Evolutionary algorithms are based on the principles of biological evolution (Bre- mermann et al., 1966; Fraser, 1957; Box, 1957). Genetic algorithms are a class of evolutionary algorithm applicable to optimisation of a wide range of problems because they do not assume that the problem to be optimised is differentiable or convex. Potential solutions to a problem are encoded by allele sequences (genes) on an artificial genome in a manner analogous to biological DNA. Populations of these artificial genomes are then tested and bred together, combining artificial genetic material by the operation of crossover and mutation of genes, so that encoded solutions which more completely optimise the problem flourish and weaker solutions die out. Genetic algorithms are applied to a very broad range of problems in a variety of industries including financial modeling, manufacturing, data mining, engineering, design and science. Some examples are: • Traveling Salesman Problems such as vehicle routing, • Scheduling Problems such as Multiprocessor scheduling, and • Packing problems such as Shipping Container Operations. However, relative to the total volume of papers on genetic algorithms, few have focused on the theoretical foundations and identification of techniques to build effective genetic algorithms. Recent research has tended to focus on industry applications, rather than design techniques or parameter setting for genetic algorithms. There are of course exceptions to these observations. Nevertheless, the exceptions generally focus on a particular parameter or operator in relative isolation and do not attempt to find a foundation, approach or model which underpins them all. The objective of this Thesis is to establish theoretically sound methods for estimating appropriate parameter settings and structurally appropriate operators for genetic algorithms. The Thesis observes a link between some fundamental ideas in information theory and the relative frequency of alleles in a population. This observation leads to a systematic approach to determining optimum values for genetic algorithm parameters and the use of generational operators such as mutation, selection, crossover and termination criteria. The practical significance of the Thesis is that the outcomes form theoretically justified guidelines for researchers and practitioners. The Thesis establishes a model for the analysis of genetic algorithm be- haviour by applying fundamental concepts from information theory. The use of information theory grounds the model and contributions to a well established mathematical framework making them reliable and reproducible. The model and techniques contribute to the field of genetic algorithms by providing a clear and practical basis for algorithm design and tuning. Two ideas are central to the approach taken. Firstly, that evolutionary processes encode information into a population by altering the relative frequency of alleles. Secondly, that the key difference between a genetic algorithm and other algorithms is the generational operators, selection and crossover. Hence the model maximises a population’s information as represented by the relative frequency of solution alleles in the population, encourages the accumulation of these alleles and maximises the number of generations able to be processed. Information theory is applied to characterise the information sources used for mutation as well as to define selection thresholds in ranked populations. The importance of crossover in distributing alleles throughout a population and in promoting the accumulation of information in populations is analysed, while the Shannon–McMillan theorem is applied to identify practical termination criteria. The concept of ideal alleles as being those symbols in the appropriate loci, which form an optimal solution and the associated solution density of the population is central to this analysis. The term solution density is introduced to refer to the relative frequency of ideal alleles in the population at a particular generation. Solution density so defined represents a measure of a population’s fitness. By analysing the key genetic operators in terms of their effect on solution density, this Thesis identifies ten contributions. • A model for the analysis of genetic algorithm behaviour inspired by information theory. • A static selection threshold in ranked populations. • A dynamic selection threshold in ranked populations. • A maximum limit on the number of loci participating in epistasis is identified whereby more epistatic loci degrade directed search. • A practical limit to the amount of useful crossover is identified as sufficient. • An optimal crossover section length is found. • A cumulative scoring method for identifying solution density. • An entropy profile of ranked lists is described. • A practical termination criteria of most probable individuals based on the Shannon–McMillan theorem is provided. • An alternative genome representation which incorporates job–shop schedule problem knowledge in the genome rather than the algorithm’s generational operators is developed. Each of these contributions is validated by simulations, benchmark problems and application to a real–world problem.

Evolutionary algorithms are based on the principles of biological evolution (Bre- mermann et al., 1966; Fraser, 1957; Box, 1957). Genetic algorithms are a class of evolutionary algorithm applicable to optimisation of a wide range of problems because they do not assume that the problem to be optimised is differentiable or convex. Potential solutions to a problem are encoded by allele sequences (genes) on an artificial genome in a manner analogous to biological DNA. Populations of these artificial genomes are then tested and bred together, combining artificial genetic material by the operation of crossover and mutation of genes, so that encoded solutions which more completely optimise the problem flourish and weaker solutions die out. Genetic algorithms are applied to a very broad range of problems in a variety of industries including financial modeling, manufacturing, data mining, engineering, design and science. Some examples are: • Traveling Salesman Problems such as vehicle routing, • Scheduling Problems such as Multiprocessor scheduling, and • Packing problems such as Shipping Container Operations. However, relative to the total volume of papers on genetic algorithms, few have focused on the theoretical foundations and identification of techniques to build effective genetic algorithms. Recent research has tended to focus on industry applications, rather than design techniques or parameter setting for genetic algorithms. There are of course exceptions to these observations. Nevertheless, the exceptions generally focus on a particular parameter or operator in relative isolation and do not attempt to find a foundation, approach or model which underpins them all. The objective of this Thesis is to establish theoretically sound methods for estimating appropriate parameter settings and structurally appropriate operators for genetic algorithms. The Thesis observes a link between some fundamental ideas in information theory and the relative frequency of alleles in a population. This observation leads to a systematic approach to determining optimum values for genetic algorithm parameters and the use of generational operators such as mutation, selection, crossover and termination criteria. The practical significance of the Thesis is that the outcomes form theoretically justified guidelines for researchers and practitioners. The Thesis establishes a model for the analysis of genetic algorithm be- haviour by applying fundamental concepts from information theory. The use of information theory grounds the model and contributions to a well established mathematical framework making them reliable and reproducible. The model and techniques contribute to the field of genetic algorithms by providing a clear and practical basis for algorithm design and tuning. Two ideas are central to the approach taken. Firstly, that evolutionary processes encode information into a population by altering the relative frequency of alleles. Secondly, that the key difference between a genetic algorithm and other algorithms is the generational operators, selection and crossover. Hence the model maximises a population’s information as represented by the relative frequency of solution alleles in the population, encourages the accumulation of these alleles and maximises the number of generations able to be processed. Information theory is applied to characterise the information sources used for mutation as well as to define selection thresholds in ranked populations. The importance of crossover in distributing alleles throughout a population and in promoting the accumulation of information in populations is analysed, while the Shannon–McMillan theorem is applied to identify practical termination criteria. The concept of ideal alleles as being those symbols in the appropriate loci, which form an optimal solution and the associated solution density of the population is central to this analysis. The term solution density is introduced to refer to the relative frequency of ideal alleles in the population at a particular generation. Solution density so defined represents a measure of a population’s fitness. By analysing the key genetic operators in terms of their effect on solution density, this Thesis identifies ten contributions. • A model for the analysis of genetic algorithm behaviour inspired by information theory. • A static selection threshold in ranked populations. • A dynamic selection threshold in ranked populations. • A maximum limit on the number of loci participating in epistasis is identified whereby more epistatic loci degrade directed search. • A practical limit to the amount of useful crossover is identified as sufficient. • An optimal crossover section length is found. • A cumulative scoring method for identifying solution density. • An entropy profile of ranked lists is described. • A practical termination criteria of most probable individuals based on the Shannon–McMillan theorem is provided. • An alternative genome representation which incorporates job–shop schedule problem knowledge in the genome rather than the algorithm’s generational operators is developed. Each of these contributions is validated by simulations, benchmark problems and application to a real–world problem.

abstract: Attitudes play a fundamental role when making critical judgments and the extremity of people’s attitudes can be influenced by one’s emotions, beliefs, or past experiences and behaviors. Human attitudes and preferences are susceptible to social influence and attempts to influence or change another person’s attitudes are pervasive in all societies. Given the importance of attitudes and attitude change, the current project investigated linguistic aspects of conversations that lead to attitude change by analyzing a dataset mined from Reddit’s Change My View (Priniski & Horne, 2018). Analysis of the data was done using Natural Language Processing (NLP), specifically information density, to predict attitude change. Top posts from Reddit’s (N = 510,149) were imported and processed in Python and information density measures were computed. The results indicate that comments with higher information density are more likely to be awarded a delta and are perceived to be more persuasive. / Dissertation/Thesis / Masters Thesis Psychology 2020

No description available.

No description available.

As with any sensory input, music might be expected to incorporate the processing of information about the safety of the environment. Little research has been done on how such processing has evolved and how different kinds of sounds may affect the experience of certain environments. In this article, we investigate if music, as a form of auditory information, can trigger the experience of safety. We hypothesized that (1) there should be an optimal, subjectively preferred degree of information density of musical sounds, at which safety-related information can be processed optimally; (2) any deviation from the optimum, that is, both higher and lower levels of information density, should elicit experiences of higher stress and danger; and (3) in general, sonic scenarios with music should reduce experiences of stress and danger more than other scenarios. In Experiment 1, the information density of short music-like rhythmic stimuli was manipulated via their tempo. In an initial session, listeners adjusted the tempo of the stimuli to what they deemed an appropriate tempo. In an ensuing session, the same listeners judged their experienced stress and danger in response to the same stimuli, as well as stimuli exhibiting tempo variants. Results are consistent with the existence of an optimum information density for a given rhythm; the preferred tempo decreased for increasingly complex rhythms. The hypothesis that any deviation from the optimum would lead to experiences of higher stress and danger was only partly fit by the data. In Experiment 2, listeners should indicate their experience of stress and danger in response to different sonic scenarios: music, natural sounds, and silence. As expected, the music scenarios were associated with lowest stress and danger whereas both natural sounds and silence resulted in higher stress and danger. Overall, the results largely fit the hypothesis that music seemingly carries safety-related information about the environment.

In practice, a communication system works with finite blocklength codes because of the delay constraints and the information-theoretic bounds which are proposed for finite blocklength systems can be exploited to determine the performance of a designed system. In this thesis, achievable rates for given average error probabilities are considered for finite blocklength systems. Although classical bounds can be used to upper bound the error probability, these bounds require the optimization of auxiliary variables. In this work, a bound which is called the dependence testing (DT) bound that is free of any auxiliary variables is exploited. The DT bound is evaluated by introducing a normal approximation to the information density. Simulations carried out both for the Gaussian and discrete input alphabets show the proposed approximation enables very good prediction of the achievable rates. The proposed approximation is also used to calculate the average error probability for block fading channels. Simulations performed for Rayleigh block fading channels demonstrate that the total blocklength of the system in addition to the number of fading blocks should be accounted for especially when the number of fading blocks is large. A power allocation problem in block fading channels when the channel state information is available to the transmitting side is investigated in the final part of this work. The DT bound is optimized for a given channel state vector by allocating different power levels to each fading block by exploiting short-term power allocation. A simple power allocation algorithm is proposed which comes out with very similar results compared with the analytically computed values.

Este trabajo de investigación tiene como objetivo principal determinar la influencia del comercio electrónico en el desempeño logístico de las empresas Courier internacionales en el territorio peruano durante los años 2016 al 2020. El comercio electrónico, actualmente, representa un gran potencial para la economía peruana, pues está ganando una mayor participación en el mercado brindando beneficios a diversos sectores, entre ellos el sector Courier. Para analizar la influencia del comercio electrónico en el desempeño logístico de las empresas Courier se realizó una investigación cuantitativa. La herramienta que permitió efectuar el análisis fue la encuesta, a partir de un cuestionario realizado a 30 colaboradores pertenecientes a 11 empresas internacionales del sector Courier peruano. Los datos obtenidos fueron procesados a través del IBM SPSS Statistics, el cual permitió validar la confiablidad del instrumento con el coeficiente alfa de Cronbach, así como contrastar la correlación de las hipótesis con el coeficiente rho Spearman. De esta forma, se confirmó que el comercio electrónico, a través de sus dimensiones de personalización y densidad de la información, tiene una influencia positiva en el desempeño logístico de las empresas Courier internacionales. En base a los resultados obtenidos, esta investigación se considera una fuente importante para futuras investigaciones. / The main objective of this research work is to determine the influence of e-commerce on the logistics performance of international courier companies in the Peruvian territory during the years 2016 to 2020. E-commerce currently represents great potential for the Peruvian economy, as it is gaining greater market share, providing benefits to various sectors, including the Courier sector. To analyze the influence of e-commerce on the logistics performance of Courier companies, a quantitative investigation was carried out. The tool that allowed the analysis to be carried out was the survey, based on a questionnaire made to 30 employees belonging to 11 international companies in the Peruvian courier sector. The data was processed through the IBM SPSS Statistics, which allowed to validate the reliability of the instrument with the Cronbach alpha coefficient, as well as to contrast the correlation of the hypotheses with the rho Spearman coefficient. In this way, it was confirmed that e-commerce, through its dimensions of personalization and density of information, has a positive influence on the logistics performance of international courier companies. Based on the results obtained, this research is considered an important source for future research. / Tesis

No description available.

Den senaste tidens utveckling inom automatisk taligenkänning har lett till mindre resurskrävan-de och mer effektiva modeller. Detta innebär nya möjligheter för forskning kring spontant tal.I den här studien används Kungliga Bibliotekets svenska version av Wav2Vec 2.0 och en tal-korpus skapas utifrån ljudklipp från Sveriges Radio för att undersöka artikulationshastighet ispontant tal. Artikulationshastighet har setts ha en negativ korrelation till informationsdensiteti tidigare studier. Utifrån Uniform Information Density-hypotesens antagande; att talare strävarefter att jämna ut distributionen av information i ett yttrande, undersöks om de sammanlagdadependenslängderna mellan alla huvud och dependenter i meningar är korrelerat med artiku-lationshastigheten. Studien visar att metoden där artikulationshastighet beräknas med hjälp avKB:s Wav2Vec 2.0 leder till systematiskt högre artikulationshastighet än vid en manuell beräk-ning. Samt att korrelationen mellan antal stavelser i ett ord och artikulationshastighet blir denomvända mot vad tidigare studier med manuella metoder visat. Hypotesen att längre depen-denslängd skulle vara relaterat till högre artikulationshastighet får inget stöd i studien. Iställetses en motsatt effekt av minskande artikulationshastighet i relation till ökande dependenslängd.Studien belyser behovet av en modell specialiserad för beräkning av duration för att vidare ut-forska artikulationshastighet genom automatisk taligenkänning. / The last few years progress within automatic speech recognition has led to models that are lessresource demanding and more effective. This means new possibilities in the research regardingspontaneous speech. In this study, KB:s Swedish version of Wav2Vec 2.0 is used to create aspeech corpus and investigate articulation rate in spontaneous speech, with data from SverigesRadio. This study aims to investigate if this is a good method. It has been observed in previousstudies that articulation rate is negatively correlated to information density. With the uniforminformation density hypothesis; that speakers aim to distribute information evenly in an utteran-ce, as a base - this study aims to investigate whether the sum of the word dependency lengths insentences is correlated to articulation rate. The result shows that the method of calculating ar-ticulation rate with KB:s Wav2Vec 2.0 leads to systematically higher articulation rates comparedto results of a manual method. The hypothesis that longer dependency lengths would correlatewith higher articulation rates is not supported in the results. Instead the opposite effect can be  observed. The study shows the need for a model specialized in calculating duration for futureresearch regarding articulation rate with automatic speech recognition.KeywordsASR, automatic speech recognition, UID, articulation rate, dependency length, dependecy mi-nimization, corpus studies, information density