Entorno bogotano de negocios 2006

Gestión del conocimiento

A Multi-Objective Genetic Algorithm with Side Effect Machines for Motif Discovery

Understanding the machinery of gene regulation to control gene expression has been one of the main focuses of bioinformaticians for years. We use a multi-objective genetic algorithm to evolve a specialized version of side effect machines for degenerate motif discovery. We compare some suggested objectives for the motifs they find, test different multi-objective scoring schemes and probabilistic models for the background sequence models and report our results on a synthetic dataset and some biological benchmarking suites. We conclude with a comparison of our algorithm with some widely used motif discovery algorithms in the literature and suggest future directions for research in this area.

Design and Development of data mining models for the predictions of manpower placement in the technical Domain

Data mining is one of the hottest research areas nowadays as it has got wide variety of applications in common man’s life to make the world a better place to live. It is all about finding interesting hidden patterns in a huge history data base. As an example, from a sales data base, one can find an interesting pattern like “people who buy magazines tend to buy news papers also” using data mining. Now in the sales point of view the advantage is that one can place these things together in the shop to increase sales. In this research work, data mining is effectively applied to a domain called placement chance prediction, since taking wise career decision is so crucial for anybody for sure. In India technical manpower analysis is carried out by an organization named National Technical Manpower Information System (NTMIS), established in 1983-84 by India's Ministry of Education & Culture. The NTMIS comprises of a lead centre in the IAMR, New Delhi, and 21 nodal centres located at different parts of the country. The Kerala State Nodal Centre is located at Cochin University of Science and Technology. In Nodal Centre, they collect placement information by sending postal questionnaire to passed out students on a regular basis. From this raw data available in the nodal centre, a history data base was prepared. Each record in this data base includes entrance rank ranges, reservation, Sector, Sex, and a particular engineering. From each such combination of attributes from the history data base of student records, corresponding placement chances is computed and stored in the history data base. From this data, various popular data mining models are built and tested. These models can be used to predict the most suitable branch for a particular new student with one of the above combination of criteria. Also a detailed performance comparison of the various data mining models is done.This research work proposes to use a combination of data mining models namely a hybrid stacking ensemble for better predictions. A strategy to predict the overall absorption rate for various branches as well as the time it takes for all the students of a particular branch to get placed etc are also proposed. Finally, this research work puts forward a new data mining algorithm namely C 4.5 * stat for numeric data sets which has been proved to have competent accuracy over standard benchmarking data sets called UCI data sets. It also proposes an optimization strategy called parameter tuning to improve the standard C 4.5 algorithm. As a summary this research work passes through all four dimensions for a typical data mining research work, namely application to a domain, development of classifier models, optimization and ensemble methods.

A Novel Decision Tree Algorithm for Numeric Datasets - C 4.5*Stat

Decision trees are very powerful tools for classification in data mining tasks that involves different types of attributes. When coming to handling numeric data sets, usually they are converted first to categorical types and then classified using information gain concepts. Information gain is a very popular and useful concept which tells you, whether any benefit occurs after splitting with a given attribute as far as information content is concerned. But this process is computationally intensive for large data sets. Also popular decision tree algorithms like ID3 cannot handle numeric data sets. This paper proposes statistical variance as an alternative to information gain as well as statistical mean to split attributes in completely numerical data sets. The new algorithm has been proved to be competent with respect to its information gain counterpart C4.5 and competent with many existing decision tree algorithms against the standard UCI benchmarking datasets using the ANOVA test in statistics. The specific advantages of this proposed new algorithm are that it avoids the computational overhead of information gain computation for large data sets with many attributes, as well as it avoids the conversion to categorical data from huge numeric data sets which also is a time consuming task. So as a summary, huge numeric datasets can be directly submitted to this algorithm without any attribute mappings or information gain computations. It also blends the two closely related fields statistics and data mining

Gap Analysis For Implementing Tqm In Seafood Exporting Firms

Gap analysis is a very useful tool for firms contemplating adoption of a new system. This paper envisages the use of the gap analysis tool as a precursor for Indian seafood exporting firms to adopt total quality management. Total quality management (TQM) is a management philosophy which strives to put quality at the forefront of all its decision-making, thereby satisfying customers. We therefore recommend that firms adopt the TQM system for better alignment of management goals. The gap analysis tool serves as a roadmap for TQM implementation, by showing the management where they actually are and where they want to be. The main gaps were found to be in the areas of usage of SPC tools (66.7%), benchmarking (65.6%), top management commitment (56.25%) and customer focus (48.1%).

Impact of Quality on Ethics and Social Responsibility in Marketing, in Industries in Kerala in the present Indian Scenario

The paper ‘Impact of Quality on Ethics and Social Responsibility in Marketing in Industries in Kerala in the present Indian scenario’ highlights the observations, based on a descriptive research carried out in five leading industries in Kerala, in the private and public sector. Ethics and social responsibilities, practiced in these industries, are reflected in the results of the survey conducted on specific queries like awareness of products/services provided by them, total understanding of the requirements of the customer, open discussion on technical matters, accountability of employees to the society and social needs, consumer ethics vis a vis business ethics etc. Team working goes a long way, in building relations, which in turn, results in a progressive and effective marketing strategy. This assumes paramount importance, considering the severe competition we are facing in the light of liberalization, privatization and globalization, which encompasses the globe. The prediction of India becoming a lead nation, along with USA, China and Japan, in this decade, can get fructified only if we follow a very high standards of ethics and social responsibility, in all domains including marketing. Organizations like TRW.Rane, Sundaram Fasteners, TVS Motors, in Chennai are a few among others in India, who have achieved the highest distinction in quality viz Deming Prize, and these demonstrate their commitment to quality, society and humanity at large. Cost effectiveness, without jeopardizing quality has become the need of the hour and MRTP has become history. This trait is being brought out through the survey and the results speak for themselves. Unethical practices like switch and bait, not only brings shame to the organization, and country but also results in the company getting wiped out from the market. Adherence to standards like ISO 14000 helps to maintain the minimum level of social responsibility and environmental friendliness. Like quality audit, safety audit etc, social audit is being insisted in all progressive countries to ensure that the organization comply with the minimum statutory requirements. The paper also touches upon Corporate Social Responsibility practiced in the industries and this becomes crystal clear through their commitment to improve the community. Green Marketing lays a lot of importance on the three Rs of environmentalism viz Reduce, Reuse and Recycle. The objective of any business is to achieve optimal profit and this is possible only by reducing the cost as well as waste. In this context, management tools like brainstorming, suggestion schemes, benchmarking etc becomes helpful. These characteristics are brought out through the analysis of survey results. The conclusions drawn throw a lot of information on the desirable practices with respect to Ethics and Social Responsibility in Marketing

Performance Study of an Improved Legendre Moment Descriptor as Region-Based Shape Descriptor

This paper reports a novel region-based shape descriptor based on orthogonal Legendre moments. The preprocessing steps for invariance improvement of the proposed Improved Legendre Moment Descriptor (ILMD) are discussed. The performance of the ILMD is compared to the MPEG-7 approved region shape descriptor, angular radial transformation descriptor (ARTD), and the widely used Zernike moment descriptor (ZMD). Set B of the MPEG-7 CE-1 contour database and all the datasets of the MPEG-7 CE-2 region database were used for experimental validation. The average normalized modified retrieval rate (ANMRR) and precision- recall pair were employed for benchmarking the performance of the candidate descriptors. The ILMD has lower ANMRR values than ARTD for most of the datasets, and ARTD has a lower value compared to ZMD. This indicates that overall performance of the ILMD is better than that of ARTD and ZMD. This result is confirmed by the precision-recall test where ILMD was found to have better precision rates for most of the datasets tested. Besides retrieval accuracy, ILMD is more compact than ARTD and ZMD. The descriptor proposed is useful as a generic shape descriptor for content-based image retrieval (CBIR) applications

Möglichkeiten zur Verbesserung der Effektivität des Handelns von Behörden vor dem Hintergrund der Theorie lernender Organisationen, untersucht am Beispiel der Arbeitsvermittlung in deutschen Optionskommunen

In der vorliegenden Arbeit wird untersucht, ob die Effektivität behördlichen Handelns durch organisationales Lernen gesteigert werden kann und welches Potential dem Organisationslernen für die Verwaltungspraxis innewohnt. Das Organisationslernen wird durch die Erhebung des Vorkommens einzelner Methoden des verwaltungspraktischen Handelns erfasst. Zur quantitativen Erfassung der Effektivität der behördlichen Tätigkeit ist eine behördenspezifische Operationalisierung erforderlich. Für die Untersuchung werden die zur Durchführung des SGB II gebildeten Abteilungen der gegenwärtig 63 Optionskreise ausgewählt. Diese betreiben seit 2005 die bis dahin getrennten Hilfesysteme von Arbeitslosen- und Sozialhilfe zusammengefasst als Grundsicherung für Arbeitsuchende in eigener Zuständigkeit (neben den alternativen Organisationsformen der Arbeitsgemeinschaft und der getrennten Aufgabenträgerschaft). Zur Operationalisierung des behördlichen Handlungsergebnisses der Optionskreise wird die Zahl der Bedarfsgemeinschaften gewählt. Es kann folglich die Hypothese formuliert werden, dass umfangreiches Organisationslernen zu einer beschleunigten Reduzierung der Zahl der Bedarfsgemeinschaften führt. Zur Prüfung dieser Hypothese wurde Anfang 2009 eine schriftliche Vollerhebung bei den 63 Optionskreisen durchgeführt. Die Rücklaufquote der Erhebungsbögen betrug 59%. Der Nutzungsgrad der in der Erhebung berücksichtigten Methoden liegt zwischen 85% (Benchmarking) und 4% (Qualitätsmanagement). Die Erhebungsergebnisse werden bepunktet, um den Nutzungsgrad des Organisationslernens zu operationalisieren. Von den erzielbaren 20 Punkten je Optionskreis werden maximal 12 erreicht (Median: 9 Punkte; geringster Wert: 2 Punkte). Im definierten Zeitraum betrug der Median der Entwicklung der Zahl der Bedarfsgemeinschaften bei den an der Erhebung teilnehmenden Optionskreisen – 16,5% (günstigster Wert: – 27,4%; ungünstigster Wert: +0,4 %). Die Anwendung eines Rangkorrelationskoeffizienten offenbart, dass die Rangfolgen „Grad des Organisationslernens“ und „Entwicklung der Zahl der Bedarfsgemeinschaften“ nicht korrelieren. Insoweit kann die Untersuchungsfrage, ob die Effektivität behördlichen Handelns durch die Nutzung des Organisationslernens gesteigert werden kann, noch nicht abschließend beantwortet werden. Eine Analyse des Ergebnisses zeigt allerdings, dass es trotz der nicht korrelierenden Rangfolgen bestimmte Methoden des Organisationslernens gibt, die mit einer überdurchschnittlich hohen Effektivität in Bezug auf die Entwicklung der Zahl der Bedarfsgemeinschaften einhergehen. Zu dem nach dem Ergebnis der Untersuchung empfehlenswerten Methodenset gehören beispielsweise die Implementierung von Controlling- und Berichtspflichten gegenüber der Gesamtverwaltungsleitung, der Einsatz von Monitoringsystemen und die Gewährleistung einer organisationalen Grundstabilität. Darüber hinaus wird erkennbar, dass die Konkurrenzsituation zwischen Optionskommunen, Arbeitsgemeinschaften und getrennten Aufgabenträgerschaften zu einer insgesamt steigenden Effektivität des behördlichen Handelns führt. Hieraus lassen sich Ansatzpunkte für die Theoriebildung und Modellierung eines „Lizenz-Modells“ zur Erhöhung der Effektivität anderer behördlicher Leistungen entwickeln.

Understanding Subsystems in Biology through Dimensionality Reduction, Graph Partitioning and Analytical Modeling

Biological systems exhibit rich and complex behavior through the orchestrated interplay of a large array of components. It is hypothesized that separable subsystems with some degree of functional autonomy exist; deciphering their independent behavior and functionality would greatly facilitate understanding the system as a whole. Discovering and analyzing such subsystems are hence pivotal problems in the quest to gain a quantitative understanding of complex biological systems. In this work, using approaches from machine learning, physics and graph theory, methods for the identification and analysis of such subsystems were developed. A novel methodology, based on a recent machine learning algorithm known as non-negative matrix factorization (NMF), was developed to discover such subsystems in a set of large-scale gene expression data. This set of subsystems was then used to predict functional relationships between genes, and this approach was shown to score significantly higher than conventional methods when benchmarking them against existing databases. Moreover, a mathematical treatment was developed to treat simple network subsystems based only on their topology (independent of particular parameter values). Application to a problem of experimental interest demonstrated the need for extentions to the conventional model to fully explain the experimental data. Finally, the notion of a subsystem was evaluated from a topological perspective. A number of different protein networks were examined to analyze their topological properties with respect to separability, seeking to find separable subsystems. These networks were shown to exhibit separability in a nonintuitive fashion, while the separable subsystems were of strong biological significance. It was demonstrated that the separability property found was not due to incomplete or biased data, but is likely to reflect biological structure.

MonoGIS, un servidor de mapas para la administración pública

This document explains the map server MonoGIS as an open source project. It includes a benchmarking between other open source map servers

Resum del curs "Aprendre dels millors: construir propostes innovadores per a serveis d’informació a través de l’anàlisi dels millors: taller de casos d’empresa"

Resum del curs "Aprendre dels millors: construir propostes innovadores per a serveis d’informació a través de l’anàlisi dels millors: taller de casos d’empresa", organitzat pel COBDC. Es defineix què és innovació i es posa èmfasi en què s'innova. En aquest marc, s'introdueix el Benchmarking, sobretot a les biblioteques

Productividad del sector ganadero bovino en Colombia durante los años 2000 a 2009

En este trabajo se pretende calcular la productividad del sector ganadero bovino especializado en la producción de carne en Colombia para el periodo comprendido entre el año 2000 y el 2009. Se hace una revisión teórica sobre la productividad y cómo aplica para el sector objeto de estudio. Así mismo, se definen un conjunto de indicadores entre los que se encuentra la tasa de extracción, peso y edad al sacrificio, peso y rendimiento de la canal, capacidad de carga y productividad animal, con el fin de hacer la medición. Al tiempo que se calculan para Colombia, se hace para Argentina y Uruguay, países seleccionados por su liderazgo ganadero a nivel mundial, con el objetivo de hacer un benchmarking de la productividad. Los resultados que se obtuvieron señalan que Argentina es el país más productivo, seguido de Uruguay y Colombia. Sin embargo, los únicos que presentan mejoría en el nivel de productividad son Argentina y Colombia, estando este último muy distante de los demás. Las razones que determinan esta situación son múltiples, y en el trabajo se explican detenidamente. Por último, se presenta una visión de FEDEGAN sobre cómo se puede mejorar la productividad en el país, de tal manera que se puedan alcanzar los objetivos planteados al 2019.

Análisis estructural de la visión estratégica futura internacional de la organización para alcanzar objetivos diferenciales enfocados en contact center: MAPFRE, ANDIASISTENCIA

Por medio del estudio realizado a los diferentes enfoques y estudios hechos hacia el área de recursos humanos y cultura (organizacional y nacional) se han logrado identificar ciertos procesos y características que pueden ser implementados en el modelo de integración de operaciones de Call Center de Mapfre. Partiendo de la cultura organizacional pasando por la cultura nacional y sabiendo como ingresar y ser aceptado en una cultura internacional. Características y procesos totalmente opuestos desde su implementación pasando por sus costos y su posterior gestión; debido al choque cultural y la forma de gestión planteada por la organización basado en su modelo estructural de jerarquización y centralización de toma de decisiones. Queriendo lograr con éste trabajo generar un proyecto de unificación de un sector operativo dirigido hacia servicio al cliente y de la misma manera servir como un ejemplo a demás organizaciones nacionales o multinacionales con el objetivo de aumentar la eficiencia de su administración y la eficiencia de su estructura de costos siempre enfocado a un bien último que es el servicio al cliente.

Plan de empresa : S. R. Contact Center

El presente trabajo de grado esgrime un plan de empresa. S.R. Contact Center es una compañía del sector servicios en Colombia, que como su nombre lo indica se dedica a tercerizar operaciones relacionadas con los centros de contacto. El contenido que encontrará en sus páginas abarca un análisis del sector en el que se encuentra, una revisión a la competencia y el espacio que hay en el mercado para la empresa. Se profundiza en la forma de trabajar, un esquema desvinculado del espacio físico, con alto componente tecnológico y de innovación, que dará nuevas oportunidades de empleo a una población menos favorecida; la empresa se enfocará al minucioso cuidado y aplicación de la información y de sus clientes y usuarios del sistema. También se analiza la viabilidad de la empresa desde el punto de vista jurídico, comercial, financiero y social.

Análisis de los factores de localización de centros de innovación en Colombia. Estudio de caso: configuración de Ruta N en la ciudad de Medellín, a partir de la localización de proyectos estratégicos en el marco de los procesos de competitividad para la ciudad. (2007-2011)

Esta investigación busca analizar los factores de localización urbanos que se convierten en componentes importantes para establecer Parques Tecnológicos en Colombia como estrategia de competitividad y desarrollo territorial. Particularmente se ha enfocado en la configuración del Centro de Innovación Ruta N en la ciudad de Medellín en el marco de los procesos de competitividad para la ciudad durante el periodo 2007-2011.