Es besteht weitgehend Einigkeit darüber, dass inzidentelles Lernen bewusstes Wissen über eine sequenziell strukturierte Regelhaftigkeit erzeugen kann, auch wenn die zu Grunde liegenden Lernprozesse nur ungenügend verstanden sind. Ob jedoch Sequenzlernen auch „implizit“ oder unbewusst erfolgen kann, ist umstritten. Fortschritte in diese Frage sind von Untersuchungen zu bewusstem und unbewusstem Lernen zu erwarten, die vor dem Hintergrund übergreifender Bewusstseinstheorien erfolgen. Rünger und Frensch (2008a) zeigen, wie „bewusstes Sequenzwissen“ in Rückgriff auf die „global workspace“-Theorie des Bewusstseins definiert und operationalisiert werden kann. Im Rahmen dieser Theorie wird „inferenzielle Promiskuität“ als zentrales funktionales Merkmal bewusster mentaler Repräsentationen betrachtet. Rünger und Frensch (2008b) überprüfen eine zentrale Vorhersage der „unexpected event“-Hypothese, einer Theorie zur Entstehung bewussten Wissens in inzidentellen Lernsituationen. In einer Serie von Experimenten wurden unerwartete Ereignisse durch Unterbrechungen des inzidentellen Lernprozesses experimentell induziert. In Übereinstimmung mit der „unexpected event“-Hypothese fanden die Autoren, dass sich die Verfügbarkeit bewussten Sequenzwissens erhöhte. Rünger, Nagy und Frensch (in Druck) untersuchen schließlich die Funktion bewussten Sequenzwissens im Kontext eines Rekognitionstests. Die empirischen Befunde deuten darauf hin, dass bewusstes Sequenzwissen die epistemische Grundlage für rationale Urteile im Gegensatz zu intuitiven oder heuristischen Urteilen darstellt. / There is a general consensus that incidental learning can produce conscious knowledge about a hidden sequential regularity, even though the underlying learning mechanisms are still poorly understood. By contrast, whether sequence learning can also be “implicit” or nonconscious is a matter of intense debate. Progress can be achieved by grounding research on conscious and nonconscious learning in larger theoretical frameworks of consciousness. Rünger and Frensch (2008a) show how “conscious sequence knowledge” can be defined and operationalized in reference to global workspace theory of consciousness that depicts “inferential promiscuity” as the functional hallmark of conscious mental representations. Rünger and Frensch (2008b) test a central prediction of the unexpected-event hypothesis — a theoretical account of the generation of conscious knowledge in incidental learning situations. In a series of experiments, unexpected events were induced experimentally by disrupting the incidental learning process. In line with the unexpected-event hypothesis, the authors observed an increased availability of conscious sequence knowledge. Finally, Rünger, Nagy, and Frensch (in press) explore the function of conscious sequence knowledge in the context of a sequence recognition test. The empirical results suggest that conscious sequence knowledge provides the epistemic basis for reasoned — as opposed to intuitive or heuristic — judgments.

Dot peen markings are used by Scania Ferruform to maintain a traceability of their products throughout the manufacturing. Quality inspection of the markings are performed to ensure that they are added correctly and readable. This is, however, done manually by workers, which they are looking to change. Machine vision, in combination with machine learning, could prove helpful in automating this process, which is where this thesis comes in. Images of two types of dot peen markings were gathered using different experimental setups and equipment. Amazon Rekognition and MVTec Halcon were both used to predict the characters of the images, in order to determine if the two systems could be used to demonstrate that the quality inspection can be automated. To improve the result, the images were also processed with varied techniques. The pretrained version of Amazon Rekognition and MVTec Halcon, with unprocessed image, performed the best. They both predicted all the characters correctly, and showed a high confidence in their predictions, with an average confidence of 96.41% and 99.87% respectively. When processing the images before predicting the confidence of the systems decreased and predictions were also made incorrectly. Custom training a model also showed a poor result, with the best combination of average precision and overall recall being at 0.733 and 0.561 respectively.

Encoding hieroglyphic texts is time-consuming. If a text already exists as hand-written transcription, there is an alternative, namely OCR. Off-the-shelf OCR systems seem difficult to adapt to the peculiarities of Ancient Egyptian. Presented is a proof-of-concept tool that was designed to digitize texts of Urkunden IV in the hand-writing of Kurt Sethe. It automatically recognizes signs and produces a normalized encoding, suitable for storage in a database, or for printing on a screen or on paper, requiring little manual correction. The encoding of hieroglyphic text is RES (Revised Encoding Scheme) rather than (common dialects of) MdC (Manuel de Codage). Earlier papers argued against MdC and in favour of RES for corpus development. Arguments in favour of RES include longevity of the encoding, as its semantics are font-independent. The present study provides evidence that RES is also much preferable to MdC in the context of OCR. With a well-understood parsing technique, relative positioning of scanned signs can be straightforwardly mapped to suitable primitives of the encoding.

Den Europeiska organisationen IASB och den Amerikanska organisationen FASB gav i maj 2014 ut IFRS 15-Intäkter från avtal med kunder vilket är den nya standarden med anvisningar om hur intäkter ska redovisas. Denna standard började gälla 1 januari 2018 och ersatte de äldre intäktsredovisningsstandarderna IAS 11 och IAS 18. Problemet med de äldre standarderna var att det fanns en svårighet med att hitta den kritiska tidpunkten för rekognition av intäkter. Med anledning av detta var den nya standardens yttersta syfte att klargöra för när intäkter ska tas upp i bolagens räkenskaper. Syftet med denna studie är att belysa de redovisningsskillnader som finns mellan IFRS 15 och IAS 11 samt undersöka vilka konsekvenser dessa skillnader får för bolags intressenter och deras beslutsfattande. För att på bästa sätt kunna belysa dessa skillnader består empirin av egenkonstruerade typfall där de olika redovisningsstandarderna appliceras. Användandet av typfall grundar sig i att det när studien gjordes inte fanns några årsredovisningar som hade IFRS 15 som redovisningsgrund eftersom standarden är så ny. För att kunna bestämma när en intäkt ska tas upp i redovisningen blir matchnings och realisationsprincipen två centrala delar i analysen. Med hjälp av vetenskapliga källor och etablerade teorier analyseras dessa. Vid analys av empirin och vid slutsatserna är det främst intressentteorin som ligger till grund för analysen. Således är de slutsatser som dras baserade på intressentteorin. Studien kommer fram till att IFRS 15 betraktas som något mer försiktig än sin föregångare IAS 11.

Encoding hieroglyphic texts is time-consuming. If a text already exists as hand-written transcription, there is an alternative, namely OCR. Off-the-shelf OCR systems seem difficult to adapt to the peculiarities of Ancient Egyptian. Presented is a proof-of-concept tool that was designed to digitize texts of Urkunden IV in the hand-writing of Kurt Sethe. It automatically recognizes signs and produces a normalized encoding, suitable for storage in a database, or for printing on a screen or on paper, requiring little manual correction. The encoding of hieroglyphic text is RES (Revised Encoding Scheme) rather than (common dialects of) MdC (Manuel de Codage). Earlier papers argued against MdC and in favour of RES for corpus development. Arguments in favour of RES include longevity of the encoding, as its semantics are font-independent. The present study provides evidence that RES is also much preferable to MdC in the context of OCR. With a well-understood parsing technique, relative positioning of scanned signs can be straightforwardly mapped to suitable primitives of the encoding.