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.

Field-Based Evaluations of Horizontal Flat-Plate Fish Screens

Diversions from streams are often screened to prevent the loss of or injury to fish. Hydraulic criteria meant to protect fish that encounter screens have been developed, but primarily for screens that are vertical to the water flow rather than horizontal. For this reason, we measured selected hydraulic variables and released wild rainbow trout Oncorhynchus mykiss over two types of horizontal flat-plate fish screens in the field. Our goal was to assess the efficacy of these screens under a variety of conditions in the field and provide information that could be used to develop criteria for safe fish passage. We evaluated three different inverted-weir screens over a range of strewn (0.24-1.77 m(3)/s) and diversion flows (0.10-0.31 m(3)/s). Approach velocities (AVs) ranged from 3 to 8 cm/s and sweeping velocities (SVs) from 69 to 143 cm/s. We also evaluated a simple backwatered screen over stream flows of 0.23-0.79 m(3)/s and diversion flows of 0.08-0.32 m(3)/s. The mean SVs for this screen ranged from 15 to 66 cm/s and the mean AVs from 1 to 5 cm/s. The survival rates of fish held for 24 h after passage over these screens exceeded 98%. Overall, the number of fish-screen contacts was low and the injuries related to passage were infrequent and consisted primarily of minor fin injuries. Our results indicate that screens of this type have great potential as safe and effective fish screens for small diversions. Care must be taken, however, to avoid operating conditions that produce shallow or no water over the screen surface, situations of high AVs and low SVs at backwatered screens, and situations producing a localized high AV with spiraling flow.

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. ^

Continuous safety screens for randomized controlled clinical trials with blinded treatment information

Standard methods for testing safety data are needed to ensure the safe conduct of clinical trials. In particular, objective rules for reliably identifying unsafe treatments need to be put into place to help protect patients from unnecessary harm. DMCs are uniquely qualified to evaluate accumulating unblinded data and make recommendations about the continuing safe conduct of a trial. However, it is the trial leadership who must make the tough ethical decision about stopping a trial, and they could benefit from objective statistical rules that help them judge the strength of evidence contained in the blinded data. We design early stopping rules for harm that act as continuous safety screens for randomized controlled clinical trials with blinded treatment information, which could be used by anyone, including trial investigators (and trial leadership). A Bayesian framework, with emphasis on the likelihood function, is used to allow for continuous monitoring without adjusting for multiple comparisons. Close collaboration between the statistician and the clinical investigators will be needed in order to design safety screens with good operating characteristics. Though the math underlying this procedure may be computationally intensive, implementation of the statistical rules will be easy and the continuous screening provided will give suitably early warning when real problems were to emerge. Trial investigators and trial leadership need these safety screens to help them to effectively monitor the ongoing safe conduct of clinical trials with blinded data.^

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

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.

On loader productivity, rock strength and explosive energy in metal mining

Twenty production blasts in two open pit mines were monitored, in rocks with medium to very high strength. Three different blasting agents (ANFO, watergel and emulsion blend) were used, with powder factors ranging between 0.88 and 1.45 kg/m3. Excavators were front loaders and rope shovels. Mechanical properties of the rock, blasting characteristics and mucking rates were carefully measured. A model for the calculation of the productivity of excavators is developed thereof, in which the production rate results as a product of an ideal, maximum, productivity rate times an operating efficiency. The maximum rate is a function of the dipper capacity and the efficiency is a function of rock density, strength, and explosive energy concentration in the rock. The model is statistically significant and explains up to 92 % of the variance of the production rate measurements.

The effect of acoustic screens on orchestra musicians

La Directiva 2003/10/CE del Parlamento Europeo y del Consejo, del 6 de febrero de 2003, específica con arreglo al apartado 1 del artículo 16 de la Directiva 89/391/CEE las disposiciones mínimas de seguridad y de salud relativas a la exposición de los trabajadores a los riesgos derivados de los agentes físicos (ruido). En la industria musical, y en concreto en los músicos de orquesta, una exposición de más de ocho horas al día a un nivel de presión sonora de 80dB(A) o más es algo muy común. Esta situación puede causar a los trabajadores daños auditivos como la hiperacusia, hipoacusia, tinitus o ruptura de la membrana basilar entre otros. Esto significa que deben tomarse medidas para implementar las regulaciones de la forma más razonable posible para que la interpretación del músico, la dinámica y el concepto musical que se quiere transmitir al público se vea lo menos afectada posible. Para reducir la carga auditiva de los músicos de orquesta frente a fuertes impactos sonoros provenientes de los instrumentos vecinos, se está investigando sobre el uso de unos paneles acústicos que colocados en puntos estratégicos de la orquesta pueden llegar a reducir el impacto sonoro sobre el oído hasta 20dB. Los instrumentos de viento metal y de percusión son los responsables de la mayor emisión de presión sonora. Para proteger el oído de los músicos frente a estos impactos, se colocan los paneles en forma de barrera entre dichos instrumentos y los músicos colocados frente a ellos. De esta forma se protege el oído de los músicos más afectados. Para ver el efecto práctico que producen estos paneles en un conjunto orquestal, se realizan varias grabaciones en los ensayos y conciertos de varias orquestas. Los micrófonos se sitúan a la altura del oído y a una distancia de no más de 10cm de la oreja de varios de los músicos más afectados y de los músicos responsables de la fuerte emisión sonora. De este modo se puede hacer una comparación de los niveles de presión sonora que percibe cada músico y evaluar las diferencias de nivel existentes entre ambos. Así mismo se utilizan configuraciones variables de los paneles para comparar las diferencias de presión sonora que existen entre las distintas posibilidades de colocarlos y decidir así sobre la mejor ubicación y configuración de los mismos. A continuación, una vez obtenidos las muestras de audio y los diferentes archivos de datos medidos con un analizador de audio en distintas posiciones de la orquesta, todo ello se calibra y analiza utilizando un programa desarrollado en Matlab, para evaluar el efecto de los paneles sobre la percepción auditiva de los músicos, haciendo especial hincapié en el análisis de las diferencias de nivel de presión sonora (SPL). Mediante el cálculo de la envolvente de las diferencias de nivel, se evalúa de un modo estadístico el efecto de atenuación de los paneles acústicos en los músicos de orquesta. El método está basado en la probabilidad estadística de varias muestras musicales ya que al tratarse de música tocada en directo, la dinámica y la sincronización entre los músicos varía según el momento en que se toque. Estos factores junto con el hecho de que la partitura de cada músico es diferente dificulta la comparación entre dos señales grabadas en diferentes puntos de la orquesta. Se necesita por lo tanto de varias muestras musicales para evaluar el efecto de atenuación de los paneles en las distintas configuraciones mencionadas anteriormente. El estudio completo del efecto de los paneles como entorno que influye en los músicos de orquesta cuando están sobre el escenario, tiene como objetivo la mejora de sus condiciones de trabajo. Abstract For several years, the European Union has been adopting many laws and regulations to protect and give more security to people who are exposed to some risk in their job. Being exposed to a loud sound pressure level during many hours in the job runs the risk of hearing damage. Particularly in the field of music, the ear is the most important working tool. Not taking care of the ear can cause some damage such as hearing loss, tinnitus, hyperacusis, diplacusis, etc. This could have an impact on the efficiency and satisfaction of the musicians when they are playing, which could also cause stress problems. Orchestra musicians, as many other workers in this sector, are usually exposed to a sound level of 80dB(A) or more during more than eight hours per day. It means that they must satisfy the law and their legal obligations to avoid health problems proceeding from their job. Putting into practice the new regulations is a challenge for orchestras. They must make sure that the repertoire, with its dynamic, balance and feeling, is not affected by the reduction of sound levels imposed by the law. This study tries to investigate the benefits and disadvantages of using shields as a hearing protector during rehearsals and orchestral concerts.

Adapting autonomously classification data mining algorithms for ubiquitous devices

Abstract Due to recent scientific and technological advances in information sys¬tems, it is now possible to perform almost every application on a mobile device. The need to make sense of such devices more intelligent opens an opportunity to design data mining algorithm that are able to autonomous execute in local devices to provide the device with knowledge. The problem behind autonomous mining deals with the proper configuration of the algorithm to produce the most appropriate results. Contextual information together with resource information of the device have a strong impact on both the feasibility of a particu¬lar execution and on the production of the proper patterns. On the other hand, performance of the algorithm expressed in terms of efficacy and efficiency highly depends on the features of the dataset to be analyzed together with values of the parameters of a particular implementation of an algorithm. However, few existing approaches deal with autonomous configuration of data mining algorithms and in any case they do not deal with contextual or resources information. Both issues are of particular significance, in particular for social net¬works application. In fact, the widespread use of social networks and consequently the amount of information shared have made the need of modeling context in social application a priority. Also the resource consumption has a crucial role in such platforms as the users are using social networks mainly on their mobile devices. This PhD thesis addresses the aforementioned open issues, focusing on i) Analyzing the behavior of algorithms, ii) mapping contextual and resources information to find the most appropriate configuration iii) applying the model for the case of a social recommender. Four main contributions are presented: - The EE-Model: is able to predict the behavior of a data mining algorithm in terms of resource consumed and accuracy of the mining model it will obtain. - The SC-Mapper: maps a situation defined by the context and resource state to a data mining configuration. - SOMAR: is a social activity (event and informal ongoings) recommender for mobile devices. - D-SOMAR: is an evolution of SOMAR which incorporates the configurator in order to provide updated recommendations. Finally, the experimental validation of the proposed contributions using synthetic and real datasets allows us to achieve the objectives and answer the research questions proposed for this dissertation.

Cooperation between expert knowledge and data mining discovered knowledge: Lessons learned

Expert systems are built from knowledge traditionally elicited from the human expert. It is precisely knowledge elicitation from the expert that is the bottleneck in expert system construction. On the other hand, a data mining system, which automatically extracts knowledge, needs expert guidance on the successive decisions to be made in each of the system phases. In this context, expert knowledge and data mining discovered knowledge can cooperate, maximizing their individual capabilities: data mining discovered knowledge can be used as a complementary source of knowledge for the expert system, whereas expert knowledge can be used to guide the data mining process. This article summarizes different examples of systems where there is cooperation between expert knowledge and data mining discovered knowledge and reports our experience of such cooperation gathered from a medical diagnosis project called Intelligent Interpretation of Isokinetics Data, which we developed. From that experience, a series of lessons were learned throughout project development. Some of these lessons are generally applicable and others pertain exclusively to certain project types.