Subjects in laboratory experiments are prone to effects of social desirability. This reactive behavior is due to the subjects perceived anonymity in the entire experiment. Especially, socially desirable behavior is also triggered by assembling and/or payment procedures that are not anonymous. Indeed, in a laboratory experiments with a one-shot prisoner’s dilemma (PD) and perfect stranger anonymity subjects (n=174) showed significantly different cooperation rates depending on the anonymity conditions during assembling and the payment procedure, ranging from 33.3% to 19.9%. In addition, a first experiment with the PD and anonymous payment and double blind experimenting lead to a cooperation rate of 33.3%. Only after the same subjects (n=34) took part a second time in same, entire experiment, the cooperation rate fell to 8.8%. Therefore this measurement of the cooperation rates in a laboratory experiment failed the test-retest check on reliability. This happened though all manipulations used fulfilled the standards of fully anonymous experimenting. This means that such processes could go unnoticed and bias the results of any standard laboratory experiment on cooperation in one shot decisions. Therefore, in accordance with the textbook logic of laboratory experiments, but in contrast to a common practice (cf. Behavioral Game Theory) marginal totals from cooperation experiments in the laboratory should not be interpreted.

En este presente informe se abordará el Expediente Administrativo N° 676684-2016 en donde se analizará la oposición marcaria dentro de la normativa del derecho de marcas. Empieza el presente caso cuando el señor Andrew Michell Olivares solicita el registro de una marca denominada “Candelaria Pilsener”, la cual para el correcto registro se presentó todos los documentos y se realizó los pagos correspondientes. Posteriormente a ello, la empresa Unión de Cervecerías Backus y Johnston, titular de la marca “Pilsen Callao”, presenta su escrito de oposición marcaria toda vez que podría causar riesgo de confusión a los consumidores. En ese sentido, habiendo una oposición marcaria compete a la Comisión de signos distintivos del INDECOPI evaluar y resolver sobre el asunto materia de conflicto. Esta autoridad resuelve, entre otros, declarar fundada la oposición interpuesta y denegar el registro de marca. Ahora bien, teniendo por rechazada el registro de “Candelaria Pilsener”, el señor Michell presenta recurso de apelación bajo el principal fundamento de que el término “Pilsener” es solo una expresión descriptiva que no debería de considerarse para el examen comparativo entre ambas marcas. Finalmente, el Tribunal de Defensa de la competencia y de la Propiedad Intelectual resuelve, entre otros, revocar la resolución de primera instancia y otorgar el registro de la marca “Candelaria Pilsener”. / This report will address Administrative File No. 676684-2016 where trademark opposition will be analyzed within the regulations of trademark law. The present case begins when Mr. Andrew Michell Olivares requests the registration of a trademark called “Candelaria Pilsener”, which for the correct registration all the documents were presented and the corresponding payments were made. Subsequently, the company Unión de Cervecerías Backus y Johnston, owner of the "Pilsen Callao" trademark, presents its trademark opposition statement since it could cause a risk of confusion to consumers. In this sense, if there is a trademark opposition, it is the responsibility of the INDECOPI Distinctive Signs Commission to evaluate and resolve the matter of conflict. This authority resolves, among others, to declare the opposition filed founded and to deny the registration of the trademark. Now, considering that the registration of “Candelaria Pilsener” was rejected, Mr. Michell filed an appeal on the main grounds that the term “Pilsener” is only a descriptive expression that should not be considered for the comparative examination between both brands. Finally, the Court for the Defense of Competition and Intellectual Property resolves, among others, to revoke the first instance decision and grant the registration of the "Candelaria Pilsener" trademark. / Trabajo de suficiencia profesional

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I den här uppsatsen beskrivs en ansats till att med hjälp av statistiska metoder förutse utfallet i förmögenhetsrättsliga dispositiva tvistemål. Logistiska- och multilogistiska regressionsmodeller skattades på data för 13299 tvistemål från 5 tingsrätter och användes  till att förutse utfallet för 1522 tvistemål från 3 andra tingsrätter.   Modellerna presterade bättre än slumpen vilket ger stöd för slutsatsen att man kan använda statistiska metoder för att förutse utfallet i denna typ av tvistemål. / BACKROUND: The idea of legal automatization is a controversial topic that's been discussed for hundreds of years, in modern times in the context of Law & Artificial Intelligence. Strangely, real world applications are very rare. Assuming that the judicial system is like any system that transforms inputs into outputs one would think that we should be able measure it and and gain insight into its inner workings and ultimately use these measurements to make predictions about its output. In this thesis, civil procedures on commercial matters amenable to out-of-court settlement (Förmögenhetsrättsliga Dispositiva Tvistemål) was devoted particular interest and the question was posed: Can we predict the outcome of civil procedures using Statistical Methods? METHOD: By analyzing procedural law and legal doctrin, the civil procedure was modeled in terms of a random variable with a discrete observable outcome. Some data for 14821 cases was extracted from eight different courts. Five of these courts (13299 cases) were used to train the models and three courts (1522 cases) were chosen randomly and kept untouched for validation. Most cases seemed to concern monetary claims (66%) and/or damages (12%). Binary- and Multinomial- logistic regression methods were used as classifiers. RESULTS: The models where found to be uncalibrated but they clearly outperformed random score assignment at separating classes and at a preset threshold gave accuracies significantly higher (p<<0.001) than that of random guessing and in identifying settlements or the correct type of verdict performance was significantly better (p<<0.003) than consequently guessing the most common outcome. CONCLUSION: Using data for cases from one set of courts can to some extent predict the outcomes of cases from another set of courts. The results from applying the models to new data concludes that the outcome in civil processes can be predicted using statistical methods.

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À l’heure où le numérique s’est totalement imposé dans notre quotidien, nous pouvons nous demander comment évolue notre bien-être. La réalité virtuelle hautement immersive permet de développer des environnements propices à la relaxation qui peuvent améliorer les capacités cognitives et la qualité de vie de nombreuses personnes. Le premier objectif de cette étude est de réduire les émotions négatives et améliorer les capacités cognitives des personnes souffrant de déclin cognitif subjectif (DCS). À cette fin, nous avons développé un environnement de réalité virtuelle appelé Savannah VR, où les participants ont suivi un avatar à travers une savane. Nous avons recruté dix-neuf personnes atteintes de DCS pour participer à l’expérience virtuelle de la savane. Le casque Emotiv Epoc a capturé les émotions des participants pendant toute l’expérience virtuelle. Les résultats montrent que l’immersion dans la savane virtuelle a réduit les émotions négatives des participants et que les effets positifs ont continué par la suite. Les participants ont également amélioré leur performance cognitive. La confusion se manifeste souvent au cours de l’apprentissage lorsque les élèves ne comprennent pas de nouvelles connaissances. C’est un état qui est également très présent chez les personnes atteintes de démence à cause du déclin de leurs capacités cognitives. Détecter et surmonter la confusion pourrait ainsi améliorer le bien-être et les performances cognitives des personnes atteintes de troubles cognitifs. Le deuxième objectif de ce mémoire est donc de développer un outil pour détecter la confusion. Nous avons mené deux expérimentations et obtenu un modèle d’apprentissage automatique basé sur les signaux du cerveau pour reconnaître quatre niveaux de confusion (90% de précision). De plus, nous avons créé un autre modèle pour reconnaître la fonction cognitive liée à la confusion (82 % de précision). / At a time when digital technology has become an integral part of our daily lives, we can ask ourselves how our well-being is evolving. Highly immersive virtual reality allows the development of environments that promote relaxation and can improve the cognitive abilities and quality of life of many people. The first aim of this study is to reduce the negative emotions and improve the cognitive abilities of people suffering from subjective cognitive decline (SCD). To this end, we have developed a virtual reality environment called Savannah VR, where participants followed an avatar across a savannah. We recruited nineteen people with SCD to participate in the virtual savannah experience. The Emotiv Epoc headset captured their emotions for the entire virtual experience. The results show that immersion in the virtual savannah reduced the negative emotions of the participants and that the positive effects continued afterward. Participants also improved their cognitive performance. Confusion often occurs during learning when students do not understand new knowledge. It is a state that is also very present in people with dementia because of the decline in their cognitive abilities. Detecting and overcoming confusion could thus improve the well-being and cognitive performance of people with cognitive impairment. The second objective of this paper is, therefore, to develop a tool to detect confusion. We conducted two experiments and obtained a machine learning model based on brain signals to recognize four levels of confusion (90% accuracy). In addition, we created another model to recognize the cognitive function related to the confusion (82% accuracy).

This diploma's thesis is based around creating a classifier, which will be able to recognize an email communication received by Topefekt.s.r.o on daily basis and assigning it into classification class. This project will implement some of the most commonly used classification methods including machine learning. Thesis will also include evaluation comparing all used methods.