Small business performance:business, strategy and owner-manager characteristics

Purpose: This paper aims to contribute to the understanding of the factors that influence small to medium-sized enterprise (SME) performance and particularly, growth. Design/methodology/approach: This paper utilises an original data set of 360 SMEs employing 5-249 people to run logit regression models of employment growth, turnover growth and profitability. The models include characteristics of the businesses, the owner-managers and their strategies. Findings: The results suggest that size and age of enterprise dominate performance and are more important than strategy and the entrepreneurial characteristics of the owner. Having a business plan was also found to be important. Research limitations/implications: The results contribute to the development of theoretical and knowledge bases, as well as offering results that will be of interest to research and policy communities. The results are limited to a single survey, using cross-sectional data. Practical implications: The findings have a bearing on business growth strategy for policy makers. The results suggest that policy measures that promote the take-up of business plans and are targeted at younger, larger-sized businesses may have the greatest impact in terms of helping to facilitate business growth. Originality/value: A novel feature of the models is the incorporation of entrepreneurial traits and whether there were any collaborative joint venture arrangements. © Emerald Group Publishing Limited.

Conceptual Information Compression and Efficient Pattern Search

This paper introduces an encoding of knowledge representation statements as regular languages and proposes a two-phase approach to processing of explicitly declared conceptual information. The idea is presented for the simple conceptual graphs where conceptual pattern search is implemented by the so called projection operation. Projection calculations are organised into off-line preprocessing and run-time computations. This enables fast run-time treatment of NP-complete problems, given that the intermediate results of the off-line phase are kept in suitable data structures. The experiments with randomly-generated, middle-size knowledge bases support the claim that the suggested approach radically improves the run-time conceptual pattern search.

Fuzzy Set Theory Approach as the Basis of Analysis of Financial Flows in the Economical Security System

The problems of formalization of the process of matching different management subjects’ functioning characteristics obtained on the financial flows analysis basis is considered. Formal generalizations for gaining economical security system knowledge bases elements are presented. One of feedback directions establishment between knowledge base of the system of economical security and financial flows database analysis is substantiated.

The On-board Operative Advisory Expert Systems for Anthropocentric Object

A class of intelligent systems located on anthropocentric objects that provide a crew with recommendations on the anthropocentric object's rational behavior in typical situations of operation is considered. We refer to this class of intelligent systems as onboard real-time advisory expert systems. Here, we present a formal model of the object domain, procedures for obtaining knowledge about the object domain, and a semantic structure of basic functional units of the onboard real-time advisory expert systems of typical situations. The stages of the development and improvement of knowledge bases for onboard real-time advisory expert systems of typical situations that are important in practice are considered.

Analogical Reasoning Techniques in Intelligent Counterterrorism Systems

The paper develops a set of ideas and techniques supporting analogical reasoning throughout the life-cycle of terrorist acts. Implementation of these ideas and techniques can enhance the intellectual level of computer-based systems for a wide range of personnel dealing with various aspects of the problem of terrorism and its effects. The method combines techniques of structure-sensitive distributed representations in the framework of Associative-Projective Neural Networks, and knowledge obtained through the progress in analogical reasoning, in particular the Structure Mapping Theory. The impact of these analogical reasoning tools on the efforts to minimize the effects of terrorist acts on civilian population is expected by facilitating knowledge acquisition and formation of terrorism-related knowledge bases, as well as supporting the processes of analysis, decision making, and reasoning with those knowledge bases for users at various levels of expertise before, during, and after terrorist acts.

Multilingualism and conceptual modelling

One of the leading motivations behind the multilingual semantic web is to make resources accessible digitally in an online global multilingual context. Consequently, it is fundamental for knowledge bases to find a way to manage multilingualism and thus be equipped with those procedures for its conceptual modelling. In this context, the goal of this paper is to discuss how common-sense knowledge and cultural knowledge are modelled in a multilingual framework. More particularly, multilingualism and conceptual modelling are dealt with from the perspective of FunGramKB, a lexico-conceptual knowledge base for natural language understanding. This project argues for a clear division between the lexical and the conceptual dimensions of knowledge. Moreover, the conceptual layer is organized into three modules, which result from a strong commitment towards capturing semantic knowledge (Ontology), procedural knowledge (Cognicon) and episodic knowledge (Onomasticon). Cultural mismatches are discussed and formally represented at the three conceptual levels of FunGramKB.

Methods, Models & Systems for Dealing with Some Business, Management & Engineering Problems

This keynote presentation will report some of our research work and experience on the development and applications of relevant methods, models, systems and simulation techniques in support of different types and various levels of decision making for business, management and engineering. In particular, the following topics will be covered. Modelling, multi-agent-based simulation and analysis of the allocation management of carbon dioxide emission permits in China (Nanfeng Liu & Shuliang Li Agent-based simulation of the dynamic evolution of enterprise carbon assets (Yin Zeng & Shuliang Li) A framework & system for extracting and representing project knowledge contexts using topic models and dynamic knowledge maps: a big data perspective (Jin Xu, Zheng Li, Shuliang Li & Yanyan Zhang) Open innovation: intelligent model, social media & complex adaptive system simulation (Shuliang Li & Jim Zheng Li) A framework, model and software prototype for modelling and simulation for deshopping behaviour and how companies respond (Shawkat Rahman & Shuliang Li) Integrating multiple agents, simulation, knowledge bases and fuzzy logic for international marketing decision making (Shuliang Li & Jim Zheng Li) A Web-based hybrid intelligent system for combined conventional, digital, mobile, social media and mobile marketing strategy formulation (Shuliang Li & Jim Zheng Li) A hybrid intelligent model for Web & social media dynamics, and evolutionary and adaptive branding (Shuliang Li) A hybrid paradigm for modelling, simulation and analysis of brand virality in social media (Shuliang Li & Jim Zheng Li) Network configuration management: attack paradigms and architectures for computer network survivability (Tero Karvinen & Shuliang Li)

A gestão dos afetos, numa sala de 3 anos, para a construção de valores e competências sociais

Relatório de Estágio apresentado à Escola Superior de Educação de Paula Frassinetti para obtenção do grau de mestre em Educação pré-escolar

Adaptação do paradigma orientado a notificações para desenvolvimento de sistemas fuzzy

This work proposes to adjust the Notification Oriented Paradigm (NOP) so that it provides support to fuzzy concepts. NOP is inspired by elements of imperative and declarative paradigms, seeking to solve some of the drawbacks of both. By decomposing an application into a network of smaller computational entities that are executed only when necessary, NOP eliminates the need to perform unnecessary computations and helps to achieve better logical-causal uncoupling, facilitating code reuse and application distribution over multiple processors or machines. In addition, NOP allows to express the logical-causal knowledge at a high level of abstraction, through rules in IF-THEN format. Fuzzy systems, in turn, perform logical inferences on causal knowledge bases (IF-THEN rules) that can deal with problems involving uncertainty. Since PON uses IF-THEN rules in an alternative way, reducing redundant evaluations and providing better decoupling, this research has been carried out to identify, propose and evaluate the necessary changes to be made on NOP allowing to be used in the development of fuzzy systems. After that, two fully usable materializations were created: a C++ framework, and a complete programming language (LingPONFuzzy) that provide support to fuzzy inference systems. From there study cases have been created and several tests cases were conducted, in order to validate the proposed solution. The test results have shown a significant reduction in the number of rules evaluated in comparison to a fuzzy system developed using conventional tools (frameworks), which could represent an improvement in performance of the applications.

Um modelo para aferir o nível de maturidade na adoção de SOA

Tese (doutorado)—Universidade de Brasília, Faculdade de Tecnologia, Departamento de Engenharia Elétrica, 2015.

Interorganizational Innovation: The Role of Suppliers in Enhancing Buyer Innovation

This dissertation explores the effect of innovative knowledge transfer across supply chain partners. My research seeks to understand the manner by which a firm is able to benefit from the innovative capabilities of its supply chain partners and utilize the external knowledge they hold to increase its own levels of innovation. Specifically, I make use of patent data as a proxy for firm-level innovation and develop both independent and dependent variables from the data contained within the patent filings. I further examine the means by which key dyadic and portfolio supply chain relationship characteristics moderate the relationship between supplier innovation and buyer innovation. I investigate factors such as the degree of transactional reciprocity between the buyer and supplier, the similarity of the firms’ knowledge bases, and specific chain characteristics (e.g., geographic propinquity) to provide greater understanding of the means by which the transfer of innovative knowledge across firms in a supply chain can be enhanced or inhibited. This dissertation spans three essays to provide insights into the role that supply chain relationships play in affecting a focal firm’s level of innovation. While innovation has been at the core of a wide body of research, very little empirical work exists that considers the role of vertical buyer-supplier relationships on a firm’s ability to develop new and novel innovations. I begin by considering the fundamental unit of analysis within a supply chain, the buyer-supplier dyad. After developing initial insights based on the interactions between singular buyers and suppliers, essay two extends the analysis to consider the full spectrum of a buyer’s supply base by aggregating the individual buyer-supplier dyad level data into firm-supply network level data. Through this broader level of analysis, I am able to examine how the relational characteristics between a buyer firm and its supply base affect its ability to leverage the full portfolio of its suppliers’ innovative knowledge. Finally, in essay three I further extend the analysis to explore the means by which a buyer firm can use its suppliers to enhance its ability to access distant knowledge held by other organizations that the buyer is only connected to indirectly through its suppliers.

A NEURAL NET FOR EXTRACTING KNOWLEDGE FROM NATURAL-LANGUAGE DATA-BASES

The present paper introduces a new model of fuzzy neuron, one which increases the computational power of the artificial neuron, turning it also into a symbolic processing device. This model proposes the synapsis to be symbolically and numerically defined, by means of the assignment of tokens to the presynaptic and postsynaptic neurons. The matching or concatenation compatibility between these tokens is used to decided about the possible connections among neurons of a given net. The strength of the compatible synapsis is made dependent on the amount of the available presynaptic and post synaptic tokens. The symbolic and numeric processing capacity of the new fuzzy neuron is used here to build a neural net (JARGON) to disclose the existing knowledge in natural language data bases such as medical files, set of interviews, and reports about engineering operations.

Data bases for the assessment of medical technologies: examples from Europe.

The assessment of medical technologies has to answer several questions ranging from safety and effectiveness to complex economical, social, and health policy issues. The type of data needed to carry out such evaluation depends on the specific questions to be answered, as well as on the stage of development of a technology. Basically two types of data may be distinguished: (a) general demographic, administrative, or financial data which has been collected not specifically for technology assessment; (b) the data collected with respect either to a specific technology or to a disease or medical problem. On the basis of a pilot inquiry in Europe and bibliographic research, the following categories of type (b) data bases have been identified: registries, clinical data bases, banks of factual and bibliographic knowledge, and expert systems. Examples of each category are discussed briefly. The following aims for further research and practical goals are proposed: criteria for the minimal data set required, improvement to the registries and clinical data banks, and development of an international clearinghouse to enhance information diffusion on both existing data bases and available reports on medical technology assessments.

Knowledge of Glasgow coma scale by air-rescue physicians

Rapport de synthèse Introduction : Le Glasgow coma score (GCS) est un outil reconnu permettant l'évaluation des patients après avoir subi un traumatisme crânien. Il est réputé pour sa simplicité et sa reproductibilité permettant ainsi aux soignants une évaluation appropriée et continue du status neurologique des patients. Le GCS est composé de trois catégories évaluant la réponse oculaire, verbale et motrice. En Suisse, les soins préhospitaliers aux patients victimes d'un trauma crânien sévère sont effectués par des médecins, essdntiellement à bord des hélicoptères médicalisés. Avant une anesthésie générale nécessaire à ces patients, une évaluation du GCS est essentielle indiquant au personnel hospitalier la gravité des lésions cérébrales. Afin d'évaluer la connaissance du GCS par les médecins à bord des hélicoptères médicalisés en Suisse, nous avons élaboré un questionnaire, contenant dans une première partie des questions sur les connaissances générales du GCS suivi d'un cas clinique. Objectif : Evaluation des connaissances pratiques et théoriques du GCS par les médecins travaillant à bord des hélicoptères médicalisés en Suisse. Méthode : Etude observationnelle prospective et anonymisée à l'aide d'un questionnaire. Evaluation des connaissances générales du GCS et de son utilisation clinique lors de la présentation d'un cas. Résultats : 16 des 18 bases d'hélicoptères médicalisés suisses ont participé à notre étude. 130 questionnaires ont été envoyés et le taux de réponse a été de 79.2%. Les connaissances théoriques du GCS étaient comparables pour tous les médecins indépendamment de leur niveau de formation. Des erreurs dans l'appréciation du cas clinique étaient présentes chez 36.9% des participants. 27.2% ont commis des erreurs dans le score moteur et 18.5% dans le score verbal. Les erreurs ont été répertoriées le plus fréquemment chez les médecins assistants (47.5%, p=0.09), suivi par les chefs de clinique (31.6%, p=0.67) et les médecins installés en cabinet (18.4%, p=1.00). Les médecins cadres ont fait significativement moins d'erreurs que les autres participants (0%, p<0.05). Aucune différence significative n'à été observée entre les différentes spécialités (anesthésie, médecine interne, médecine général et «autres »). Conclusion Même si les connaissances théoriques du GCS sont adéquates parmi les médecins travaillant à bord des hélicoptères médicalisés, des erreurs dans son application clinique sont présentes dans plus d'un tiers des cas. Les médecins avec le moins d'expériences professionnelle font le plus d'erreurs. Au vu de l'importance de l'évaluation correcte du score de Glasgow initial, une amélioration des connaissances est indispensable.

Generació, actualització y consulta de bases de dades relacionals utilitzant XML (Servei d'emmagatzemament de dades a internet)

El que es vol, en aquest projecte, és generar una sèrie d'eines que permetin a una entitat externa d'interactuar en una base de dades relacional sense necessitat de coneixements específics sobre bases de dades. Quan es diu interactuar, s'hi inclou des de la creació de la base de dades fins a la consulta de la informació, passant per l'actualització d'aquesta base de dades.