeed, a topologically induced 1.5 eV loss feature reects the predicted electronic structure of graphene cones, where localized states near the Fermi level result from the topological disorder created by pentagonal defects. 2,3 Fig. 6(a) and (d) show

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The consideration of the dynamic effect and extreme vibration of the **structures** due to the wind action is described in item 9 of NBR 6123/88. Blessmann (1989) clarifies that the Brazilian code presents a equivalent static action of the wind, based in the method of random vibration considered by Davenport. Differs from it in the parameters determination which define this action. The existing recommendations in NBR 6123/88 for the dynamic analysis take into account the variation in the module and in the orientation of the average wind speed. The average speed produces static effect in the structure, whereas the fluctuations or gusts produce important oscillations, “especially in high constructions”. This model of dynamic analysis of high **structures** is also commented by Simiu& Scalan (1996) who associates it with the necessity of the induced vibrations analysis for floating loads. NBR 6123/88 incorporates these concepts and says that constructions with basic period superior of 1 s, frequencies up to 1 Hz, can present important floating reply in the direction of the average wind.

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The Cordus explanation for gravitation is that the sequential energisation of the HEDs creates a torsional pulse that is transmitted outwards, and this creates gravitational attraction. Activation of the three HEDs seems necessary for an enduring mass or gravitational effect. The neutrino does not have the necessary complete HEDs to offer its own gravitational interaction: a similar situation to the photon. Therefore this theory predicts that the neutrino has no nominal mass, based on its lack of the necessary **structures**. However, “mass” may not be quite the right way to look at this. In particular, both the photon and neutrino make up for their incompletely energised HEDs by moving in the fabric. Thus they temporarily do have full HEDs, albeit only instantaneously. Therefore it is possible that they also do have an instantaneous mass and gravitation. While it may register as mass, it would however not be an enduring mass. We conceptualise it rather as an artefact of the propagation process. So it is possible to conceive of the neutrino having zero nominal mass, though a small dynamic mass. This is comparable to the MSW effect (Wolfenstein, 1978) which models the situation as the neutrino obtaining an “effective mass” by a forward scattering process when propagating through matter.

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Electron-beam-plasma interactions are one of the most fun- damental processes in space plasmas. It is well known that electron beam instabilities develop into nonlinear waves and turbulence. Electron phase-space-density holes (e.g. Berk and Roberts, 1967) or electrostatic solitary waves (Mat- sumoto et al., 1994) are coherent nonlinear electrostatic **structures**, while harmonic Langmuir waves and Langmuir wave packets have an incoherent quasi-power-law wavenum- ber spectrum which indicate a turbulent feature (Yoon et al., 2003; Gaelzer et al., 2003; Umeda et al., 2003; Umeda, 2006; Silin et al., 2007). The present study is aimed at the genera- tion of amplitude-modulated Langmuir waves and Langmuir wave packets which is called a Langmuir turbulence in space plasmas.

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This paper presents a robust hybrid improved dolphin echolocation and ant colony optimization algorithm (IDEACO) for optimizing the truss **structures** with **discrete** sizing variables. The dolphin echolocation (DE) is inspired by the navigation and hunting behavior of dolphins. An improved version of dolphin echolocation (IDE), as the main engine, is proposed and uses the positive attributes of ant colony optimization (ACO) to increase the efficiency of the IDE. Here, ACO is employed to improve the precision of the global optimization solution. In the proposed hybrid optimization method, the balance between exploration and exploitation process was the main factor to control the performance of the algorithm. IDEACO algorithm performance is tested on several problems of benchmarks **discrete** truss structure optimization. The results indicate the excellent performance of the proposed algorithm in optimum design and rate of convergence in comparison with other metaheuristic optimization methods, so IDEACO offers a good degree of competitiveness against other existing metaheuristic methods.

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interactions can be naturally captured by an atomistic model. For these reasons, simula- tions combining the continuum and atomistic models can be useful not only for the far field but also for the dislocation center. One of the available tools combining the contin- uum and atomistic models is the variational Peierls-Nabarro (PN) method [21, 22], which generally has been used to calculate dislocation core **structures** by minimizing the total energy of the system. More precisely, the energy in the far field is captured by the energy formulation of continuum linear elasticity theory, while the energy in the core region is obtained by using the crystalline misfit energy and a spread displacement field on the slip plane. The total energy is the sum of both these energy formulations, and the optimal dis- location core **structures** are found when the total energy is minimum. The PN model is known as a tool providing good descriptions of dislocation core **structures** in comparison with MD results [5, 15, 23–25].

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In the Java examples we've shown so far, we've stored primitive variables of type double in our data **structures**. This simplifies the program examples, but it's not repre sentative of how you use data storage **structures** in the real world. Usually, the data items (records) you want to store are combinations of many fields. For a personnel record, you would store last name, first name, age, Social Security number, and so forth. For a stamp collection, you'd store the name of the country that issued the stamp, its catalog number, condition, current value, and so on.

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W structuring techniques of a traditional data **structures** course in an object- oriented context. You’ll find that all of the familiar topics of lists, stacks, queues, trees, graphs, sorting, searching, Big-O complexity analysis, and recursion are still here, but covered from an object-oriented point of view using Java. Thus, our struc- tures are defined with Java interfaces and encapsulated as Java classes. We use abstract classes and inheritance, as appropriate, to take advantage of the relation- ships among various versions of the data **structures**. We use design aids, such as Class-Responsibility-Collaborator (CRC) Cards and Universal Modeling Language (UML) diagrams, to help us model and visualize our classes and their interrelation- ships. We hope that you enjoy this modern and up-to-date approach to the tradi- tional data **structures** course.

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The principles of OOP and classical data **structures** are language independent. Our experience has shown that these principles need to be brought to life using well-crafted examples supported by a rich object-oriented programming language. In our view, Java fits this bill. It provides constructs and predefined standard libraries that directly support and connect to the rich body of underlying OOP and data structure principles. We have chosen Java because its usage is rising rapidly, it provides relative safety in programming, it is readily and inexpensively available (free in many cases), and it offers the user a clean and powerful object model. But make no mistake – this is not yet another book on Java programming. So what do we wish to achieve?

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fying integration of many topics from the areas of problem solving, data **structures**, program development, and algorithm analysis. Students need time and practice to understand general methods. By combining the studies of data abstraction, data **structures**, and algorithms with their implementations in projects of realistic size, an integrated course can build a solid foundation on which, later, more theoretical courses can be built. Even if it is not covered in its entirety, this book will provide enough depth to enable interested students to continue using it as a reference in later work. It is important in any case to assign major programming projects and to allow adequate time for their completion.

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MWSS: Data Structures and Algorithms in Java:Introduction A Simple Linked List THE Link CLASS THE LinkList CLASS THE insertFirst METHOD THE deleteFirst METHOD THE displayList METHOD THE [r]

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This book presents the data **structures** and algorithms that underpin much of today's computer programming. The basis of this book is the material contained in the first six chapters of our earlier work, The Design and Analysis of Computer Algorithms. We have expanded that coverage and have added material on algorithms for external storage and memory management. As a consequence, this book should be suitable as a text for a first course on data **structures** and algorithms. The only prerequisite we assume is familiarity with some high-level programming language such as Pascal. We have attempted to cover data **structures** and algorithms in the broader context of solving problems using computers. We use abstract data types informally in the description and implementation of algorithms. Although abstract data types are only starting to appear in widely available programming languages, we feel they are a useful tool in designing programs, no matter what the language.

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In this chapter, we show: why these features are important; how the v e c t o r is used to implement arrays in C++; how the s t r i n g is used to implement strings in C++; how basic poi[r]

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