Revitalizing Japan's remote areas has become a crucial task, and Matsue City exemplifies this effort in its temporary event spaces, created through collective efforts to foster urban vibrancy and bring together residents and visitors. This research examines the relationship between data-driven in-sights using generative AI and visual attractiveness by evaluating tempo-rary events in Matsue City, particularly considering the cognitive-cultural differences in processing visual information of the participants. The first phase employs semantic keyword extraction from interviews, categorizing responses into physical elements, activities, and atmosphere. The second phase analyzes spatial perception through three categories: layout hierar-chy, product visibility, and visual attention. The correlation indicates that successful event design requires a balance between spatial efficiency and diverse needs, with a spatial organization that optimizes visitor flow and visibility strategies considering cultural and demographic diversity. These findings contribute to understanding the urban quality of temporary event spaces and offer a replicable framework for enhancing the visual appeal of events in remote areas throughout Japan.

In this paper, we study two problems: determining action model equivalence and minimizing the event space of an action model under certain structural relationships. The Kripke model equivalence is perfectly caught by the structural relationship called bisimulation. In this paper, we propose the generalized action emulation perfectly catching the action model equivalence. Previous structural relationships sufficient for the action model equivalence, i.e. the bisimulation, the propositional action emulation, the action emulation, and the action emulation of canonical action models, can be described by various restricted versions of the generalized action emulation. We summarize four critical properties of the atom set over preconditions, and prove that any formula set satisfying these properties can be used to restrict the generalized action emulation to determine the action model equivalence by an iteration algorithm. We also construct a new formula set with these four properties, which is generally more efficient than the atom set. The technique of the partition refinement has been used to minimize the world space of a Kripke model under the bisimulation. Applying the partition refinement to action models allows one to minimize their event spaces under the bisimulation. The propositional action emulation is weaker than bismulation but still sufficient for the action model equivalence. We prove that it is PSPACE-complete to minimize the event space of an action model under the propositional action emulation, and provide a PSPACE algorithm for it. Finally, we prove that minimize the event space under the action model equivalence is PSPACE-hard, and propose a computable method based on the canonical formulas of modal logics to solve this problem.

Random permutation set (RPS), as a recently proposed theory, enables powerful information representation by traversing all possible permutations. However, the repetition of items is not allowed in RPS while it is quite common in real life. To address this issue, we propose repeatable random permutation set ($\rm R^2PS$) which takes the repetition of items into consideration. The right and left junctional sum combination rules are proposed and their properties including consistency, pseudo-Matthew effect and associativity are researched. Based on these properties, a decision support system application is simulated to show the effectiveness of $\rm R^2PS$.

Last fall, the MIT Stephen A. Schwarzman College of Computing embarked on a project to design and construct a new building on Vassar Street in Cambridge, at the former site of Building 44. Working with Skidmore, Owings & Merrill (SOM), the design for the new building is taking shape, with plans for the exterior façade now complete. The proposed project will establish a home for the MIT Schwarzman College of Computing, providing state-of-the-art space for computing research and education. The building's central location in the Vassar Street block between Main Street and Massachusetts Avenue will help form a new cluster of connectivity, and will enable the space to have a multifaceted role. The project has been reviewed extensively with city planning staff and will be presented to the Cambridge Planning Board for review and approval.

The Cotton Bowl is the first stadium in Texas to take a chance on the technology, which has the capability of disinfecting a 92,000 person stadium within 4 hours. DALLAS -- Stadiums are looking for ways to bring fans back to the stands in time for fall sports despite the coronavirus outrbreak, leading some Texas facilities to turn to drones for help. Cotton Bowl senior marketing director Julian Bowman describes the feeling of seeing the iconic Cotton Bowl Stadium in Dallas empty for the last few months, saying, "It is a weird feeling." "The Cotton Bowl opened up in 1930, so this was our 90th year and it was set to be our best year ever and unfortunately with COVID we are not able to do that," Bowman said. "It has really affected how we have been able to connect with our sports community and our entertainment community." The last event the Cotton Bowl was able to host was in January of 2020, before COVID-19 shut them down.

"The only constant in life is change" How many times you have seen a movie or a show and think "This is the future of technology". Well it's not all future anymore, because the future is here! We are currently witnessing a technological revolution in all industry verticals and as one of the most agile industry, events business is one of them. To be on top of the game and facilitate business, events businesses have accommodated and incorporated the change. These are the certain trends that are coming and forward-looking events companies have started embracing them.

Classical probability theory[2] is formulated using sets. Unfortuna tely, the language of sets lacks expressiveness and is, in a sense, a low-level'assembly language' of the probability theory. In this paper, we develop a'high -level approach' to classical probability theory with propositional compu tability logic[1] (CoL). Unlike other formalisms such as sets, logic and linear log ic, computability logic is built on the notion of events/games, which is cent ral to probability theory. Therefore, CoL is a perfect place to begin th e study of automating probability theory. To be specific, CoL is well-suited to describing complex (sequential/parallel) experiments and events, and more expressive than set operation s. In contrast, classical probability theory - based on,, etc - is designed to represent mainly the simple/additive events - the events that occur under a single experiment. Naturally, we need to talk about composite/multiplicative events - events that occur under two different experiments. Developing probability along this line requires a new, powerful language.

Reconstructing network connectivity from the collective dynamics of a system typically requires access to its complete continuous-time evolution although these are often experimentally inaccessible. Here we propose a theory for revealing physical connectivity of networked systems only from the event time series their intrinsic collective dynamics generate. Representing the patterns of event timings in an event space spanned by inter-event and cross-event intervals, we reveal which other units directly influence the inter-event times of any given unit. For illustration, we linearize an event space mapping constructed from the spiking patterns in model neural circuits to reveal the presence or absence of synapses between any pair of neurons as well as whether the coupling acts in an inhibiting or activating (excitatory) manner. The proposed model-independent reconstruction theory is scalable to larger networks and may thus play an important role in the reconstruction of networks from biology to social science and engineering.