Managing Knowledge in the Electric Power Production Sector

Knowledge management is a topic of increasing involvements in strategic development of the Electric Power Production Sector in Croatia particularly because of the recent emergence of unification and integration of the European Electric Power market. New ways of thinking about management and organization are a key for Croatian participation in the European Union and in an integrated European Power market. Management of knowledge is the most important point of new sustain development towards the appropriate position of Croatian Electric power production sector in the European integration processes. The awareness of importance of processing and managing knowledge is of vast importance as a focus on an application capacity of information science. It is a means to enable establishing hard connections between business activities and the development of information sciences

Dynamic information processing states revealed through neurocognitive models of object semantics.

Recognising objects relies on highly dynamic, interactive brain networks to process multiple aspects of object information. To fully understand how different forms of information about objects are represented and processed in the brain requires a neurocognitive account of visual object recognition that combines a detailed cognitive model of semantic knowledge with a neurobiological model of visual object processing. Here we ask how specific cognitive factors are instantiated in our mental processes and how they dynamically evolve over time. We suggest that coarse semantic information, based on generic shared semantic knowledge, is rapidly extracted from visual inputs and is sufficient to drive rapid category decisions. Subsequent recurrent neural activity between the anterior temporal lobe and posterior fusiform supports the formation of object-specific semantic representations - a conjunctive process primarily driven by the perirhinal cortex. These object-specific representations require the integration of shared and distinguishing object properties and support the unique recognition of objects. We conclude that a valuable way of understanding the cognitive activity of the brain is though testing the relationship between specific cognitive measures and dynamic neural activity. This kind of approach allows us to move towards uncovering the information processing states of the brain and how they evolve over time.This is the fnal version. It was first published by Taylor and Francis at http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4337742/

District facility managers’ perspectives of mental health information processing and utilisation at primary care level in the Western Cape

District health facility managers play a significant role in provision of primary health care (PHC) services, particularly in integration of mental health services into the PHC level and developing a district health information system, which includes an integrated mental health information system (MHIS). The aim of the study was to explore the views and involvement of district health facility managers in the mental health information processing and utilization in improving mental health service delivery within the context of PHC. The study employed a qualitative research approach. Fourteen facility mangers were recruited using purposive sampling techniques, and interviews were conducted in 2012 and 2013. The interview data were analysed using thematic content analysis. The study identified that mental health information processing systems are fragmented and inadequate for decision making, and it was not known how to use mental health information. Lack of knowledge in information processing and utilization, as well as poor information infrastructure and networking was associated with poor understanding about mental health, not considering mental health as one of the priorities within the district health services, and lack of higher officials’ interest in the mental health development programme. Also notable were the attitudes towards mental illness, which were a major problem. These findings have major implications, such as behavioral /attitudinal risk factors of higher officials, policy makers, and the community for MHIS development and interventions in the reduction of mental health problems in South Africa.Department of HE and Training approved lis

Computational Knowledge Integration in Biopharmaceutical Research

An initiative to increase biopharmaceutical research productivity by capturing, sharing and computationally integrating proprietary scientific discoveries with public knowledge is described. This initiative involves both organisational process change and multiple interoperating software systems. The software components rely on mutually supporting integration techniques. These include a richly structured ontology, statistical analysis of experimental data against stored conclusions, natural language processing of public literature, secure document repositories with lightweight metadata, web services integration, enterprise web portals and relational databases. This approach has already begun to increase scientific productivity in our enterprise by creating an organisational memory (OM) of internal research findings, accessible on the web. Through bringing together these components it has also been possible to construct a very large and expanding repository of biological pathway information linked to this repository of findings which is extremely useful in analysis of DNA microarray data. This repository, in turn, enables our research paradigm to be shifted towards more comprehensive systems-based understandings of drug action

Towards a new approach for enterprise integration : the semantic modeling approach

Manufacturing today has become a matter of the effective and efficient application of information technology and knowledge engineering. Manufacturing firms’ success depends to a great extent on information technology, which emphasizes the integration of the information systems used by a manufacturing enterprise. This integration is also called enterprise application integration (here the term application means information systems or software systems). The methodology for enterprise application integration, in particular enterprise application integration automation, has been studied for at least a decade; however, no satisfactory solution has been found. Enterprise application integration is becoming even more difficult due to the explosive growth of various information systems as a result of ever increasing competition in the software market. This thesis aims to provide a novel solution to enterprise application integration. The semantic data model concept that evolved in database technology is revisited and applied to enterprise application integration. This has led to two novel ideas developed in this thesis. First, an ontology of an enterprise with five levels (following the data abstraction: generalization/specialization) is proposed and represented using unified modeling language. Second, both the ontology for the enterprise functions and the ontology for the enterprise applications are modeled to allow automatic processing of information back and forth between these two domains. The approach with these novel ideas is called the enterprise semantic model approach. The thesis presents a detailed description of the enterprise semantic model approach, including the fundamental rationale behind the enterprise semantic model, the ontology of enterprises with levels, and a systematic way towards the construction of a particular enterprise semantic model for a company. A case study is provided to illustrate how the approach works and to show the high potential of solving the existing problems within enterprise application integration

Text mining and natural language processing for the early stages of space mission design

Final thesis submitted December 2021 - degree awarded in 2022A considerable amount of data related to space mission design has been accumulated since artificial satellites started to venture into space in the 1950s. This data has today become an overwhelming volume of information, triggering a significant knowledge reuse bottleneck at the early stages of space mission design. Meanwhile, virtual assistants, text mining and Natural Language Processing techniques have become pervasive to our daily life. The work presented in this thesis is one of the first attempts to bridge the gap between the worlds of space systems engineering and text mining. Several novel models are thus developed and implemented here, targeting the structuring of accumulated data through an ontology, but also tasks commonly performed by systems engineers such as requirement management and heritage analysis. A first collection of documents related to space systems is gathered for the training of these methods. Eventually, this work aims to pave the way towards the development of a Design Engineering Assistant (DEA) for the early stages of space mission design. It is also hoped that this work will actively contribute to the integration of text mining and Natural Language Processing methods in the field of space mission design, enhancing current design processes.A considerable amount of data related to space mission design has been accumulated since artificial satellites started to venture into space in the 1950s. This data has today become an overwhelming volume of information, triggering a significant knowledge reuse bottleneck at the early stages of space mission design. Meanwhile, virtual assistants, text mining and Natural Language Processing techniques have become pervasive to our daily life. The work presented in this thesis is one of the first attempts to bridge the gap between the worlds of space systems engineering and text mining. Several novel models are thus developed and implemented here, targeting the structuring of accumulated data through an ontology, but also tasks commonly performed by systems engineers such as requirement management and heritage analysis. A first collection of documents related to space systems is gathered for the training of these methods. Eventually, this work aims to pave the way towards the development of a Design Engineering Assistant (DEA) for the early stages of space mission design. It is also hoped that this work will actively contribute to the integration of text mining and Natural Language Processing methods in the field of space mission design, enhancing current design processes

Digital Libraries and Portals Saving National Cultural Heritage (IMI–BAS Experience)

The current research activities of the Institute of Mathematics and Informatics at the Bulgarian Academy of Sciences (IMI—BAS) include the study and application of knowledge-based methods for the creation, integration and development of multimedia digital libraries with applications in cultural heritage. This report presents IMI-BAS’s developments at the digital library management systems and portals, i.e. the Bulgarian Iconographical Digital Library, the Bulgarian Folklore Digital Library and the Bulgarian Folklore Artery, etc. developed during the several national and international projects: - "Digital Libraries with Multimedia Content and its Application in Bulgarian Cultural Heritage" (contract 8/21.07.2005 between the IMI–BAS, and the State Agency for Information Technologies and Communications; - FP6/IST/P-027451 PROJECT LOGOS "Knowledge-on-Demand for Ubiquitous Learning", EU FP6, IST, Priority 2.4.13 "Strengthening the Integration of the ICT research effort in an Enlarged Europe" - NSF project D-002-189 SINUS "Semantic Technologies for Web Services and Technology Enhanced Learning". - NSF project IO-03-03/2006 ―Development of Digital Libraries and Information Portal with Virtual Exposition "Bulgarian Folklore Heritage". The presented prototypes aims to provide flexible and effective access to the multimedia presentation of the cultural heritage artefacts and collections, maintaining different forms and format of the digitized information content and rich functionality for interaction. The developments are a result of long- standing interests and work in the technological developments in information systems, knowledge processing and content management systems. The current research activities aims at creating innovative solutions for assembling multimedia digital libraries for collaborative use in specific cultural heritage context, maintaining their semantic interoperability and creating new services for dynamic aggregation of their resources, access improvement, personification, intelligent curation of content, and content protection. The investigations are directed towards the development of distributed tools for aggregating heterogeneous content and ensuring semantic compatibility with the European digital library EUROPEANA, thus providing possibilities for pan- European access to rich digitalised collections of Bulgarian cultural heritage

Integration of Neuroimaging and Microarray Datasets through Mapping and Model-Theoretic Semantic Decomposition of Unstructured Phenotypes

An approach towards heterogeneous neuroscience dataset integration is proposed that uses Natural Language Processing (NLP) and a knowledge-based phenotype organizer system (PhenOS) to link ontology-anchored terms to underlying data from each database, and then maps these terms based on a computable model of disease (SNOMED CT®). The approach was implemented using sample datasets from fMRIDC, GEO, The Whole Brain Atlas and Neuronames, and allowed for complex queries such as “List all disorders with a finding site of brain region X, and then find the semantically related references in all participating databases based on the ontological model of the disease or its anatomical and morphological attributes”. Precision of the NLP-derived coding of the unstructured phenotypes in each dataset was 88% (n = 50), and precision of the semantic mapping between these terms across datasets was 98% (n = 100). To our knowledge, this is the first example of the use of both semantic decomposition of disease relationships and hierarchical information found in ontologies to integrate heterogeneous phenotypes across clinical and molecular datasets

Neural alpha oscillations index the balance between self-other integration and segregation in real-time joint action

Shared knowledge and interpersonal coordination are prerequisites for most forms of social behavior. Influential approaches to joint action have conceptualized these capacities in relation to the separate constructs of co-representation (knowledge) and self-other entrainment (coordination). Here we investigated how brain mechanisms involved in co-representation and entrainment interact to support joint action. To do so, we used a musical joint action paradigm to show that the neural mechanisms underlying co-representation and self-other entrainment are linked via a process – indexed by EEG alpha oscillations – regulating the balance between self-other integration and segregation in real time. Pairs of pianists performed short musical items while action familiarity and interpersonal (behavioral) synchronization accuracy were manipulated in a factorial design. Action familiarity referred to whether or not pianists had rehearsed the musical material performed by the other beforehand. Interpersonal synchronization was manipulated via congruent or incongruent tempo change instructions that biased performance timing towards the impending, new tempo. It was observed that, when pianists were familiar with each other's parts, millisecond variations in interpersonal synchronized behavior were associated with a modulation of alpha power over right centro-parietal scalp regions. Specifically, high behavioral entrainment was associated with self-other integration, as indexed by alpha suppression. Conversely, low behavioral entrainment encouraged reliance on internal knowledge and thus led to self-other segregation, indexed by alpha enhancement. These findings suggest that alpha oscillations index the processing of information about self and other depending on the compatibility of internal knowledge and external (environmental) events at finely resolved timescales