Sum rules and short-range correlations in nuclear matter at finite temperature

The nucleon spectral function in nuclear matter fulfills an energy weighted sum rule. Comparing two different realistic potentials, these sum rules are studied for Greens functions that are derived self-consistently within the T matrix approximation at finite temperature.

Sum rules and correlations in asymmetric nuclear matter

The neutron and proton single-particle spectral functions in asymmetric nuclear matter fulfill energy-weighted sum rules. The validity of these sum rules within the self-consistent Green's function approach is investigated. The various contributions to these sum rules and their convergence as a function of energy provide information about correlations induced by the realistic interaction between the nucleons. The study of the sum rules in asymmetric nuclear matter exhibits the isospin dependence of the nucleon-nucleon correlations.

Pionic branches in neutron matter and the problem of pion condensation

The pion spectrum for charged and neutral pions is investigated in pure neutron matter, by letting the pions interact with a neutron Fermi sea in a self-consistent scheme that renormalizes simultaneously the mesons, considered the source of the interaction, and the nucleons. The possibility of obtaining different kinds of pion condensates is investigated with the result that they cannot be reached even for values of the spin-spin correlation parameter, g', far below the range commonly accepted.

The Fishing Industry in Kerala - Problem and Potentials

importance of fishing and other allied industries in the economy was realised only very recently. Consequently only very few studies are available on the subject. Here an attempt is made to survey the available literature on the subject.

Median Sets and Median Number of a Graph

A profile is a finite sequence of vertices of a graph. The set of all vertices of the graph which minimises the sum of the distances to the vertices of the profile is the median of the profile. Any subset of the vertex set such that it is the median of some profile is called a median set. The number of median sets of a graph is defined to be the median number of the graph. In this paper, we identify the median sets of various classes of graphs such as Kp − e, Kp,q forP > 2, and wheel graph and so forth. The median numbers of these graphs and hypercubes are found out, and an upper bound for the median number of even cycles is established.We also express the median number of a product graph in terms of the median number of their factors.

On the generalized obnoxious center problem: antimedian subsets

The set of vertices that maximize (minimize) the remoteness is the antimedian (median) set of the profile. It is proved that for an arbitrary graph G and S V (G) it can be decided in polynomial time whether S is the antimedian set of some profile. Graphs in which every antimedian set is connected are also considered.

Reinforcement Learning approaches to Economic Dispatch problem

This paper presents Reinforcement Learning (RL) approaches to Economic Dispatch problem. In this paper, formulation of Economic Dispatch as a multi stage decision making problem is carried out, then two variants of RL algorithms are presented. A third algorithm which takes into consideration the transmission losses is also explained. Efficiency and flexibility of the proposed algorithms are demonstrated through different representative systems: a three generator system with given generation cost table, IEEE 30 bus system with quadratic cost functions, 10 generator system having piecewise quadratic cost functions and a 20 generator system considering transmission losses. A comparison of the computation times of different algorithms is also carried out.

Reinforcement Learning Solution for Unit Commitment Problem Considering Minimum Start Up and Shut Down Times

Unit Commitment Problem (UCP) in power system refers to the problem of determining the on/ off status of generating units that minimize the operating cost during a given time horizon. Since various system and generation constraints are to be satisfied while finding the optimum schedule, UCP turns to be a constrained optimization problem in power system scheduling. Numerical solutions developed are limited for small systems and heuristic methodologies find difficulty in handling stochastic cost functions associated with practical systems. This paper models Unit Commitment as a multi stage decision making task and an efficient Reinforcement Learning solution is formulated considering minimum up time /down time constraints. The correctness and efficiency of the developed solutions are verified for standard test systems

Reinforcement Learning solution for Unit Commitment Problem through pursuit method

Unit commitment is an optimization task in electric power generation control sector. It involves scheduling the ON/OFF status of the generating units to meet the load demand with minimum generation cost satisfying the different constraints existing in the system. Numerical solutions developed are limited for small systems and heuristic methodologies find difficulty in handling stochastic cost functions associated with practical systems. This paper models Unit Commitment as a multi stage decision task and Reinforcement Learning solution is formulated through one efficient exploration strategy: Pursuit method. The correctness and efficiency of the developed solutions are verified for standard test systems

Testing Isotropy and a related Random Walk problem

One comes across directions as the observations in a number of situations. The first inferential question that one should answer when dealing with such data is, “Are they isotropic or uniformly distributed?” The answer to this question goes back in history which we shall retrace a bit and provide an exact and approximate solution to this so-called “Pearson’s Random Walk” problem.

Employment Realm in Technical Education in Kerala-A Study on the Problem of Unemployment among Engineers

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Konzeption eines generischen Vorgehensmodells zur strategieorientierten und partizipativen Einführung komplexer Softwaresysteme unter Berücksichtigung organisatorischer Gestaltungsprozesse

Die Dissertation befasst sich mit der Einführung komplexer Softwaresysteme, die, bestehend aus einer Kombination aus parametrisierter Standardsoftware gepaart mit Wettbewerbsvorteil sichernden Individualsoftwarekomponenten, keine Software-Engineering-Projekte im klassischen Sinn mehr darstellen, sondern einer strategieorientierten Gestaltung von Geschäftsprozessen und deren Implementierung in Softwaresystemen bedürfen. Die Problemstellung einer adäquaten Abwägung zwischen TCO-optimierender Einführung und einer gleichzeitigen vollständigen Unterstützung der kritischen Erfolgsfaktoren des Unternehmens ist hierbei von besonderer Bedeutung. Der Einsatz integrierter betriebswirtschaftlicher Standardsoftware, mit den Möglichkeiten einer TCO-Senkung, jedoch ebenfalls der Gefahr eines Verlustes von Alleinstellungsmerkmalen am Markt durch Vereinheitlichungstendenzen, stellt ein in Einführungsprojekten wesentliches zu lösendes Problem dar, um Suboptima zu vermeiden. Die Verwendung von Vorgehensmodellen, die sich oftmals an klassischen Softwareentwicklungsprojekten orientieren oder vereinfachte Phasenmodelle für das Projektmanagement darstellen, bedingt eine fehlende Situationsadäquanz in den Detailsituationen der Teilprojekte eines komplexen Einführungsprojektes. Das in dieser Arbeit entwickelte generische Vorgehensmodell zur strategieorientierten und partizipativen Einführung komplexer Softwaresysteme im betriebswirtschaftlichen Anwendungsbereich macht - aufgrund der besonders herausgearbeiteten Ansätze zu einer strategieorientierten Einführung, respektive Entwicklung derartiger Systeme sowie aufgrund der situationsadäquaten Vorgehensstrategien im Rahmen der Teilprojektorganisation � ein Softwareeinführungsprojekt zu einem Wettbewerbsfaktor stärkenden, strategischen Element im Unternehmen. Die in der Dissertation diskutierten Überlegungen lassen eine Vorgehensweise präferieren, die eine enge Verschmelzung des Projektes zur Organisationsoptimierung mit dem Softwareimplementierungsprozess impliziert. Eine Priorisierung der Geschäftsprozesse mit dem Ziel, zum einen bei Prozessen mit hoher wettbewerbsseitiger Priorität ein organisatorisches Suboptimum zu vermeiden und zum anderen trotzdem den organisatorischen Gestaltungs- und den Systemimplementierungsprozess schnell und ressourcenschonend durchzuführen, ist ein wesentliches Ergebnis der Ausarbeitungen. Zusätzlich führt die Ausgrenzung weiterer Prozesse vom Einführungsvorgang zunächst zu einem Produktivsystem, welches das Unternehmen in den wesentlichen Punkten abdeckt, das aber ebenso in späteren Projektschritten zu einem System erweitert werden kann, welches eine umfassende Funktionalität besitzt. Hieraus ergeben sich Möglichkeiten, strategischen Anforderungen an ein modernes Informationssystem, das die kritischen Erfolgsfaktoren eines Unternehmens konsequent unterstützen muss, gerecht zu werden und gleichzeitig ein so weit als möglich ressourcenschonendes, weil die Kostenreduktionsaspekte einer Standardlösung nutzend, Projekt durchzuführen. Ein weiterer wesentlicher Aspekt ist die situationsadäquate Modellinstanziierung, also die projektspezifische Anpassung des Vorgehensmodells sowie die situationsadäquate Wahl der Vorgehensweisen in Teilprojekten und dadurch Nutzung der Vorteile der verschiedenen Vorgehensstrategien beim konkreten Projektmanagement. Der Notwendigkeit der Entwicklung einer Projektorganisation für prototypingorientiertes Vorgehen wird in diesem Zusammenhang ebenfalls Rechnung getragen. Die Notwendigkeit der Unternehmen, sich einerseits mit starken Differenzierungspotenzialen am Markt hervorzuheben und andererseits bei ständig sinkenden Margen einer Kostenoptimierung nachzukommen, lässt auch in Zukunft das entwickelte Modell als erfolgreich erscheinen. Hinzu kommt die Tendenz zu Best-Of-Breed-Ansätzen und komponentenbasierten Systemen im Rahmen der Softwareauswahl, die eine ausgesprochen differenzierte Vorgehensweise in Projekten verstärkt notwendig machen wird. Durch die in das entwickelte Modell integrierten Prototyping-Ansätze wird der auch in Zukunft an Bedeutung gewinnenden Notwendigkeit der Anwenderintegration Rechnung getragen.

Research through DESIGN through research - a problem statement and a conceptual sketch

This paper re-addresses the issue of a lacking genuine design research paradigm. It tries to sketch an operational model of such a paradigm, based upon a generic design process model, which is derived from basic notions of evolution and learning in different domains of knowing (and turns out to be not very different from existing ones). It does not abandon the scientific paradigm but concludes that the latter has to be embedded into / subordinated under a design paradigm.

Approximate Approximations and a Boundary Point Method for the Linearized Stokes System

The method of approximate approximations, introduced by Maz'ya [1], can also be used for the numerical solution of boundary integral equations. In this case, the matrix of the resulting algebraic system to compute an approximate source density depends only on the position of a finite number of boundary points and on the direction of the normal vector in these points (Boundary Point Method). We investigate this approach for the Stokes problem in the whole space and for the Stokes boundary value problem in a bounded convex domain G subset R^2, where the second part consists of three steps: In a first step the unknown potential density is replaced by a linear combination of exponentially decreasing basis functions concentrated near the boundary points. In a second step, integration over the boundary partial G is replaced by integration over the tangents at the boundary points such that even analytical expressions for the potential approximations can be obtained. In a third step, finally, the linear algebraic system is solved to determine an approximate density function and the resulting solution of the Stokes boundary value problem. Even not convergent the method leads to an efficient approximation of the form O(h^2) + epsilon, where epsilon can be chosen arbitrarily small.