ROMANIA IN EU CONTEXT. COMPETITIVENESS AND KNOWLEDGE-BASED ECONOMY

The paper analyses Romania’s competitiveness and knowledge-based economyin an EU comparative context for the 2006-2007 period. The main compared pillar-indices are the following: global competitiveness index;higher education and training; technological readiness; business sophistication; innovation.Each pillar index is disaggregated into several relevant sub indices. Comparisons are madebetween Romania and EU-25, EU-10 (new member states since 2004), Bulgaria and Turkeyon the basis of positions and scores of each country or group of countries, within a totalframework of 131 countries. The size of Romania’s digital divide vis-à-vis EU-25 can beused as a tool for national priority setting and better policies regarding catching up andconvergence processes in digital economy.competitiveness; knowledge-based society; national and international value chains;catching-up; convergence; digital divide; brain drain; knowledge creation, absorption and diffusion.

The Role of Ontologies for Designing Accounting Information Systems

The accounting ontologies were conceptualized as a framework for building accounting information systems in a shared data environment, within enterprises or between different enterprises. The model’s base feature was an object pattern consisting of two mirror-image that represented conceptual the input and output components of a business process. The REA acronym derives from that pattern’s structure, which consisted of economic resources, economic events, and economic agents. The REA model was proposed as a means for an organization to capture the signification of economic exchanges between two business partners. The REA ontology provides an alternative for modelling an enterprise’s economic resources, economic events, economic agents, and their relationships. Resources are considerate organization assets that are able to generate revenue for implicated parties. Events provide a source of detailed data in this approach. Agents participate in events and can affect some resources. They can be an individual or organization inside or outside the organization that is capable of controlling economic resources and interacting with other agents. The objective of this work is to offer an understandable of this framework and to explain how this model can help us via the identification of the afferent concepts.REA ontology, accounting information systems, business process, economic exchange

Romania’s Regional Development in the Economical Reform Process

The scientific basis of regional development strategies implies the most exact possible knowledge of the development level of each region in the field of national development complexity, the mutations that occurred from one period to another. The diversity of activities which take place within villages, regions etc. do not permit their addition only. In this context, their merging into one single synthetic indicator is necessary. We believe that this indicator can be determined starting with the basic principles of information energy. Such a synthetic, aggregated indicator allows the setting of direct connections between certain parts of development, measured by different indicators, as well as their importance, the specific transformations of the quantitative aspects of the development in their qualitative elements. By this approach, the premises of the implied organisms in this field are created, to set the realistic political coordinates of regional development, which are meant to decrease the existent differences between regions and to prevent the appearance of other differences, and to assure as similar as possible working and living conditions for the inhabitants of all regions.banque, divergence de pratiques, changement culturel, entreprise multinationale

The Traceability and Safety of Fishery Products

The paper follows two main objectives: to understand consumers’ perception of safety trasability and quality of fishery products and to identify communication levers in order to improve the perceived image of fishery products. The present research is focused on the fishery products, regardless of their presentation – fresh, frozen or processed. This paper conducted a questionnaire survey of Romanian consumers’ perception toward fishery products. The empirical study with brands indicated that consumers are different awareness to domestic and foreign safety fish products. National fishery products got more attention from the consumers

Human Group Activity Recognition based on Modelling Moving Regions Interdependencies

n this research study, we model the interdepen- dency of actions performed by people in a group in order to identify their activity. Unlike single human activity recognition, in interacting groups the local movement activity is usually influenced by the other persons in the group. We propose a model to describe the discriminative characteristics of group activity by considering the relations between motion flows and the locations of moving regions. The inputs of the proposed model are jointly represented in time-space and time-movement spaces. These spaces are modelled using Kernel Density Estimation (KDE) which is then fed into a machine learning classifier. Unlike in other group-based human activity recognition algorithms, the proposed methodology is automatic and does not rely on any pedestrian detection or on the manual annotation of tracks. Index Terms —Group Activity Identification, Motion Segm

Group Activity Recognition on Outdoor Scenes

In this research study, we propose an automatic group activity recognition approach by modelling the interdependencies of group activity features over time. Unlike in simple human activity recognition approaches, the distinguishing characteristics of group activities are often determined by how the movement of people are influenced by one another. We propose to model the group interdependences in both motion and location spaces. These spaces are extended to time-space and time-movement spaces and modelled us- ing Kernel Density Estimation (KDE). Such representations are then fed into a machine learning classifier which iden- tifies the group activity. Unlike other approaches to group activity recognition, we do not rely on the manual annota- tion of pedestrian tracks from the video sequence

Selection of robust features for the Cover Source Mismatch problem in 3D steganalysis

This paper introduces a novel method for extracting sets of feature from 3D objects characterising a robust stegan- alyzer. Specifically, the proposed steganalyzer should mitigate the Cover Source Mismatch (CSM) paradigm. A steganalyzer is considered as a classifier aiming to identify separately cover and stego objects. A steganalyzer behaves as a classifier by considering a set of features extracted from cover stego pairs of 3D objects as inputs during the training stage. However, during the testing stage, the steganalyzer would have to identify whether specific information was hidden in a set of 3D objects which can be different from those used during the training. Addressing the CSM paradigm corresponds to testing the generalization ability of the steganalyzer when introducing distortions in the cover objects before hiding information through steganography. Our method aims to select those 3D features that model best the changes introduced in objects by steganography or information hiding and moreover they are able to generalize for different objects, not present in the training set. The proposed robust steganalysis approach is tested when considering changes in 3D objects such as those produced by mesh simplification and additive noise. The results obtained from this study show that the steganalyzers trained with the selected set of robust features achieve better detection accuracy of the changes embedded in the objects, when compared to other sets of features

Learning Spatio-Temporal Representations with Temporal Squeeze Pooling

In this paper, we propose a new video representation learning method, named Temporal Squeeze (TS) pooling, which can extract the essential movement information from a long sequence of video frames and map it into a set of few images , named Squeezed Images. By embedding the Temporal Squeeze pooling as a layer into off-the-shelf Convolution Neural Networks (CNN), we design a new video classification model, named Temporal Squeeze Network (TeSNet). The resulting Squeezed Images contain the essential movement information from the video frames, corresponding to the optimization of the video classification task. We evaluate our architecture on two video classification benchmarks, and the results achieved are compared to the state-of-the-art

Antifragility Analysis and Measurement Framework for Systems of Systems

The twenty-first century is defined by the social and technical hazards we face. A hazardous situation is a condition, or event, that threatens the well-being of people, organizations, societies, environments, and property. The most extreme of the hazards are considered X-Events and are an exogenous source of extreme stress to a system. X-Events can also be the unintended outputs of a system with both positive (serendipitous) and negative (catastrophic) consequences. Systems can vary in their ability to withstand these stress events. This ability exists on a continuum of fragility that ranges from fragile (degrading with stress), to robust (unchanged by stress), to antifragile (improving with stress). The state of the art does not include a method for analyzing or measuring fragility. Given that what we measure we will improve, the absence of a measurement approach limits the effectiveness of governance in making our systems less fragile and more robust if not antifragile. The authors present an antifragile system simulation model, and propose a framework for analyzing and measuring antifragility based on system of systems concepts. The framework reduces a multidimensional concept of fragility into a two-dimensional continuous interval scale