Forecasting Intraday Stock Price Trends with Text Mining Techniques

In this paper, we describe NewsCATS (news categorization and trading system), a system implemented to predict stock price trends for the time immediately after the publication of press releases. NewsCATS consists mainly of three components. The first component retrieves relevant information from press releases through the application of text preprocessing techniques. The second component sorts the press releases into predefined categories. Finally, appropriate trading strategies are derived by the third component by means of the earlier categorization. The findings indicate that a categorization of press releases is able to provide additional information that can be used to forecast stock price trends, but that an adequate trading strategy is essential for the results of the categorization to be fully exploited.

PSHARE: Stata module to compute and graph percentile shares

-pshare- computes and graphs percentile shares from individual level data. Percentile shares are often used in inequality research to study the distribution of income or wealth. They are defined as differences between Lorenz ordinates of the outcome variable. Technically, the observations are sorted in increasing order of the outcome variable and the specified percentiles are computed from the running sum of the outcomes. Percentile shares are then computed as differences between percentiles, divided by total outcome. pshare requires moremata to be installed on the system; see ssc describe moremata.

New algorithms for automated phylogenetic reconstruction using artificial intelligence and data mining techniques

Academic and industrial research in the late 90s have brought about an exponential explosion of DNA sequence data. Automated expert systems are being created to help biologists to extract patterns, trends and links from this ever-deepening ocean of information. Two such systems aimed on retrieving and subsequently utilizing phylogenetically relevant information have been developed in this dissertation, the major objective of which was to automate the often difficult and confusing phylogenetic reconstruction process. ^ Popular phylogenetic reconstruction methods, such as distance-based methods, attempt to find an optimal tree topology (that reflects the relationships among related sequences and their evolutionary history) by searching through the topology space. Various compromises between the fast (but incomplete) and exhaustive (but computationally prohibitive) search heuristics have been suggested. An intelligent compromise algorithm that relies on a flexible “beam” search principle from the Artificial Intelligence domain and uses the pre-computed local topology reliability information to adjust the beam search space continuously is described in the second chapter of this dissertation. ^ However, sometimes even a (virtually) complete distance-based method is inferior to the significantly more elaborate (and computationally expensive) maximum likelihood (ML) method. In fact, depending on the nature of the sequence data in question either method might prove to be superior. Therefore, it is difficult (even for an expert) to tell a priori which phylogenetic reconstruction method—distance-based, ML or maybe maximum parsimony (MP)—should be chosen for any particular data set. ^ A number of factors, often hidden, influence the performance of a method. For example, it is generally understood that for a phylogenetically “difficult” data set more sophisticated methods (e.g., ML) tend to be more effective and thus should be chosen. However, it is the interplay of many factors that one needs to consider in order to avoid choosing an inferior method (potentially a costly mistake, both in terms of computational expenses and in terms of reconstruction accuracy.) ^ Chapter III of this dissertation details a phylogenetic reconstruction expert system that selects a superior proper method automatically. It uses a classifier (a Decision Tree-inducing algorithm) to map a new data set to the proper phylogenetic reconstruction method. ^

El CIFOT como apoyo a la gestión gubernamental : inconveniente para la inversión minera

La falta de información sistematizada sobre reservas mineras causa desinterés de los capitales extranjeros, que demandan un conocimiento preciso sobre localización de yacimientos y un catastro saneado (con los títulos de propiedad correctos). En este artículo se presenta la experiencia del CIFOT en el trabajo solicitado a tales fines por la Dirección de Minería, denominado Situación de la Información Minera- Provincia de Mendoza, 1993" El objetivo principal fue evaluar la información disponible en la Dirección, procesarla, graficarla y generar cartografía temática a partir del uso de GIS, para ser presentada por las autoridades gubernamentales en Denver, USA, ante diversos inversores del sector. Se logra evidenciar la representatividad de la minería en Mendoza, por departamentos, la distribución de los yacimientos mineros, el estado de cada uno y la infraestructura vial de acceso. Esto permite a la Dirección de Minería implementar un sistema unificado de información minera, tarea que a posteriori es completada por el programa nacional PASMA.

Romanian glocalization : Case study on the Rosia Montana Gold Corporation Mining Project

At the end of the communist era, which was characterised as a closed social experiment, Romania found itself in the middle of a globalization process. Its industrial capacities have been considerably reduced through a poor and spendthrift management. There was a mass exodus of the labour force abroad and the educational background for the remaining part was no longer in agreement with the labour market. On these grounds, the vectors of globalization, in the form of foreign investments, entered Romania effortlessly. There even were local communities where the arrival of foreign investors was expected like a second coming of Christ. This is the context in which a Canadian company set forth the mining project Rosia Montana Gold Corporation. The implementation of the project should have started in 2005. Nevertheless, the project has not been effectively launched yet. This situation is based on what we call Romanian glocalization, namely a specific confrontation between global and local on Romanian land

Romanian glocalization : Case study on the Rosia Montana Gold Corporation Mining Project

At the end of the communist era, which was characterised as a closed social experiment, Romania found itself in the middle of a globalization process. Its industrial capacities have been considerably reduced through a poor and spendthrift management. There was a mass exodus of the labour force abroad and the educational background for the remaining part was no longer in agreement with the labour market. On these grounds, the vectors of globalization, in the form of foreign investments, entered Romania effortlessly. There even were local communities where the arrival of foreign investors was expected like a second coming of Christ. This is the context in which a Canadian company set forth the mining project Rosia Montana Gold Corporation. The implementation of the project should have started in 2005. Nevertheless, the project has not been effectively launched yet. This situation is based on what we call Romanian glocalization, namely a specific confrontation between global and local on Romanian land

Romanian glocalization : Case study on the Rosia Montana Gold Corporation Mining Project

At the end of the communist era, which was characterised as a closed social experiment, Romania found itself in the middle of a globalization process. Its industrial capacities have been considerably reduced through a poor and spendthrift management. There was a mass exodus of the labour force abroad and the educational background for the remaining part was no longer in agreement with the labour market. On these grounds, the vectors of globalization, in the form of foreign investments, entered Romania effortlessly. There even were local communities where the arrival of foreign investors was expected like a second coming of Christ. This is the context in which a Canadian company set forth the mining project Rosia Montana Gold Corporation. The implementation of the project should have started in 2005. Nevertheless, the project has not been effectively launched yet. This situation is based on what we call Romanian glocalization, namely a specific confrontation between global and local on Romanian land

Building the View Graph of a Category by Exploiting Image Realism

We propose a weakly supervised method to arrange images of a given category based on the relative pose between the camera and the object in the scene. Relative poses are points on a sphere centered at the object in a given canonical pose, which we call object viewpoints. Our method builds a graph on this sphere by assigning images with similar viewpoint to the same node and by connecting nodes if they are related by a small rotation. The key idea is to exploit a large unlabeled dataset to validate the likelihood of dominant 3D planes of the object geometry. A number of 3D plane hypotheses are evaluated by applying small 3D rotations to each hypothesis and by measuring how well the deformed images match other images in the dataset. Correct hypotheses will result in deformed images that correspond to plausible views of the object, and thus will likely match well other images in the same category. The identified 3D planes are then used to compute affinities between images related by a change of viewpoint. We then use the affinities to build a view graph via a greedy method and the maximum spanning tree.

Patrimonio Histórico Minero-Metalúrgico, Patrimonio Cultural/ Mining-Metallurgical Historical Heritage, Cultural Heritage

El panel se divide en tres secciones : Minería histórica , Patrimonio Minero y Museos.

A Methodological model to assist the optimization and risk management of mining investment decisions

Identifying, quantifying, and minimizing technical risks associated with investment decisions is a key challenge for mineral industry decision makers and investors. However, risk analysis in most bankable mine feasibility studies are based on the stochastic modelling of project “Net Present Value” (NPV)which, in most cases, fails to provide decision makers with a truly comprehensive analysis of risks associated with technical and management uncertainty and, as a result, are of little use for risk management and project optimization. This paper presents a value-chain risk management approach where project risk is evaluated for each step of the project lifecycle, from exploration to mine closure, and risk management is performed as a part of a stepwise value-added optimization process.

An investigation of the performance of a new Mechanical thrombectomy device using Bond Graph modelling: application to the extraction of blood clots in the middle cerebral artery

A number of thrombectomy devices using a variety of methods have now been developed to facilitate clot removal. We present research involving one such experimental device recently developed in the UK, called a ‘GP’ Thrombus Aspiration Device (GPTAD). This device has the potential to bring about the extraction of a thrombus. Although the device is at a relatively early stage of development, the results look encouraging. In this work, we present an analysis and modeling of the GPTAD by means of the bond graph technique; it seems to be a highly effective method of simulating the device under a variety of conditions. Such modeling is useful in optimizing the GPTAD and predicting the result of clot extraction. The aim of this simulation model is to obtain the minimum pressure necessary to extract the clot and to verify that both the pressure and the time required to complete the clot extraction are realistic for use in clinical situations, and are consistent with any experimentally obtained data. We therefore consider aspects of rheology and mechanics in our modeling.

Uniformly Reweighted Belief Propagation: A Factor Graph Approach

Tree-reweighted belief propagation is a message passing method that has certain advantages compared to traditional belief propagation (BP). However, it fails to outperform BP in a consistent manner, does not lend itself well to distributed implementation, and has not been applied to distributions with higher-order interactions. We propose a method called uniformly-reweighted belief propagation that mitigates these drawbacks. After having shown in previous works that this method can substantially outperform BP in distributed inference with pairwise interaction models, in this paper we extend it to higher-order interactions and apply it to LDPC decoding, leading performance gains over BP.

A graph-based approach for latency modeling and optimization in multiview video encoding

We present a novel framework for encoding latency analysis of arbitrary multiview video coding prediction structures. This framework avoids the need to consider an specific encoder architecture for encoding latency analysis by assuming an unlimited processing capacity on the multiview encoder. Under this assumption, only the influence of the prediction structure and the processing times have to be considered, and the encoding latency is solved systematically by means of a graph model. The results obtained with this model are valid for a multiview encoder with sufficient processing capacity and serve as a lower bound otherwise. Furthermore, with the objective of low latency encoder design with low penalty on rate-distortion performance, the graph model allows us to identify the prediction relationships that add higher encoding latency to the encoder. Experimental results for JMVM prediction structures illustrate how low latency prediction structures with a low rate-distortion penalty can be derived in a systematic manner using the new model.