Towards a Lexically Oriented Automatic Parsing

1991 ◽  
Vol 15 (1) ◽  
pp. 1-40
Author(s):  
Lucio Costa
Keyword(s):  
Artificial Intelligence ◽  
Distributed Control ◽  
Data Structures ◽  
General Framework ◽  
Computational Models ◽  
The Other ◽  
Sono Stati ◽  
Use Context ◽  
And Linguistics ◽  
Context Free

RIASSUNTO La ricerca sul linguaggio naturale condotta in Intelligenza Artificiale si è sviluppata, malgrado le apparenze, in modo alquanto indipendente dal la-voro dei linguisti. Da un lato sono stati elaborati modelli computazionali delle facoltà di lunguaggio che si configurano come largamente autonomi rispetto a quelli sviluppati in linguistica. D'altro lato, l'implementazione dei sistemi è stata influenzata da soluzioni pragmatiche connesse all'efficacia computazionale delle regole indipendenti dal contesto, alla necessità di evitare componenti trasformazionali inversi e ad una concezione rappresenta-zionale del significato. Il presente articolo propone l'interesse dei lavori lin-guistici di Z. S. Harris e M. Gross ai fini dello sviluppo di un'analisi sintat-tica automatica che sia a controllo diffuso e incentrata sul comportamento idiosincratico delle unità lessicali. Essa è anche inquadrata nel tentativo di gettare luce sulla natura del processo denotazionale. SUMMARY In spite of the claim on the interactions between artificial intelligence (AI) and linguistics, AI research on natural language has developed independently from the work of linguists. On one hand, computational models of the faculties of language which are independent from the models developed in linguistics have been worked out. On the other hand, the AI system design has been oriented towards practical solutions, whose main motivations where to use context-free rules, to avoid an inverse transformational component, and to represent meanings by some data structures. This paper is about the linguistic works of Z.S. Harris and M. Gross to develop automatic distributed control parsing which takes seriously into account the indiosyncratic behaviour of the lexical items. The general framework for the discussion is the procedural nature of the denotational process.

DEVELOPING THE SCIENTIFIC MAGAZINE IN THE PERIOD OF THE FOURTH INDUSTRIAL REVOLUTION 4.0

2019 ◽  
Vol 8 (1) ◽  
Author(s):  
Nguyen Duy Dung
Keyword(s):  
Artificial Intelligence ◽  
Information Technology ◽  
Industrial Revolution ◽  
Scientific Journal ◽  
Publishing Research ◽  
The Other ◽  
High Tech ◽  
Fourth Industrial Revolution ◽  
Socio Economic Development ◽  
International Scientific Journal

Characteristics of the industrial revolution 4.0 is the wide application of high-tech achievements, especially information technology, digitalization, artificial intelligence, network connections for management to create sudden changes in socio-economic development of many countries. Therefore, to reach the high-tech time, many magazines in Vietnam have changed dramatically, striving to reach the international scientific journal system of ISI, Scopus. The publication of international standard scientific journal will meet the demand of publishing research results of local scientists, on the other hand contribute to strengthening exchange, cooperation, international integration in science and technology.

Computing Possible Futures

2019 ◽  
Author(s):  
William B. Rouse
Keyword(s):  
Artificial Intelligence ◽  
Machine Learning ◽  
Computational Modeling ◽  
Mental Model ◽  
Data Analytics ◽  
Computational Models ◽  
Senior Managers ◽  
Interactive Visualizations ◽  
Use Of Models ◽  
Better Than

This book discusses the use of models and interactive visualizations to explore designs of systems and policies in determining whether such designs would be effective. Executives and senior managers are very interested in what “data analytics” can do for them and, quite recently, what the prospects are for artificial intelligence and machine learning. They want to understand and then invest wisely. They are reasonably skeptical, having experienced overselling and under-delivery. They ask about reasonable and realistic expectations. Their concern is with the futurity of decisions they are currently entertaining. They cannot fully address this concern empirically. Thus, they need some way to make predictions. The problem is that one rarely can predict exactly what will happen, only what might happen. To overcome this limitation, executives can be provided predictions of possible futures and the conditions under which each scenario is likely to emerge. Models can help them to understand these possible futures. Most executives find such candor refreshing, perhaps even liberating. Their job becomes one of imagining and designing a portfolio of possible futures, assisted by interactive computational models. Understanding and managing uncertainty is central to their job. Indeed, doing this better than competitors is a hallmark of success. This book is intended to help them understand what fundamentally needs to be done, why it needs to be done, and how to do it. The hope is that readers will discuss this book and develop a “shared mental model” of computational modeling in the process, which will greatly enhance their chances of success.

scholarly journals Interventional radiology and artificial intelligence in radiology: Is it time to enhance the vision of our medical students?

2020 ◽  
Vol 11 (1) ◽  
Author(s):  
Pierre Auloge ◽  
Julien Garnon ◽  
Joey Marie Robinson ◽  
Sarah Dbouk ◽  
Jean Sibilia ◽  
...  
Keyword(s):  
Artificial Intelligence ◽  
Interventional Radiology ◽  
Clinical Practice ◽  
Medical Students ◽  
Medical Curriculum ◽  
New Technology ◽  
Large Population ◽  
The Other ◽  
Clinical Phase ◽  
Preclinical Phase

Abstract Objectives To assess awareness and knowledge of Interventional Radiology (IR) in a large population of medical students in 2019. Methods An anonymous survey was distributed electronically to 9546 medical students from first to sixth year at three European medical schools. The survey contained 14 questions, including two general questions on diagnostic radiology (DR) and artificial intelligence (AI), and 11 on IR. Responses were analyzed for all students and compared between preclinical (PCs) (first to third year) and clinical phase (Cs) (fourth to sixth year) of medical school. Of 9546 students, 1459 students (15.3%) answered the survey. Results On DR questions, 34.8% answered that AI is a threat for radiologists (PCs: 246/725 (33.9%); Cs: 248/734 (36%)) and 91.1% thought that radiology has a future (PCs: 668/725 (92.1%); Cs: 657/734 (89.5%)). On IR questions, 80.8% (1179/1459) students had already heard of IR; 75.7% (1104/1459) stated that their knowledge of IR wasn’t as good as the other specialties and 80% would like more lectures on IR. Finally, 24.2% (353/1459) indicated an interest in a career in IR with a majority of women in preclinical phase, but this trend reverses in clinical phase. Conclusions Development of new technology supporting advances in artificial intelligence will likely continue to change the landscape of radiology; however, medical students remain confident in the need for specialty-trained human physicians in the future of radiology as a clinical practice. A large majority of medical students would like more information about IR in their medical curriculum; almost a quarter of students would be interested in a career in IR.

scholarly journals Out of the loop? On the radical and the routine in urban big data

Urban Studies ◽  
2021 ◽  
pp. 004209802110140
Author(s):  
Sarah Barns
Keyword(s):  
Artificial Intelligence ◽  
Big Data ◽  
Computational Models ◽  
Data Driven ◽  
Urban Systems ◽  
Out Of The Loop ◽  
Urban Futures ◽  
Urban Behaviour ◽  
The City

This commentary interrogates what it means for routine urban behaviours to now be replicating themselves computationally. The emergence of autonomous or artificial intelligence points to the powerful role of big data in the city, as increasingly powerful computational models are now capable of replicating and reproducing existing spatial patterns and activities. I discuss these emergent urban systems of learned or trained intelligence as being at once radical and routine. Just as the material and behavioural conditions that give rise to urban big data demand attention, so do the generative design principles of data-driven models of urban behaviour, as they are increasingly put to use in the production of replicable, autonomous urban futures.

scholarly journals Representations, Affordances, and Interactive Systems

2021 ◽  
Vol 5 (5) ◽  
pp. 23
Author(s):  
Robert Rowe
Keyword(s):  
Artificial Intelligence ◽  
Cognitive Science ◽  
Data Structures ◽  
Digital Computer ◽  
Mental Representations ◽  
Interactive Systems ◽  
Algorithmic Composition ◽  
The World ◽  
History Of

The history of algorithmic composition using a digital computer has undergone many representations—data structures that encode some aspects of the outside world, or processes and entities within the program itself. Parallel histories in cognitive science and artificial intelligence have (of necessity) confronted their own notions of representations, including the ecological perception view of J.J. Gibson, who claims that mental representations are redundant to the affordances apparent in the world, its objects, and their relations. This review tracks these parallel histories and how the orientations and designs of multimodal interactive systems give rise to their own affordances: the representations and models used expose parameters and controls to a creator that determine how a system can be used and, thus, what it can mean.

Studying Political Leadership: The Case of François Mitterrand

1994 ◽  
Vol 42 (3) ◽  
pp. 453-468 ◽  
Author(s):  
Alistair Cole
Keyword(s):  
General Framework ◽  
Political Leadership ◽  
The Other ◽  
The Political ◽  
Environmental Constraints ◽  
Liberal Democratic ◽  
The One

The study of political leadership, in France and elsewhere, must be appreciated in terms of the interaction between leadership resources (personal and positional) on the one hand, and environmental constraints and opportunities on the other. This article proposes a general framework for appraising comparative liberal democratic political leaderships. It illustrates the possibilities of the framework by evaluating the political leadership of the French President François Mitterrand.

scholarly journals Rising Sino-U.S. Competition in Artificial Intelligence

2018 ◽  
Vol 04 (02) ◽  
pp. 241-258 ◽  
Author(s):  
You Wang ◽  
Dingding Chen
Keyword(s):  
Artificial Intelligence ◽  
United States ◽  
The United States ◽  
Cutting Edge ◽  
The Other ◽  
Strategic Competition ◽  
Bilateral Relations ◽  
The Future ◽  
Important Field ◽  
Political Security

Both China and the United States are international leaders in artificial intelligence (AI). Although there remains a significant gap between them in cutting-edge technologies, and they have adopted different methods of planning and implementation, both countries have been mobilizing national resources and formulating policies to promote AI development, so as to achieve a strategic advantage over the other, especially against the backdrop of ever more intense and complicated strategic competition between them in recent years. As an epitome of their changing relationship, Sino-U.S. competition in AI development is manifested in economic, political, security, technological and other fields. It is expected that artificial intelligence will become an even more important field of competition between China and the United States, and that the trends of AI development and competition will to some extent determine the future dynamics of their bilateral relations.

scholarly journals El sesgo de la máquina en la toma de decisiones en el proceso penal.

2020 ◽  
Vol 6 (2) ◽  
pp. 54-71
Author(s):  
Raquel Borges Blázquez
Keyword(s):  
Artificial Intelligence ◽  
The Other ◽  
Human Being ◽  
Criminal Process ◽  
Ethical Problems ◽  
Intelligent Machines ◽  
Other Hand ◽  
Toma De Decisiones ◽  
Legal Thinking ◽  
The One

Artificial intelligence has countless advantages in our lives. On the one hand, computer’s capacity to store and connect data is far superior to human capacity. On the other hand, its “intelligence” also involves deep ethical problems that the law must respond to. I say “intelligence” because nowadays machines are not intelligent. Machines only use the data that a human being has previously offered as true. The truth is relative and the data will have the same biases and prejudices as the human who programs the machine. In other words, machines will be racist, sexist and classist if their programmers are. Furthermore, we are facing a new problem: the difficulty to understand the algorithm of those who apply the law.This situation forces us to rethink the criminal process, including artificial intelligence and spinning very thinly indicating how, when, why and under what assumptions we can make use of artificial intelligence and, above all, who is going to program it. At the end of the day, as Silvia Barona indicates, perhaps the question should be: who is going to control global legal thinking?

scholarly journals THE ADVANCEMENT OF ARTIFICIAL INTELLIGENCE A WAY TO MAN AND MACHINE IN COMBAT IN TIME MACHINE AND I ROBOT

2019 ◽  
Vol 6 (1) ◽  
pp. 14-16
Author(s):  
Sumathi R ◽  
Sutharshan V
Keyword(s):  
Artificial Intelligence ◽  
Science Fiction ◽  
20Th Century ◽  
Scientific Knowledge ◽  
The Other ◽  
Time Machine ◽  
General Outline ◽  
Fantasy Fiction ◽  
Research Article ◽  
Future Events

Science fiction has proved notoriously difficult to define. It can be explained as a combination of science and technology and development in robotics in short it can be otherwise called as ‘realistic speculation about future events and a genre based on an imagined alternative to the reader's environment. It has been called a form of fantasy fiction and an historical literature. The paper goes further with two main concepts one with clash between two people of future and the other with advancement of science particularly on robotics. First is about general outline to science fiction in short a (SF) a genre cause problem because itdoes not recognize the hybrid nature of many SF works. It is more helpful to think of it as a mode or field where different genres and subgenres intersect. And then there is the issue of science. In the early decades of the 20th century, a number of writers attempted to tie this fiction to science and event to use it as a means of promoting scientific knowledge, a position which continues into what has become known as ‘hard SF’. The research article is completely based on advancement of science and its effects.

scholarly journals Stochastic Fuzzy Algorithms for Impairment of Assets Management

2020 ◽  
Vol 15 (1) ◽  
Author(s):  
Marcel Ioan Bolos ◽  
Victoria Bogdan ◽  
Ioana Alexandra Bradea ◽  
Claudia Diana Sabau Popa ◽  
Dorina Nicoleta Popa
Keyword(s):  
Artificial Intelligence ◽  
Decision Making ◽  
Fuzzy Numbers ◽  
Cash Flows ◽  
The Other ◽  
Dual Purpose ◽  
Fuzzy Algorithms ◽  
Tangible Assets ◽  
The Impact

The present paper aims to analyze the impairment of tangible assets with the help of artificial intelligence. Stochastic fuzzy numbers have been introduced with a dual purpose: on one hand to estimate the cash flows generated by tangible assets exploitation and, on the other hand, to ensure the value ranges stratifications that define these cash flows. Estimation of cash flows using stochastic fuzzy numbers was based on cash flows generated by tangible assets in previous periods of operation. Also, based on the Lagrange multipliers, were introduced: the objective function of minimizing the standard deviations from the recorded value of the cash flows generated by the tangible assets, as well as the constraints caused by the impairment of tangible assets identification according to which the cash flows values must be equal to the annual value of the invested capital. Within the determination of the impairment value and stratification of the value ranges determined by the cash flows using stochastic fuzzy numbers, the impairment of assets risk was identified. Information provided by impairment of assets but also the impairment risks, is the basis of the decision-making measures taken to mitigate the impact of accumulated impairment losses on company’s financial performance.

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