A Variety Metric Accounting for Unbalanced Idea Space Distributions

AbstractProving the effectiveness of an idea generation method is key to its acceptance in an industrial and academic environment. This necessitates the development of a set of widely accepted metrics covering the different aspects on which idea generation methods can be characterized. This paper gives an overview of the existing metrics, and demonstrates a number of shortcomings in the variety metric, such as not accounting for the fairness of the distribution of ideas over nodes on an abstraction level. A level-based, correctly normalized variety metric, based on the Shannon entropy, is proposed which is shown to resolve the identified issues

The nature and evaluation of commercial expert system building tools, revision 1

This memorandum reviews the factors that constitute an Expert System Building Tool (ESBT) and evaluates current tools in terms of these factors. Evaluation of these tools is based on their structure and their alternative forms of knowledge representation, inference mechanisms and developer end-user interfaces. Next, functional capabilities, such as diagnosis and design, are related to alternative forms of mechanization. The characteristics and capabilities of existing commercial tools are then reviewed in terms of these criteria

A Comprehensive Review of Congestion Management in Power System

In recent decades, restructuring has cut across all probable domains, involving the power supply industry. The restructuring has brought about considerable changes whereby electricity is now a commodity and has become a deregulated one. These competitive markets have paved the way for countless entrants. This has caused overload and congestion on transmission lines. In addition, the open access transmission network has created a more intensified congestion issue. Therefore, congestion management on power systems is relevant and central significance to the power industry. This manuscript review few congestion management techniques, consists of Reprogramming Generation (GR), Load Shedding, Optimal Distributed Generation (DG) Location, Nodal Pricing, Free Methods, Genetic Algorithm (GA), Particle Swarm Optimization (PSO), Fuzzy Logic System Method, as well as Additional Renewable Energy Sources. In this manuscript a review work is performed to unite the entire publications on congestion management

A Comprehensive Review of Congestion Management in Power System

In recent decades, restructuring has cut across all probable domains, involving the power supply industry. The restructuring has brought about considerable changes whereby electricity is now a commodity and has become a deregulated one. These competitive markets have paved the way for countless entrants. This has caused overload and congestion on transmission lines. In addition, the open access transmission network has created a more intensified congestion issue. Therefore, congestion management on power systems is relevant and central significance to the power industry. This manuscript review few congestion management techniques, consists of Reprogramming Generation (GR), Load Shedding, Optimal Distributed Generation (DG) Location, Nodal Pricing, Free Methods, Genetic Algorithm (GA), Particle Swarm Optimization (PSO), Fuzzy Logic System Method, as well as Additional Renewable Energy Sources. In this manuscript a review work is performed to unite the entire publications on congestion management

Hierarchical information clustering by means of topologically embedded graphs

We introduce a graph-theoretic approach to extract clusters and hierarchies in complex data-sets in an unsupervised and deterministic manner, without the use of any prior information. This is achieved by building topologically embedded networks containing the subset of most significant links and analyzing the network structure. For a planar embedding, this method provides both the intra-cluster hierarchy, which describes the way clusters are composed, and the inter-cluster hierarchy which describes how clusters gather together. We discuss performance, robustness and reliability of this method by first investigating several artificial data-sets, finding that it can outperform significantly other established approaches. Then we show that our method can successfully differentiate meaningful clusters and hierarchies in a variety of real data-sets. In particular, we find that the application to gene expression patterns of lymphoma samples uncovers biologically significant groups of genes which play key-roles in diagnosis, prognosis and treatment of some of the most relevant human lymphoid malignancies

Spatial sustainability in cities: organic patterns and sustainable forms

Because the complexity of cities seems to defy description, planners and urban designers have always been forced to work with simplified concepts of the city. Drawn from natural language, these concepts emphasize clear hierarchies, regular geometries and the separation of parts from wholes, all seemingly at variance with the less orderly complexity of most real cities. Such concepts are now dominating the debate about sustainability in cities. Here it is argued that space syntax has now brought to light key underlying structures in the city, which have a direct bearing on sustainability in that they seem to show that the spatial form of the self-organised city, as a foreground network of linked centres at all scales set into a background network of mainly residential space, is already a reflection of the relations between environmental, economic and socio-cultural forces, that is between the three domains of sustainability. Evidence that this is so in all three domains is drawn from recent and new research, and a concept of spatial sustainability is proposed focused on the structure of the primary spatial structure of the city, the street network

Potential on Using Cultural Syndromes for Explaining Differences in Attitudes in Northern and Southern EU Countries

Nowadays, it is more realistic to view the development of a new technology as a result of a complex social system of interactions and decisions. Understanding the public's range of views on biotechnology is important for decision makers, in order to be able to anticipate potential acceptance problems or, one step further, to take consumer or public desires and concerns into account so that desirable applications can be developed. Previous work from the same research group, using data from Eurobarometer surveys, was trying to explore the attitudes of the European consumers towards genetic modification of food. Emerging differences in attitudes towards genetically modified food have not been explained adequately in most cases using only sociodemographic variables. In addition strong national differences lead to the idea that cultural differences should also be taken into account, despite the difficulties in formulating specific hypotheses that can be tested empirically. In this paper, in an effort to approach culture in a more clear way, we try to track down and analyse the specific units (customs, traditions, beliefs, and other social norms) that comprise cultures. The notion of cultural syndromes as approached by Triandis is tackled. Furthermore applying data from the European Social Survey (ESS) to Schwartz's value system, our objective is to validate empirically the potential utilisation of Schwartz values to further explain existing differences in attitudes towards GM food among European countries. Further research can lead to a deeper and more precise understanding of cultural differentiation as well as to a more valid cross-cultural theory of attitude formation.attitudes towards genetically modified food, attitude formation, cultural differentiation, cultural syndromes, Consumer/Household Economics,

Viewfinder: final activity report

The VIEW-FINDER project (2006-2009) is an 'Advanced Robotics' project that seeks to apply a semi-autonomous robotic system to inspect ground safety in the event of a fire. Its primary aim is to gather data (visual and chemical) in order to assist rescue personnel. A base station combines the gathered information with information retrieved from off-site sources. The project addresses key issues related to map building and reconstruction, interfacing local command information with external sources, human-robot interfaces and semi-autonomous robot navigation. The VIEW-FINDER system is a semi-autonomous; the individual robot-sensors operate autonomously within the limits of the task assigned to them, that is, they will autonomously navigate through and inspect an area. Human operators monitor their operations and send high level task requests as well as low level commands through the interface to any nodes in the entire system. The human interface has to ensure the human supervisor and human interveners are provided a reduced but good and relevant overview of the ground and the robots and human rescue workers therein

Dry Port Terminal Location Selection by Applying the Hybrid Grey MCDM Model

Globalization and decentralization of production generate the intensive growth of goods and transport flows, mostly performed by the maritime transport. Ports, as the main nodes in the global logistics networks, are becoming congested, space for their expansion limited, and traffic in their hinterland congested. As a solution to these and many other hinterland-transport-related problems stands out the development of dry port (DP) terminals. Selection of their location is one of the most important strategic decisions on which depends their competitiveness in the market and the functionality of the logistics network. Accordingly, the evaluation and selection of locations for the development of the DP in accordance with the requirements of various stakeholders is performed in this paper, as a prerequisite for the establishment of an ecological, economic, and socially sustainable logistics network in the observed area. To solve this problem, a new hybrid model of multi-criteria decision-making (MCDM) that combines Delphi, AHP (Analytical Hierarchy Process), and CODAS (Combinative Distance-based Assessment) methods in a grey environment is developed. The main contributions of this paper are the defined model, the problem-solving approach based on finding a compromise solution, simultaneous consideration of the environmental, economic, and social sustainability of the DP concept and its implementation in the regional international markets. The applicability of the approach and the defined MCDM model is demonstrated by solving a real-life case study of ranking the potential DP locations in the Western Balkans region. Based on the obtained results, it is concluded that in the current market conditions, it would be most realistic to open three DP terminals, in Zagreb, Ljubljana, and Belgrad

A deep residual architecture for skin lesion segmentation

In this paper, we propose an automatic approach to skin lesion region segmentation based on a deep learning architecture with multi-scale residual connections. The architecture of the proposed model is based on UNet [22] with residual connections to maximise the learning capability and performance of the network. The information lost in the encoder stages due to the max-pooling layer at each level is preserved through the multi-scale residual connections. To corroborate the efficacy of the proposed model, extensive experiments are conducted on the ISIC 2017 challenge dataset without using any external dermatologic image set. An extensive comparative analysis is presented with contemporary methodologies to highlight the promising performance of the proposed methodology