Improved Measures of Integrated Information

Although there is growing interest in measuring integrated information in computational and cognitive systems, current methods for doing so in practice are computationally unfeasible. Existing and novel integration measures are investigated and classified by various desirable properties. A simple taxonomy of Φ-measures is presented where they are each characterized by their choice of factorization method (5 options), choice of probability distributions to compare (3 × 4 options) and choice of measure for comparing probability distributions (7 options). When requiring the Φ-measures to satisfy a minimum of attractive properties, these hundreds of options reduce to a mere handful, some of which turn out to be identical. Useful exact and approximate formulas are derived that can be applied to real-world data from laboratory experiments without posing unreasonable computational demands.United States. Army Research Office (Grant W911NF-15-1-0300

Semantic Image Retrieval via Active Grounding of Visual Situations

We describe a novel architecture for semantic image retrieval---in particular, retrieval of instances of visual situations. Visual situations are concepts such as "a boxing match," "walking the dog," "a crowd waiting for a bus," or "a game of ping-pong," whose instantiations in images are linked more by their common spatial and semantic structure than by low-level visual similarity. Given a query situation description, our architecture---called Situate---learns models capturing the visual features of expected objects as well the expected spatial configuration of relationships among objects. Given a new image, Situate uses these models in an attempt to ground (i.e., to create a bounding box locating) each expected component of the situation in the image via an active search procedure. Situate uses the resulting grounding to compute a score indicating the degree to which the new image is judged to contain an instance of the situation. Such scores can be used to rank images in a collection as part of a retrieval system. In the preliminary study described here, we demonstrate the promise of this system by comparing Situate's performance with that of two baseline methods, as well as with a related semantic image-retrieval system based on "scene graphs.

"This is not 13th Grade": Making the Transition to College through Coding

The Summer Coding Academy 2017 at the University of the Incarnate Word (UIW) was designed for the first-year freshman and transfer students with a declared Science, Technology, Engineering and Mathematics (STEM) major. The camp participants were from diverse STEM fields that included engineering, biochemistry, nuclear medicine science, biology, computer information systems, meteorology, and 3-D animation & game design. The objectives of the camp were (1) to improve the student’s preparation for a rigorous STEM degree, (2) to increase their skills in communication and data analytics through coding and robotics. This paper describes the teaching materials that we utilized, the results of students evaluations, lessons learned and the future work.Cockrell School of Engineerin

Effects of MiFID II: Corporate Governance as a Mitigating Factor for Sell-Side Analysts Coverage

Mestrado Bolonha em FinançasEste artigo analisa se a governança corporativa tem um efeito atenuante para a decisão dos analistas sell-side de seguir uma empresa após a implementação da Diretiva de Mercados em Instrumentos Financeiros (MiFID II). Estudos anteriores descobriram que a nova legislação diminuiu o número de analistas que seguem empresas cotadas de menor dimensão com menor participação de investidores institucionais. Este efeito levou a participantes no mercado de capitais argumentarem que a assimetria de informação aumentou como efeito da MiFID II. Este estudo analisa se é possível testar esta hipótese através do recurso a métodos quantitativos, cobrindo observações antes e depois da implementação da MiFID II. A hipótese testada é que os analistas tendem a seguir empresas com maior nível agregado de governança corporativa e que sua tendência aumentou após a implementação da MiFID II. Os resultados mostram que o nível agregado de governança corporativa tornou-se num fator menos importante após a implementação da MiFID II, considerando o número de analistas que seguem uma empresa. Os resultados também mostram que o nível agregado de governança corporativa está positivamente associado à diminuição da cobertura dos analistas após a MiFID II. Este estudo conclui que podem haver outros fatores a serem considerados pelos analistas após a introdução da MiFID II. O período em análise é relativamente curto, uma vez que MiFID II foi implementado em 2018, pelo que o efeito total da introdução da Diretiva pode ainda não ter sido capturado.This paper will investigate if corporate governance has a mitigating effect for Sell-side analysts’ decision to follow a firm after the implementation of Markets in Financial Instruments Directive (MiFID II). Previous studies have found that the new legislation decreased the number of analysts following smaller publicly traded firms with lower institutional holdings. This raised concerns from actors on the financial market which argued that the information asymmetry increased as an effect of MiFID II. This study investigates if it is possible to prove this uses a quantitative method with observations ranging before and after the implementation of MiFID II. The hypothesis tested is that analysts tend to follow firms with a higher aggregated level of corporate governance and that his tendency increased after MiFID II. The examination shows that the aggregated level of corporate governance became a less important factor after MiFID II for the number of analysts that follow a firm. Results also show that the aggregated level of corporate governance is positively associated with the decrease of analyst firm coverage after MiFID II. The conclusions drawn is that there might be other factors that became more important than corporate governance after MiFID II when analysts decide to follow a firm. The period used is also relatively short since MiFID II was implemented in 2018 and the full effect might not have been captured.info:eu-repo/semantics/publishedVersio

Information Technology Innovation Spirals in Cross-Cultural Collaboration: A Case of Software Localization in Africa

There is little doubt that IT innovation can be a driving force for economic growth. Economic theories promote the notion of innovation adoption, in which technological slipover from technologically advanced countries advance growth in less technologically advanced countries. The ability to adopt these technologies is often reliant on previous experience and knowledge. Thus capacity building has been proposed as a central driver to enable the adoption of IT innovation. However, the adoption of innovation and capacity building are subject to significant barriers, which are particular to the context. By viewing IT innovation as a process where IT gets adopted, diffused and assimilated into the organization, we present a conceptual framework that fosters innovation through collaborative innovation spirals. The framework is developed through the analysis of a case study conducted in Ethiopia. The resulting framework presents researchers and practitioners with a potential tool for cross-cultural innovation

Challenges in Knowledge Management

Knowledge management is an ever researched area in the discipline of information systems. Though the terminology might change with the waves of fashion, how information systems can support the multiple dimensions of knowledge management is an underlying theme in many streams of research. This article examines literature on knowledge management in order to synthesize a number of key challenges, which emerge from a multidimensional and boundary-spanning view on knowledge management. Six interrelated issues attempt to explain some of the essential aspects of knowledge in the organizational context: these issues are (1) standardization of processes, structures, and systems, (2) contextualization, (3) invasiveness in natural ways of working, (4) strategic alignment, (5) intelligence, and (6) cultural environment

Research Priorities for Robust and Beneficial Artificial Intelligence

Artificial intelligence (AI) research has explored a variety of problems and approaches since its inception, but for the last 20 years or so has been focused on the problems surrounding the construction of intelligent agents —systems that perceive and act in some environment. In this context, the criterion for intelligence is related to statistical and economic notions of rationality — colloquially, the ability to make good decisions, plans, or inferences. The adoption of probabilistic representations and statistical learning methods has led to a large degree of integration and cross-fertilization between AI, machine learning, statistics, control theory, neuroscience, and other fields. The establishment of shared theoretical frameworks, combined with the availability of data and processing power, has yielded remarkable suc- cesses in various component tasks such as speech recognition, image classification, autonomous vehicles, machine translation, legged locomotion, and question-answering systems

Afghanistan: Final Assessment Report

In December 2005 the European Commission (EC) performed an Assessment Mission with the overall objective of assisting the EC in designing its strategy to support the government of Afghanistan in implementing its Mine Action and Ammunition Stockpile Destruction programmes. The objective of the mission was to sketch out a strategy for landmine and ammunition stockpile destruction and contribute to its implementation

Coordinate Independent Convolutional Networks -- Isometry and Gauge Equivariant Convolutions on Riemannian Manifolds

Motivated by the vast success of deep convolutional networks, there is a great interest in generalizing convolutions to non-Euclidean manifolds. A major complication in comparison to flat spaces is that it is unclear in which alignment a convolution kernel should be applied on a manifold. The underlying reason for this ambiguity is that general manifolds do not come with a canonical choice of reference frames (gauge). Kernels and features therefore have to be expressed relative to arbitrary coordinates. We argue that the particular choice of coordinatization should not affect a network's inference -- it should be coordinate independent. A simultaneous demand for coordinate independence and weight sharing is shown to result in a requirement on the network to be equivariant under local gauge transformations (changes of local reference frames). The ambiguity of reference frames depends thereby on the G-structure of the manifold, such that the necessary level of gauge equivariance is prescribed by the corresponding structure group G. Coordinate independent convolutions are proven to be equivariant w.r.t. those isometries that are symmetries of the G-structure. The resulting theory is formulated in a coordinate free fashion in terms of fiber bundles. To exemplify the design of coordinate independent convolutions, we implement a convolutional network on the M\"obius strip. The generality of our differential geometric formulation of convolutional networks is demonstrated by an extensive literature review which explains a large number of Euclidean CNNs, spherical CNNs and CNNs on general surfaces as specific instances of coordinate independent convolutions.Comment: The implementation of orientation independent M\"obius convolutions is publicly available at https://github.com/mauriceweiler/MobiusCNN