119,983 research outputs found
Predicting multiple domain queue waiting time via machine learning
This paper describes an implementation of the Cross-Industry Standard Process for Data Mining (CRISP-DM) methodology for a demonstrative case of human queue waiting time prediction. We collaborated with a multiple domain (e.g., bank, pharmacies) ticket management service software development company, aiming to study a Machine Learning (ML) approach to estimate queue waiting time. A large multiple domain database was analyzed, which included millions of records related with two time periods (one year, for the modeling experiments; and two year, for a deployment simulation). The data was first preprocessed (including data cleaning and feature engineering tasks) and then modeled by exploring five state-of-the-art ML regression algorithms and four input attribute selections (including newly engineered features). Furthermore, the ML approaches were compared with the estimation method currently adopted by the analyzed company. The computational experiments assumed two main validation procedures, a standard cross-validation and a Rolling Window scheme. Overall, competitive and quality results were obtained by an Automated ML (AutoML) algorithm fed with newly engineered features. Indeed, the proposed AutoML model produces a small error (from 5 to 7 min), while requiring a reasonable computational effort. Finally, an eXplainable Artificial Intelligence (XAI) approach was applied to a trained AutoML model, demonstrating the extraction of useful explanatory knowledge for this domain.This work has been supported by FCT - Fundação para a CiĂȘncia e Tecnologia within the R &D Units Project Scope: UIDB/00319/2020 and the project âQOMPASS .: Solução de GestĂŁo de Serviços de Atendimento multi-entidade, multi-serviço e multi-idiomaâ within the Project Scope NORTE-01-0247-FEDER-038462
What is Computational Intelligence and where is it going?
What is Computational Intelligence (CI) and what are its relations with Artificial Intelligence (AI)? A brief survey of the scope of CI journals and books with ``computational intelligence'' in their title shows that at present it is an umbrella for three core technologies (neural, fuzzy and evolutionary), their applications, and selected fashionable pattern recognition methods. At present CI has no comprehensive foundations and is more a bag of tricks than a solid branch of science. The change of focus from methods to challenging problems is advocated, with CI defined as a part of computer and engineering sciences devoted to solution of non-algoritmizable problems. In this view AI is a part of CI focused on problems related to higher cognitive functions, while the rest of the CI community works on problems related to perception and control, or lower cognitive functions. Grand challenges on both sides of this spectrum are addressed
Assessing computational thinking process using a multiple evaluation approach
This study explored the ways that the Computational Thinking (CT) process can be evaluated in a classroom environment. Thirty Children aged 10â11 years, from a primary school in London took part in a game-making project using the Scratch and Alice 2.4 applications for eight months. For the focus of this specific paper, data from participant observations, informal conversations, problem-solving sheets, semi-structured interviews and childrenâs completed games were used to make sense of elements of the computational thinking process and approaches to evaluate these elements in a computer game design context. The discussions around what CT consists, highlighted the complex structure of computational thinking and the interaction between the elements of artificial intelligence (AI), computer, cognitive, learning and psychological sciences. This also emphasised the role of metacognition in the Computational Thinking process. These arguments illustrated that it is not possible to evaluate Computational Thinking using only programming constructs, as CT process provides opportunities for developing many other skills and concepts. Therefore a multiple evaluation approach should be adopted to illustrate the full learning scope of the Computational Thinking Process. Using the support of literature review and the findings of the data analysis I proposed a multiple approach evaluation model where âcomputational conceptsâ, âmetacognitive practicesâ, and âlearning behavioursâ were discussed as the main elements of the CT process. Additionally, in order to investigate these dimensions within a game-making context, computer game design was also included in this evaluation model
Post-Westgate SWAT : C4ISTAR Architectural Framework for Autonomous Network Integrated Multifaceted Warfighting Solutions Version 1.0 : A Peer-Reviewed Monograph
Police SWAT teams and Military Special Forces face mounting pressure and
challenges from adversaries that can only be resolved by way of ever more
sophisticated inputs into tactical operations. Lethal Autonomy provides
constrained military/security forces with a viable option, but only if
implementation has got proper empirically supported foundations. Autonomous
weapon systems can be designed and developed to conduct ground, air and naval
operations. This monograph offers some insights into the challenges of
developing legal, reliable and ethical forms of autonomous weapons, that
address the gap between Police or Law Enforcement and Military operations that
is growing exponentially small. National adversaries are today in many
instances hybrid threats, that manifest criminal and military traits, these
often require deployment of hybrid-capability autonomous weapons imbued with
the capability to taken on both Military and/or Security objectives. The
Westgate Terrorist Attack of 21st September 2013 in the Westlands suburb of
Nairobi, Kenya is a very clear manifestation of the hybrid combat scenario that
required military response and police investigations against a fighting cell of
the Somalia based globally networked Al Shabaab terrorist group.Comment: 52 pages, 6 Figures, over 40 references, reviewed by a reade
SameSameButDifferent v.02 â Iceland
The history of computer music is to a great extent the history of algorithmic composition. Here generative approaches are seen as an artistic technique. However, the generation of algorithmic music is normally done in the studio, where the music is aesthetically valued by the composer. The public only gets to know one, or perhaps few, variations of the expressive scope of the algorithmic system itself. In this paper, we describe a generative music system of infinite compositions, where the system itself is aimed for distribution and to be used on personal computers. This system has a dual structure of a compositional score and a performer that performs the score in real-time every time a piece is played. We trace the contextual background of such systems and potential future applications
A Type-coherent, Expressive Representation as an Initial Step to Language Understanding
A growing interest in tasks involving language understanding by the NLP
community has led to the need for effective semantic parsing and inference.
Modern NLP systems use semantic representations that do not quite fulfill the
nuanced needs for language understanding: adequately modeling language
semantics, enabling general inferences, and being accurately recoverable. This
document describes underspecified logical forms (ULF) for Episodic Logic (EL),
which is an initial form for a semantic representation that balances these
needs. ULFs fully resolve the semantic type structure while leaving issues such
as quantifier scope, word sense, and anaphora unresolved; they provide a
starting point for further resolution into EL, and enable certain structural
inferences without further resolution. This document also presents preliminary
results of creating a hand-annotated corpus of ULFs for the purpose of training
a precise ULF parser, showing a three-person pairwise interannotator agreement
of 0.88 on confident annotations. We hypothesize that a divide-and-conquer
approach to semantic parsing starting with derivation of ULFs will lead to
semantic analyses that do justice to subtle aspects of linguistic meaning, and
will enable construction of more accurate semantic parsers.Comment: Accepted for publication at The 13th International Conference on
Computational Semantics (IWCS 2019
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Harnessing agile concepts for the development of intelligent systems
Traditional and current approaches to intelligent systems design, have led to the creation of sophisticated and computationally-intensive packages and environments, for a wide range of applications. This paper proposes methods with which to extend the functionality of such systems, borrowing knowledge management concepts from the field of Agile Manufacturing. As such, this paper proposes that the future of intelligent systems design should be based not only upon the continuing development of artificial intelligence techniques, but also effective methods for harnessing human skills and core competencies to achieve these aims
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