Machinic Ontology:Review: Mehdi Parsa, ‘Machinic Ontology’

The book Machinic Ontology draws parallels between books and brains and indeed models itself on a brain conceived of as a network of problems. A book is also regarded as a little machine, and in echoing Deleuze and Guattari in making this observation, Parsa’s objective in writing the book becomes apparent: it is a detailed evaluation of the becoming-concept of the machine-metaphor, one that applies a universal ‘machinism’ as a metaphysical foundation. This is a hugely important and timely undertaking, though not without various tensions, which will be examined in this review

Handling Grammar Cycles in the 1997 SML Definition

Fully general parsers permit the syntax specification of formallanguages to be unrestricted, allowing language designersto use a syntax specification that supports semanticsspecification, but also permitting ambiguity. Language workbenchesthat support fully general grammars need toolswhich can generate robust default behaviour but also allowexperienced designers to specify particular choices when ambiguityis encountered. The standard longest match approachto ambiguity resolution is not robust when a grammar containscycles. Although cycles can be removed from a grammar,this disrupts the syntax specification. We present analgorithm that safely removes cycles from the shared packedparse forests generated by general parsers and explore theapplication of the algorithm to the 1997 SML Definition. Thealgorithm results in a sub-forest to which further designerspecifiedor default disambiguation rules can be applied

Towards a Psychological Understanding of Character Design in Screenwriting:How Character Values, Viewer Values, and Film Narratives' Value Messages Shape Mainstream Film Popularity

Creating psychologically 'deep' characters is considered central to mainstream fiction films' popularity and a very challenging aspect of character design for screenwriters. However, there appear to be few effective training and problem-solving tools due to a lack of systematic and evidence-based understanding of character psychology. Seeking to address this gap, the thesis develops an interdisciplinary model drawing, amongst others, from the Schwartz Value Theory. The model defines film characters’ Wants and Needs and their value-driven motivations to address two research questions: how characters' value change and stability communicates film narratives' value messages, and how the alignment between film and viewer values affects film popularity.As hypothesised, an online experiment revealed that main characters often seem to follow one of two paths: either shifting from pan-culturally less preferred values to their preferred counterparts in the Schwartz value circle – when these derive from a basic human need described by Self-Determination Theory – or maintaining such need-derived values throughout a film. Particularly important in film value communication appear to be the final values of changing and the stable values of non-changing characters, as they correlated most consistently with film value perceptions. The initial values of changing characters seem to be perceived as either opposed or unrelated to a film's value message.Contrary to predictions, neither an online experiment (examining individuals’ film interest) nor an archival study (examining box office revenues and audience ratings of 1,200 films) supported the proposed alignment effect of film and viewer values. As endorsement of pan-culturally preferred values appears highly prevalent in films, it likely does not serve as a selection criterion. Moreover, the more strongly films express pan-culturally preferred values, the lower seem to be their audience ratings, potentially as they become too predictable. The thesis contributes to the scientific study of character psychology and the development of evidence-based screenwriting tools

A Novel Sonar Image Preprocessing Method for AUV Positioning Based on Underwater SLAM

Imaging sonar, as an efficient sensor for underwater observation and measurement, plays a very important role in the positioning and mapping of autonomous underwater vehicles (AUVs). Compared to visual simultaneous localization and mapping (SLAM) susceptible to the water quality and distance, sonar SLAM based on acoustic images has a better perception range and immunity to the surrounding fluid characteristics. However, due to the complexity of underwater environments, imaging sonar is often severely affected by noise, and sonar images usually exhibit low resolution, insufficient contrast, and blurred target edges, resulting in severe errors in positioning and mapping. To solve these problems, a sonar image preprocessing method is proposed to effectively eliminate noise, while feature edges preserved. First, the proposed image preprocessing method employs a threshold filter to eliminate potential noises; then, the contrast-limited adaptive histogram equalization algorithm is used to enhance the image features, and the guided filter (GF) is used to eliminate the residual noise. In addition, we introduce a factor graph-based sonar SLAM method, and the preprocessed sonar images are integrated into the SLAM process. Through numerical evaluation, the effectiveness of our proposed preprocessing method is validated, and the results show that it improves the processing speed, detection precision, and matching precision by about 73.9%, 30.8%, and 20.0%, respectively. Furthermore, simulation experiments and real experiment demonstrate that our proposed method improves both positioning accuracy and stability of the AUV

A Retreat from Global Solidarity:The Consequences of International Aid Cuts

As the US, UK and other countries slash development aid, Melita Lazell and Ivica Petrikova warn of the devastating consequences for global health, security, and diplomacy – and argue that the retreat from solidarity is a perilous gamble for us all