The Currency of Wiki Articles – A Language Model-based Approach

Wikis are ubiquitous in organisational and private use and provide a wealth of textual data. Maintaining the currency of this textual data is important and difficult, requiring large manual efforts. Previous approaches from literature provide valuable contributions for assessing the currency of structured data or whole wiki articles but are unsuitable for textual wiki data like single sentences. Thus, we propose a novel approach supporting the assessment and improvement of the currency of textual wiki data in an automated manner. Grounded on a theoretical model, our approach makes use of data retrieved from recently published news articles and a language model to determine the currency of fact-based wiki sentences and suggest possible updates. Our evaluation conducted on 543 sentences from six wiki domains shows that the approach yields promising results with accuracies over 80% and thus is well-suited to support assessment and improvement of the currency of textual wiki data

Hybrid genetic algorithms in agent-based artificial market model for simulating fan tokens trading

In recent years cryptographic tokens have gained popularity as they can be used as a form of emerging alter- native financing and as a means of building platforms. The token markets innovate quickly through technology and decentralization, and they are constantly changing, and they have a high risk. Negotiation strategies must therefore be suited to these new circumstances. The genetic algorithm offers a very appropriate approach to resolving these complex issues. However, very little is known about genetic algorithm methods in cryptographic tokens. Accordingly, this paper presents a case study of the simulation of Fan Tokens trading by implementing selected best trading rule sets by a genetic algorithm that simulates a negotiation system through the Monte Carlo method. We have applied Adaptive Boosting and Genetic Algorithms, Deep Learning Neural Network-Genetic Algorithms, Adaptive Genetic Algorithms with Fuzzy Logic, and Quantum Genetic Algorithm techniques. The period selected is from December 1, 2021 to August 25, 2022, and we have used data from the Fan Tokens of Paris Saint-Germain, Manchester City, and Barcelona, leaders in the market. Our results conclude that the Hybrid and Quantum Genetic algorithm display a good execution during the training and testing period. Our study has a major impact on the current decentralized markets and future business opportunitiesThis research was funded by the Universitat de Barcelona, under the grant UB-AE-AS017634

Risk Management

Every business and decision involves a certain amount of risk. Risk might cause a loss to a company. This does not mean, however, that businesses cannot take risks. As disengagement and risk aversion may result in missed business opportunities, which will lead to slower growth and reduced prosperity of a company. In today's increasingly complex and diverse environment, it is crucial to find the right balance between risk aversion and risk taking. To do this it is essential to understand the complex, out of the whole range of economic, technical, operational, environmental and social risks associated with the company's activities. However, risk management is about much more than merely avoiding or successfully deriving benefit from opportunities. Risk management is the identification, assessment, and prioritization of risks. Lastly, risk management helps a company to handle the risks associated with a rapidly changing business environment

Probabilistic multiple kernel learning

The integration of multiple and possibly heterogeneous information sources for an overall decision-making process has been an open and unresolved research direction in computing science since its very beginning. This thesis attempts to address parts of that direction by proposing probabilistic data integration algorithms for multiclass decisions where an observation of interest is assigned to one of many categories based on a plurality of information channels

Critical Market Crashes

This review is a partial synthesis of the book ``Why stock market crash'' (Princeton University Press, January 2003), which presents a general theory of financial crashes and of stock market instabilities that his co-workers and the author have developed over the past seven years. The study of the frequency distribution of drawdowns, or runs of successive losses shows that large financial crashes are ``outliers'': they form a class of their own as can be seen from their statistical signatures. If large financial crashes are ``outliers'', they are special and thus require a special explanation, a specific model, a theory of their own. In addition, their special properties may perhaps be used for their prediction. The main mechanisms leading to positive feedbacks, i.e., self-reinforcement, such as imitative behavior and herding between investors are reviewed with many references provided to the relevant literature outside the confine of Physics. Positive feedbacks provide the fuel for the development of speculative bubbles, preparing the instability for a major crash. We demonstrate several detailed mathematical models of speculative bubbles and crashes. The most important message is the discovery of robust and universal signatures of the approach to crashes. These precursory patterns have been documented for essentially all crashes on developed as well as emergent stock markets, on currency markets, on company stocks, and so on. The concept of an ``anti-bubble'' is also summarized, with two forward predictions on the Japanese stock market starting in 1999 and on the USA stock market still running. We conclude by presenting our view of the organization of financial markets.Comment: Latex 89 pages and 38 figures, in press in Physics Report

Behavioral response of mule deer to natural gas development in the Piceance Basin

2015 Spring.Includes bibliographical references.To view the abstract, please see the full text of the document

Untangling hotel industry’s inefficiency: An SFA approach applied to a renowned Portuguese hotel chain

The present paper explores the technical efficiency of four hotels from Teixeira Duarte Group - a renowned Portuguese hotel chain. An efficiency ranking is established from these four hotel units located in Portugal using Stochastic Frontier Analysis. This methodology allows to discriminate between measurement error and systematic inefficiencies in the estimation process enabling to investigate the main inefficiency causes. Several suggestions concerning efficiency improvement are undertaken for each hotel studied.info:eu-repo/semantics/publishedVersio

Empirical Performance Evaluation of Consensus Algorithms in Permissioned Blockchain Platforms

Over the past decade or so, blockchain and distributed ledger technology (DLT) have steadily made their way into the mainstream media. As a result, new blockchain platforms and protocols are emerging rapidly. However, the performance of the resultant systems, and their resilience in hostile network environments is as yet not clearly understood. This thesis proposes a methodology to compare these platforms (specifically permissioned platforms) - and analyze the role of consensus protocols in determining system performance. It studies system performance in the face of network faults and varying loads, and also provides a qualitative analysis of each shortlisted platform. The four platforms - Ethereum, Hyperledger Fabric, Hyperledger Sawtooth, and Cosmos-SDK - are shortlisted on the basis of the consensus protocols they offer, i.e. Clique, Raft, PBFT, and Tendermint respectively. The following chapters discuss our selection criteria, the performance metrics used for comparison, and the steps followed to build a blockchain application on each platform. Considering the prominence of modelling techniques in the existing literature, we build stochastic models for each shortlisted protocol, and measure the same performance metrics as in our applications. Ultimately, this research aims to determine what factors affect the performance of blockchain systems, and what is the best way to measure their performance characteristics - by building applications or by building stochastic models? The experiments show that both methods of performance measurement have their pros and cons. They also highlight the importance of platform architecture in the determination of system performance. Selecting consensus protocols and blockchain platforms are critical decisions for any blockchain system. However, different choices shine in different settings. To recognise the best choice for a given use-case, it is crucial to first compare the protocols - and this thesis does that on the basis of performance

Genetic Diversity And Stock Structure In Teleosts Of Interest To Fisheries

La sopravvivenza delle specie ittiche è messa a rischio dall’elevato sforzo di pesca e dai cambiamenti climatici in atto. Per poter sviluppare nuove strategie di gestione e conservazione delle risorse alieutiche è necessario conoscere la struttura genetica delle specie e capire come esse reagiscono al sovrasfruttamento e ai cambiamenti climatici. La struttura genetica di due specie d’interesse commerciale nel bacino del Mediterraneo, il “rossetto” (Aphia minuta) e l’acciuga (Engraulis encrasicolus), è stata analizzata in questo studio. I risultati hanno mostrato un’evidente strutturazione in stock genetici distinti sia per A. minuta, nel Mar Mediterraneo, sia per E. encrasicolus, all’interno del Mar Adriatico. È stato inoltre osservato che lo stock adriatico di acciughe ha subito rilevanti fluttuazioni demografiche negli ultimi 40 anni, con un crollo nel 1987. Analisi genetiche su campioni appartenenti a una serie storica temporale hanno mostrato una riduzione di diversità genetica consecutiva al crollo demografico e un valore di taglia effettiva della popolazione (Ne) molto più basso rispetto alla taglia censita (Nc). Ciò dimostra che l’acciuga è una specie estremamente sensibile alle fluttuazioni demografiche determinate sia dall’attività di pesca che dai cambiamenti ambientali. Infine, per capire come i pesci reagiranno ai cambiamenti climatici attuali e futuri, si è valutato in che modo una specie sensibile a variazioni di temperatura ha reagito ai cambiamenti climatici del passato. A tale scopo, analisi genetiche sono state eseguite su reperti ossei sub-fossili di Salmo trutta provenienti da una colonna stratigrafica comprendente il periodo di transizione climatica avvenuto tra Pleistocene e Olocene. I risultati hanno mostrato una netta corrispondenza tra abbondanza di resti negli strati, variazioni nella diversità genetica e fluttuazioni climatiche, dimostrando che i cambiamenti climatici hanno influenzato tale specie a livello genetico, biologico ed ecologico.Fishing activities and environmental changes can impact fish species of commercial interest at genetic level, making them more prone to the extinction. In order to understand the current population structure and how over-exploitation and future climate changes could affect fish species, it is important to develop correct management and conservation strategies. With this aim, the genetic structure of two Teleosts of commercial interest within the Mediterranean area, the transparent goby (Aphia minuta) and the European anchovy (Engraulis encrasicolus), was analysed. The results obtained revealed a pronounced genetic structure in the Mediterranean Sea for A. minuta and within the Adriatic Sea for E. encrasicolus. The European anchovy stock has fluctuated greatly during the last 40 years, with a total collapse in 1987. A temporal genetic analysis on historical samples was performed to evaluate if demographic fluctuations could affect this species at genetic level. The results obtained have demonstrated a loss of genetic diversity after the demographic collapse in 1987 and an effective population size (Ne) lower than census size (Nc), showing that the survival of E. encrasicolus could be negatively affected by demographic fluctuations due to fishing activities and/or environmental changes. Finally, sub-fossil bones of Salmo trutta, coming from a stratigraphic succession dating back to Pleistocene-Holocene transition, were genetically analysed to show the impact of past climatic fluctuations on temperature sensitive species and evaluate how they could respond to present and future climatic changes. The results obtained have highlighted a correspondence between frequency of remains in the deposit, variation in mtDNA genetic diversity and climatic fluctuations, demonstrating that climate changes can affect this species at genetic, biological and ecological level

Concepts and Methods from Artificial Intelligence in Modern Information Systems – Contributions to Data-driven Decision-making and Business Processes

Today, organizations are facing a variety of challenging, technology-driven developments, three of the most notable ones being the surge in uncertain data, the emergence of unstructured data and a complex, dynamically changing environment. These developments require organizations to transform in order to stay competitive. Artificial Intelligence with its fields decision-making under uncertainty, natural language processing and planning offers valuable concepts and methods to address the developments. The dissertation at hand utilizes and furthers these contributions in three focal points to address research gaps in existing literature and to provide concrete concepts and methods for the support of organizations in the transformation and improvement of data-driven decision-making, business processes and business process management. In particular, the focal points are the assessment of data quality, the analysis of textual data and the automated planning of process models. In regard to data quality assessment, probability-based approaches for measuring consistency and identifying duplicates as well as requirements for data quality metrics are suggested. With respect to analysis of textual data, the dissertation proposes a topic modeling procedure to gain knowledge from CVs as well as a model based on sentiment analysis to explain ratings from customer reviews. Regarding automated planning of process models, concepts and algorithms for an automated construction of parallelizations in process models, an automated adaptation of process models and an automated construction of multi-actor process models are provided