Knowledge Agents Represented by Knowledge Functions

Knowledge as the basis of science has up to now only verbally defined features which are not accepted between all sciences. On the other hand knowledge must have some interoperable, physical related features since otherwise we wouldn’t be able to exchange knowledge between humans. With the discovery of operable features knowledge becomes, like information, a tool for interdisciplinary use. It is analysed how this discovery can also contribute to the concept of economic agents. The fundamental frame for agent concepts is set by physical condi-tions, which are explained. It is shown how within this frame operable knowledge can act in a way that new economic features appear. Operable knowledge features present a structure of knowledge which is independent of the specific meaning or use of knowledge. This discovery presents a completely new mathematically based concept of knowledge for different disciplines like economy, sociology, communication science, physics or biology. It is explained how this arises by extending the well known Shannon concept of information. It is shown how competence and innovation appear as specific features of knowledge. Also it is explained how knowledge adds value to money. Some initial practical results of a pilot project in a company are discussed. Hints for application in different disciplines are given.bit of knowledge, measure of knowledge, knowledge functions of agents, quantization of knowledge

An under-Sampled Approach for Handling Skewed Data Distribution using Cluster Disjuncts

In Data mining and Knowledge Discovery hidden and valuable knowledge from the data sources is discovered. The traditional algorithms used for knowledge discovery are bottle necked due to wide range of data sources availability. Class imbalance is a one of the problem arises due to data source which provide unequal class i.e. examples of one class in a training data set vastly outnumber examples of the other class(es). Researchers have rigorously studied several techniques to alleviate the problem of class imbalance, including resampling algorithms, and feature selection approaches to this problem. In this paper, we present a new hybrid frame work dubbed as Majority Under-sampling based on Cluster Disjunct (MAJOR_CD) for learning from skewed training data. This algorithm provides a simpler and faster alternative by using cluster disjunct concept. We conduct experiments using twelve UCI data sets from various application domains using five algorithms for comparison on six evaluation metrics. The empirical study suggests that MAJOR_CD have been believed to be effective in addressing the class imbalance problem

Μοντέλο λειτουργίας των Ακαδημαϊκών Βιβλιοθηκών ως φορέων εξ αποστάσεως εκπαίδευσης : εικονικά περιβαλλοντα στην υπηρεσία των χρηστών-εκπαιδευομένων

The transformation of collections of traditional academic library in digital or simulated placed the librarian front new occasions and challenges. The internet and specifically the world web lent in the librarian a new role in the management of information with better and more suitable ways. Because his dynamic characteristics as the division, the heterogeneity, the collaboration and architecture, the web brought revolutionary changes in the information access opening new prospects as the academic pictorial libraries that they help in the more effective recuperation and diffusion of knowledge. How would be supposed the academic libraries to see their future in the discovery of information and knowledge services? In the place of existing limited frame that forces the users to visit various scattered sources, the libraries will provide a simulated service of alter-activity with incomparable content and broadness in each type and form of familiar academic content. The academic libraries in this collaborative frame contribute decisive in the creation of open network of distance learning that will offer a alternative solution in the running lists of search engines. This statement presents a model that it helps in the benefit of distance learning in real time in removed users via the facilitations of simulated environment

Polar Cyclone Identification from 4D Climate Data in a Knowledge-Driven Visualization System

abstract: Arctic cyclone activity has a significant association with Arctic warming and Arctic ice decline. Cyclones in the North Pole are more complex and less developed than those in tropical regions. Identifying polar cyclones proves to be a task of greater complexity. To tackle this challenge, a new method which utilizes pressure level data and velocity field is proposed to improve the identification accuracy. In addition, the dynamic, simulative cyclone visualized with a 4D (four-dimensional) wind field further validated the identification result. A knowledge-driven system is eventually constructed for visualizing and analyzing an atmospheric phenomenon (cyclone) in the North Pole. The cyclone is simulated with WebGL on in a web environment using particle tracing. To achieve interactive frame rates, the graphics processing unit (GPU) is used to accelerate the process of particle advection. It is concluded with the experimental results that: (1) the cyclone identification accuracy of the proposed method is 95.6% when compared with the NCEP/NCAR (National Centers for Environmental Prediction/National Center for Atmospheric Research) reanalysis data; (2) the integrated knowledge-driven visualization system allows for streaming and rendering of millions of particles with an interactive frame rate to support knowledge discovery in the complex climate system of the Arctic region

Semantic-driven matchmaking of web services using case-based reasoning

With the rapid proliferation of Web services as the medium of choice to securely publish application services beyond the firewall, the importance of accurate, yet flexible matchmaking of similar services gains importance both for the human user and for dynamic composition engines. In this paper, we present a novel approach that utilizes the case based reasoning methodology for modelling dynamic Web service discovery and matchmaking. Our framework considers Web services execution experiences in the decision making process and is highly adaptable to the service requester constraints. The framework also utilises OWL semantic descriptions extensively for implementing both the components of the CBR engine and the matchmaking profile of the Web services

The Environments of Short-Duration Gamma-Ray Bursts and Implications for their Progenitors

[Abridged] The study of short-duration gamma-ray bursts (GRBs) experienced a complete revolution in recent years thanks to the discovery of the first afterglows and host galaxies in May 2005. These observations demonstrated that short GRBs are cosmological in origin, reside in both star forming and elliptical galaxies, are not associated with supernovae, and span a wide isotropic-equivalent energy range of ~10^48-10^52 erg. However, a fundamental question remains unanswered: What are the progenitors of short GRBs? The most popular theoretical model invokes the coalescence of compact object binaries with neutron star and/or black hole constituents. However, additional possibilities exist, including magnetars formed through prompt channels (massive star core-collapse) and delayed channels (binary white dwarf mergers, white dwarf accretion-induced collapse), or accretion-induced collapse of neutron stars. In this review I summarize our current knowledge of the galactic and sub-galactic environments of short GRBs, and use these observations to draw inferences about the progenitor population. The most crucial results are: (i) some short GRBs explode in dead elliptical galaxies; (ii) the majority of short GRBs occur in star forming galaxies; (iii) the star forming hosts of short GRBs are distinct from those of long GRBs (lower star formation rates, and higher luminosities and metallicities), and instead appear to be drawn from the general field galaxy population; (iv) the physical offsets of short GRBs relative to their host galaxy centers are significantly larger than for long GRBs; (v) the observed offset distribution is in good agreement with predictions for NS-NS binary mergers; and (vi) short GRBs trace under-luminous locations within their hosts, but appear to be more closely correlated with the rest-frame optical light (old stars) than the UV light (young massive stars).Comment: Solicited review in New Astronomy Reviews; accepted version; 24 pages, 23 figures; version with full resolution figures available from https://www.cfa.harvard.edu/~eberger/eberger_shb_nar.pd

On the hopping pattern design for D2D discovery with invariant

In this paper, we focus on the hopping pattern design for device-to-device (D2D) discovery. The requirements of hopping pattern is discussed, where the impact of specific system constraints, e.g., frequency hopping, is also taken into consideration. Specifically speaking, we discover and utilize the novel feature of resource hopping, i.e., "hopping invariant" to design four new hopping patterns and analyze their performance. The hopping invariant can be used to deliver information for specific users without extra radio resources, and due to the connection between hopping invariant and resource location, receiver complexity can be significantly reduced. Furthermore, our schemes are designed to be independent of discovery frame number, which makes them more suitable to be implemented in practical systems