Academic literature on the topic 'Hard frequency reuse'

This book explores the connection between the so-called robber barons who led American big businesses during the Gilded Age and Progressive Era and the immigrants who composed many of their workforces. As the book argues, attribution of industrial-era class conflict to an “alien” presence supplements nativism—a sociocultural negativity toward foreign-born residents—as a reason for Americans' dislike and distrust of immigrants. And in the era of American industrialization, employers both relied on immigrants to meet their growing labor needs and blamed them for the frequently violent workplace

This chapter evaluates how the fundamental question of whether business interests bore responsibility for attracting pernicious foreigners dominated the 1890s. Personal connections, such as the one between Andrew Carnegie and his steel empire, characterized the decade's labor disputes. Commercial growth and the trend toward consolidation had created large conglomerates, which seemed to signify the nation's coming of age. Even so, recurring class violence affected some of the nation's largest and most prominent businesses and cast a pall upon this glittery milieu. Here was the essence of the Gilded Age, incredible opulence coupled with unsightly social unrest. Against this backdrop, Americans of the 1890s struggled to understand why such incidents seemed to occur with increasing frequency. In the minds of angry workers, fault lay with the economic barons, but those barons and their supporters saw things differently, placing responsibility on the very immigrant employees upon whom their companies relied to meet their labor needs. Employers' only transgression seemed to be their unfortunate hiring of alien subversives.

Software is increasingly being used to enable new features in systems in multiple domains. These domains include automotive, avionics, telecomunication, and industrial automation. Because the user of these systems is not aware of the presence of the software, this type of software is known as embedded software. More importantly, such a software, and the whole system in general, must satisfy not only logical functional requirements but also parafunctional (a.k.a. nonfunctional) properties such as timeliness, security, and reliability. Traditional development languages and tools provide powerful abstractions such as functions, classes, and objects to build a functional structure that reduces complexity and enables software reuse. However, the software elements responsible for the parafunctional behaviors are frequently scattered across the functional structure. This scattering prevents the easy identification of these elements and their independent manipulation/reuse to achieve a specific parafunctional behavior. As a result, the complexity of parafunctional behaviors cannot be reduced and even worse, the construction of those behaviors can corrupt the functional structure of the software. In this chapter, we propose a model-based framework for designing embedded real-time systems to enable a decomposition structure that reduces the complexity of both functional and parafunctional aspects of the software. This decomposition enables the separation of the functional and parafunctional aspects of the system into semantic dimensions (e.g., event-flow, timing, deployment, fault-tolerant) that can be represented, manipulated, and modified independent of one another from an end-user point of view. The realizations of these dimensions, however, do interact on the target platform since they consume common resources and impose constraints. These interactions can be captured during model construction and resource demands mediated during platform deployment. The use of semantic dimensions results in three significant benefits. First of all, it preserves the independence of the functional structure from parafunctional behaviors. Secondly, it enables the user to manipulate different parafunctional concerns (e.g., timeliness, reliability) independent of one another. Lastly, it enables the reuse of compositions along any dimension from other systems. The second core abstraction in our modeling approach is an entity called a coupler. A coupler expresses a particular relationship between two or more components, and can also be used recursively. Couplers enable the hierarchical decomposition of functional as well as parafunctional aspects. Aided by semantic dimensions and multiple coupler types, our framework enables the auto-generation of glue code to produce a fully deployable system. Our framework can also construct a detailed timing and resource model. This model in turn is used to optimize the usage of a given hardware configuration, or synthesize a configuration to suit a given software model. Our framework is implemented in a tool (de Niz, Bhatia & Rajkumar 2006) called SysWeaver that had been used to generate glue code and analyze the timing behavior of avionics, automotive, and software-radio pilot systems.

Being a teacher can be hard. • We invest ourselves wholeheartedly, yet sometimes our efforts fall short. • We know our subject matter, but students may seem uninterested. • We search for more and better ways to teach, but the results can be disappointing. As educators, we will fail. We will be hurt. We will be disap­pointed. We will be discouraged. Yet key to our recovery from these slumps is what we tell ourselves about those failures. What do we need to do? “Just get up.” “Just get up!” With this statement, Olympic gold medal fig­ure skater Scott Hamilton reminds us that the challenges of a skater involve many falls and frequent pain. It is impossible to be a skater and not fall down. All skaters fall. All skaters fail. They know they will fall. They know they will fail. They know both will hurt. Hamilton says: “Just get up!” Too many “falls” without strategies to recover can cause teachers to “crust up.” We generate layers of crust to protect us as we cling to our anger, refuse assistance, and numb our bod­ies, minds, and spirits. But crusting insulates us from feeling and caring, so we miss out on the vitality of our lives. Then “we forget to be glad for all the things that go right” When we know how to “get up,” when we accept that the fall will come again, we can persevere. We feel the strength of our knowing, and we use determination to pull ourselves out of the doldrums. Just get up. Just keep going. Just aspire to do better.

In Chapter 1, we saw how Lucid could be used to express solutions to standard problems such as sorting and matrix multiplication. One of the unique characteristics of Lucid is not only that it can be used as a programming language but it can also be used as a “composition” language. That is, instead of using Lucid to specify computations, it can be used to express how computation components (expressed in some other language) can be “glued” together to form a coherent application. By doing so, the resulting application can enjoy some of the practical benefits attributable to Lucid such as high performance through exploitation of implicit parallelism and robustness through software fault tolerance. In this chapter, we discuss one such use of Lucid—as part of a hybrid language to construct parallel applications to be executed on conventional parallel computers. A conventional parallel computer either consists of a number of processors each with local memory interconnected by a network (as in distributed memory architectures) or a number of processors that share memory possibly using an interconnection network (as in shared memory architectures). The past decade has seen the advent of conventional parallel computers starting with the Denelcor HEP evolving to the CM-2 and Intel Hypercube and further evolving to the CM-5, Intel Paragon, Cray T3D, and IBM SP-2. Even networks of workstations (or workstation clusters) are seen as low-cost (“poor man’s”) parallel computers. Programming of conventional parallel computers has proven to be far more challenging than had been expected. Part of the reason is the continued use of low-level, explicitly parallel programming models such as PVM [42], Linda [10]. Two factors have fueled the continuing use of such languages despite their limited success. 1. The need to reuse existing sequential code because the cost of rewriting legacy applications from scratch is considered prohibitive both in economic and technical terms. 2. The need to run on conventional parallel computers that view a “parallel program” at a low level—as consisting of sequential processes that frequently synchronize and communicate with each other using some form of message passing.

Traditional methods for developing digital learning content usually produce very large, monolithic content that barely can be reused even in similar contexts, despite of the quality they can have. Nonetheless, digital learning content can be described as a set of highly reusable, low-coupled learning objects that can be put together in order to build adaptive, learner-focused content Nowadays, in spite of all technological evolution, it cannot be affirmed that content development in computer-aided teaching/learning process had evolved the same way. This is, indeed, the most expensive, time-con

In platform videogames, players are frequently tasked with solving medium-term navigation problems in order to gather items or powerups. Artificial agents must generally obtain some form of direct experience before they can solve such tasks. Experience is gained either through training runs, or by exploiting knowledge of the game's physics to generate detailed simulations. Human players, on the other hand, seem to look ahead in high-level, abstract steps. Motivated by human play, we introduce an approach that leverages not only abstract "skills", but also knowledge of what those skills can and

During design problem-solving designers frequently come across a variety of rich visual displays. While browsing for different external sources of information, pictorial representations of existing concepts take a relevant prominence. However, once designers start devising new solution ideas to design problems, they often become particularly influenced by the exemplars they come across. Inadequate and excessive reuse of existing (parts of) available solutions has been described as design fixation. Such behaviour has been discussed having an impact on creativity and innovation. The study presen