Livres sur le sujet « Bottleneck theory »

This chapter introduces steps 4 through 7 of the theory of constraints—that, respectively, decide how to exploit and utilize the constraint, subordinate the system to the constraint, elevate and break the constraint, and do not let inertia become the system constraint. The chapter shows how to achieve more using the existing resources by focusing on the bottleneck. For example, reducing waste (“garbage time”) of the bottleneck can quite quickly increase the system’s throughput. The subordination of the rest of the system to the bottleneck is then discussed. For this purpose, the scheduling mechanism of drum–buffer–rope can be implemented in some areas of healthcare systems, like operating rooms, leading to increased throughput and reduction of waiting times as well as improved clinical quality.

Having a market constraint means that the system has excess capacity. For such cases, this chapter shows how the seven steps of the theory of constraints (TOC) can help in increasing demand for healthcare organizations’ services. The chapter adds two other important issues: peak management and the three strategic questions for constraint management. Peak management provides tools for managing systems that are characterized by peaks and dips in demand. The three strategic questions determine whether we should design the healthcare organization with excess capacity or with a bottleneck. In the latter case, the chapter analyzes where the constraint should be located in the long run.

To date, world antitrust and regulatory agencies have invariably described large technology companies—such as Google, Amazon, Microsoft, Apple, and Facebook—as dominant, bottleneck or gatekeeping companies comparable to the textbook monopolists of the early twentieth century. They have proceeded on this basis to discipline their business activities with unprecedented financial penalties and other regulatory obligations. This “techlash” is the subject of this book. Proceeding from the observation that big tech firms engage in both monopoly and oligopoly competition across digital markets, the book introduces a theory of moligopoly competition. It suggests that rivalry-spirited antitrust and regulatory laws are both conceptually and methodologically impervious to the competitive pressure that bears on big tech firms, resulting in a risk of well-intended but irrelevant policy intervention. The book proposes a refocusing of competition policy towards certain types of tipped markets where digital firms extract monopoly rents, and careful adoption of regulation toward other social harms generated by big tech’s business models.

The article focuses on Broadbent's approach to the explanation of attention. Broadbent shows that one's information-processing resources have sufficient capacity to encode the simple physical properties of all the stimuli that one is presented with, but have only a limited capacity for the encoding of the semantic properties of those stimuli. The resulting model depicts perceptual processing as proceeding in two stages. The first stage entails that a large capacity sensory system processes the physical features of all stimuli in parallel. A subset of the representations generated by the large capacity system are selected to be passed on to a second perceptual system, which has a smaller processing capacity, and which has the job of processing the stimuli's semantic properties. Broadbent's theory would explain that pre-bottleneck processing is responsible for the detection of simple physical features, and also for own-name detection. The phenomenology of one's shifting awareness in conditions of binocular rivalry is naturally described as the manifestation of a competition, and perhaps of a biased competition.

The theory of constraints has the potential to increase throughput significantly, using existing resources. It consists of seven focusing steps that, when applied, can create extra capacity in operating rooms, emergency departments, imaging services, labs, and so on. The seven steps are simple, intuitive, and easy to implement. This chapter discusses the first three steps of the theory of constraints: determining the system’s goal, establishing global performance measures, and identifying the system constraint. Tools are provided for identifying bottlenecks and determining measures of performance for the system. It also introduces the cost-utilization diagram that provides managers with a full-system view.

The competence of deep learning for the automation and manufacturing sector has received astonishing attention in recent times. The manufacturing industry has recently experienced a revolutionary advancement despite several issues. One of the limitations for technical progress is the bottleneck encountered due to the enormous increase in data volume for processing, comprising various formats, semantics, qualities and features. Deep learning enables detection of meaningful features that are difficult to perform using traditional methods. The book takes the reader on a technological voyage of the industry 4.0 space. Chapters highlight recent applications of deep learning and the associated challenges and opportunities it presents for automating industrial processes and smart applications. Chapters introduce the reader to a broad range of topics in deep learning and machine learning. Several deep learning techniques used by industrial professionals are covered, including deep feedforward networks, regularization, optimization algorithms, convolutional networks, sequence modeling, and practical project methodology. Readers will find information on the value of deep learning in applications such as natural language processing, speech recognition, computer vision, online recommendation systems, bioinformatics, and videogames. The book also discusses prospective research directions that focus on the theory and practical applications of deep learning in industrial automation. Therefore, the book aims to serve as a comprehensive reference guide for industrial consultants interested in industry 4.0, and as a handbook for beginners in data science and advanced computer science courses.

The chapter explores features of institutional design that hamper epistemic performance, especially ‘epistemic bottlenecks’. The first section looks at the influence of strong leaders. The epistemic losses can be severe, especially if the leaders are influential and their number small. The second section shows how legislative committees and smaller upper chambers can act as bottlenecks. Quality deliberation may mitigate the effect. The third section analyses the epistemic outcome when party whips or small pivotal parties are in control. Finally, bottlenecks can also be created by supermajority rules, presidential vetoes, or by ‘cooling-off periods’.

One attractive feature of democracy is its ability to track the truth by information aggregation. The formal support for this claim goes back to Condorcet’s famous jury theorem. However, the theorem has often been dismissed as a mathematical curiosity because the assumptions on which the theorem is based are demanding. Such quick dismissals tend to misunderstand the original theorem. They also fail to appreciate how Condorcet’s assumptions can be weakened to obtain jury theorems that are readily applicable in the real world. The first part of the book explains the original theorem and its various extensions and introduces results to deal with the challenge of voter dependence. Part II considers opportunities to make democracies perform better in epistemic terms by improving voter competence and diversity, by dividing epistemic labour, and by preceding voting with deliberation. In the third part, political practices are looked at through an epistemic lens, focusing on the influence of tradition, following opinion leaders or cues, and on settings in which the electorate falls into diverging factions. Part IV analyses the implications for the structures of government. While arguing against the case for epistocracy, the use of deliberation and expert advice in representative democracy can lead to improved truth-tracking, provided epistemic bottlenecks are avoided. The final part summarizes the results and explores how epistemic democracy might be undermined, using as case studies the Trump and Brexit campaigns.

This chapter reviews the status quo of research on talent management in nations with emerging economies. It highlights a number of major challenges confronting these nations and some of the initiatives of the nation states to combat the bottleneck caused by talent shortages in their economic development. The chapter highlights the research conducted on various aspects of talent management, and it presents a set of research agendas for future studies. Further, it shows that research on talent management in emerging economies has largely focused on a small number of countries and multinational corporations. While there is a growing level of understanding of the effectiveness and types of talent-management activities in different national contexts and types of organizational settings, future research in this field would benefit from drawing on a broader set of disciplinary perspectives and using more robust research design and systematic analysis of practices, processes, and outcomes.

This article presents a conspectus on the prehistory of northwestern Turkey, mainly focusing on the role played by eastern Thrace at the intersection of Anatolia, the Aegean, and the Balkans. It considers the question of whether Thrace was a bridge or a barrier between the east and the west, while acknowledging that there are substantial lacunae in our knowledge on every issue noted herein. Accordingly, what is reported here should not be considered conclusive, but as more of a general overview. There are major problems in assessing the evidence from northwestern Turkey and the region known as eastern Thrace, first because it constitutes the buffer zone between distinct cultural entities: Anatolia, the Aegean, Balkan, and Pontic regions. Moreover, it acts as the narrow bottleneck to any sort of supraregional interaction, inevitably merging distinct cultures.

Traditionally, attentional selection has been thought of as arising naturally from resource limitations, with a focus on what might be the most apt metaphor, e.g. whether it is a ‘bottleneck’ or ‘spotlight’. However, these simple metaphors cannot account for the specificity, flexibility, and heterogeneity of the way attentional selection manifests itself in different behavioural contexts. A recent body of theoretical work has taken a different approach, focusing on the computational needs of selective processing, relative to environmental constraints and behavioural goals. They typically adopt a normative computational framework, incorporating Bayes-optimal algorithms for information processing and action selection. This chapter reviews some of this recent modelling work, specifically in the context of attention for learning, covert spatial attention, and overt spatial attention.

Historical linguistics is a key witness in reconstructing the prehistory of Oceania. The extraordinary number of Papuan (non-Austronesian) language families in Near Oceania is consistent with archaeological evidence that this region was settled over 40,000 years ago. One family, Trans New Guinea, is exceptional in its wide distribution, suggesting that its expansion was underpinned by technological advances. Most Austronesian languages of Oceania fall into a single branch of the family, Oceanic, indicating that they stem from a bottleneck in the Austronesian expansion into the southwest Pacific, associated with the formation of Proto Oceanic (POc). The final stages of this formative period almost certainly took place in the Bismarck Archipelago and the subsequent rapid dispersal of Oceanic languages across the southwest Pacific can be connected with the region's colonization by bearers of the Lapita archaeological culture. The reconstructed lexicon of POc provides information about early Lapita material culture and social organization.

This article reviews recent advances in field emission cathodes and their applications, focusing on a number of possibilities emerging from the field of nanotechnology. It begins with an overview of the driving forces for the evolution of cold cathodes, laying emphasis on their fundamental characteristics and industrial applications as well as the bottlenecks of metallic field emitters. It then considers single-atom emitters, followed by different examples where the advent of nanotechnology has contributed towards improving new cold cathodes. It also discusses the Fresnel projection microscope and the microgun, a route to the microcolumn approach which is associated with the nanotip; a host of material issues for field emitters, taking into account carbon nanocompounds; carbon-nanotube field emitters; and carbon-nanopearl field emitters. The article concludes with an evaluation of the applications and uses of carbon nanocompounds, carbon nanotubes and carbon nanopearls as cold cathodes.

Medical innovation as it stands today is fundamentally unsustainable. There is a widening gap between what biomedical research promises and its current impact in terms of patient benefit and health system improvement. This book highlights the global problem, analyses underlying causes, and provides powerful prescriptions for change to close the gap.It contrasts progress in biomedicine with other areas of science and technology, such as information technology, in which there are faster, more reliable returns for society from scientific advance. It questions whether society is right to expect so much from biomedicine and why we have become accustomed to such poor returns.It focuses on four specific ‘gaps in translation’ between bioscience breakthroughs and ultimate patient benefit, and explains how unhelpful mental models and differing perceptions of value, risk, and uncertainty contribute to stifling progress.Specific examples are examined, in which these bottlenecks have prevented promised progress (e.g. antibiotic-resistant infections), and others in which these barriers have been overcome, as a result of patient pressure (e.g. HIV treatment) or a sense of impending crisis (e.g. pandemic influenza).

Innovation is an extremely context-specific activity, with both the problems sought to be addressed and the solutions at hand being shaped by the structure and flavour of predominant private activity in the domestic economy, sectoral regulations and State support, and local market needs and purchasing power. In this regard, both public and private entities have been successful in tackling several infrastructure bottlenecks and institutional voids to achieve their goals, promoting innovation along the way. At the same time, several impediments to innovation exist in India, the absence of which could make the pace of innovation-led growth much faster, and its scale, much bigger. Confusing, and often inconsistent, regulatory and policy stances are one such impediment. The absence of a clear strategy to promote research and development in emerging technologies is another. The quicker actualization of progressive policies to beneficial action is a third. An education system that internalises the core values requisite for an innovation culture is a fourth. Unless these are addressed on a war footing, a more organic transition to a creative society with indigenous solutions shall remain a distant dream.

This work aims to analyze the possible practical and legal repercussions of the implementation of technologies characteristic of the digital age in the dynamics of advocacy. Considering the increasing influence that scientific advances have exercised not only in human life, but especially in the ways of working and in the models of the professions, the objective was to prospectively investigate the transformations of this context in advocacy. In order to improve the understanding of the research, three common sectors-activities were separated between the more traditional advocacy: manual labor; systems and departments, highlighting the most recurring bottlenecks. Ahead, there were also three technologies highlighted in the technological revolution, which were: artificial intelligence; automation of legal documents and big data. In the meantime, possible resistance factors between law and technology were also discussed. Finally, through a bibliographic and exploratory methodological process, the research explored possible consequences of the direct insertion of these new technologies in each specific sector of traditional law, considering the functionalities and the problems that would be solved. Thus, there were several repercussions, both practical and legal, including the financial, methodological, strategic and organizational logistics of the offices, among which were mentioned: gain of time; fees. internal costs; data-based procedural strategy, and more. Still, in addition to the realization of the high probability of changes in the lawyer's practice, there was a need to seek solutions that really connect the law to innovations in this new scenario, with emphasis on the contracting of services offered by lawtechs.

The book is devoted to the research and development of methods for combining computational structures for reconfigurable signature-based information protection tools for computer systems and networks in order to increase their efficiency. Network security tools based, among others, on such AI-based approaches as deep neural networking, despite the great progress shown in recent years, still suffer from nonzero recognition error probability. Even a low probability of such an error in a critical infrastructure can be disastrous. Therefore, signature-based recognition methods with their theoretically exact matching feature are still relevant when creating information security systems such as network intrusion detection systems, antivirus, anti-spam, and wormcontainment systems. The real time multi-pattern string matching task has been a major performance bottleneck in such systems. To speed up the recognition process, developers use a reconfigurable hardware platform based on FPGA devices. Such platform provides almost software flexibility and near-ASIC performance. The most important component of a signature-based information security system in terms of efficiency is the recognition module, in which the multipattern matching task is directly solved. It must not only check each byte of input data at speeds of tens and hundreds of gigabits/sec against hundreds of thousand or even millions patterns of signature database, but also change its structure every time a new signature appears or the operating conditions of the protected system change. As a result of the analysis of numerous examples of the development of reconfigurable information security systems, three most promising approaches to the construction of hardware circuits of recognition modules were identified, namely, content-addressable memory based on digital comparators, Bloom filter and Aho–Corasick finite automata. A method for fast quantification of components of recognition module and the entire system was proposed. The method makes it possible to exclude resource-intensive procedures for synthesizing digital circuits on FPGAs when building complex reconfigurable information security systems and their components. To improve the efficiency of the systems under study, structural-level combinational methods are proposed, which allow combining into single recognition device several matching schemes built on different approaches and their modifications, in such a way that their advantages are enhanced and disadvantages are eliminated. In order to achieve the maximum efficiency of combining methods, optimization methods are used. The methods of: parallel combining, sequential cascading and vertical junction have been formulated and investigated. The principle of multi-level combining of combining methods is also considered and researched. Algorithms for the implementation of the proposed combining methods have been developed. Software has been created that allows to conduct experiments with the developed methods and tools. Quantitative estimates are obtained for increasing the efficiency of constructing recognition modules as a result of using combination methods. The issue of optimization of reconfigurable devices presented in hardware description languages is considered. A modification of the method of affine transformations, which allows parallelizing such cycles that cannot be optimized by other methods, was presented. In order to facilitate the practical application of the developed methods and tools, a web service using high-performance computer technologies of grid and cloud computing was considered. The proposed methods to increase efficiency of matching procedure can also be used to solve important problems in other fields of science as data mining, analysis of DNA molecules, etc. Keywords: information security, signature, multi-pattern matching, FPGA, structural combining, efficiency, optimization, hardware description language.

The 2°C target for global warming had been under severe scrutiny in the run-up to the climate negotiations in Paris in 2015 (COP21). Clearly, with a remaining carbon budget of 470–1,020 GtCO2eq from 2015 onwards for a 66% probability of stabilizing at concentration levels consistent with remaining below 2°C warming at the end of the 21st century and yearly emissions of about 40 GtCO2 per year, not much room is left for further postponing action. Many of the low stabilization pathways actually resort to the extraction of CO2 from the atmosphere (known as negative emissions or Carbon Dioxide Removal [CDR]), mostly by means of Bioenergy with Carbon Capture and Storage (BECCS): if the biomass feedstock is produced sustainably, the emissions would be low or even carbon-neutral, as the additional planting of biomass would sequester about as much CO2 as is generated during energy generation. If additionally carbon capture and storage is applied, then the emissions balance would be negative. Large BECCS deployment thus facilitates reaching the 2°C target, also allowing for some flexibility in other sectors that are difficult to decarbonize rapidly, such as the agricultural sector. However, the large reliance on BECCS has raised uneasiness among policymakers, the public, and even scientists, with risks to sustainability being voiced as the prime concern. For example, the large-scale deployment of BECCS would require vast areas of land to be set aside for the cultivation of biomass, which is feared to conflict with conservation of ecosystem services and with ensuring food security in the face of a still growing population.While the progress that has been made in Paris leading to an agreement on stabilizing “well below 2°C above pre-industrial levels” and “pursuing efforts to limit the temperature increase to 1.5°C” was mainly motivated by the extent of the impacts, which are perceived to be unacceptably high for some regions already at lower temperature increases, it has to be taken with a grain of salt: moving to 1.5°C will further shrink the time frame to act and BECCS will play an even bigger role. In fact, aiming at 1.5°C will substantially reduce the remaining carbon budget previously indicated for reaching 2°C. Recent research on the biophysical limits to BECCS and also other negative emissions options such as Direct Air Capture indicates that they all run into their respective bottlenecks—BECCS with respect to land requirements, but on the upside producing bioenergy as a side product, while Direct Air Capture does not need much land, but is more energy-intensive. In order to provide for the negative emissions needed for achieving the 1.5°C target in a sustainable way, a portfolio of negative emissions options needs to minimize unwanted effects on non–climate policy goals.