Music-Based Procedural Content Generation for Games

A geração procedimental é algo ainda recente no mundo académico, que se entende como a criação de conteúdos automaticamente via algoritmos. Há várias razões para o desenvolvimento desta técnica, mas a principal é a redução da memória consumida, pois os algoritmos de geração procedimentais são capazes de gerar conteúdo em massa, ocupando ordens de magnitude menores em disco. Este procedimento é, normalmente, utilizado em jogos para gerar níveis, mapas, vegetação, missões, sendo menos comum para gerar ou alterar o motor de jogo ou o comportamento de NPCs (Non-Player Character). Apesar de a maioria dos jogos possuírem música, é frequente este elemento apenas servir como suporte ao jogo e ajudar a criar o ambiente necessário. Os jogos que utilizam a música como fonte de informação para criar conteúdo jogável ainda são raros e mesmo nestes o conteúdo gerado é, muitas vezes, gerado previamente e estático. Nesse sentido, novos jogos têm vindo a diferenciar-se neste processo, nos quais a música escolhida irá gerar conteúdos automaticamente e de forma diversa. O objetivo desta dissertação é desenvolver um jogo, de forma completamente procedimental a partir de segmentos de música, com o intuito de ser possível diferenciar de forma significativa os diferentes níveis criados e ser capaz de tirar conclusões referentes à utilização de música como gerador procedimental de conteúdos. Jogo este que será composto por missões de stealth onde é necessário ao jogador atravessar todo o nível com os recursos que encontrar e sem ser visto/apanhado pelos inimigos. O jogo consistirá, então, em receber uma música ou segmento de música como input e através de uma análise individual poder recolher algumas características importantes que o irão distinguir de outros. Após este processo, cada nível será criado consoante estes, permitindo diversidade em cada missão, principalmente de forma a condicionar o modo como esta será jogada.The generation of content procedurally is still something that is emerging in the academic studies, and it is understood as the creation of content automatically, through algorithmic means. There are many reasons to develop this technic, but, mainly, it is used to decrease the memory used for this matter, as this algorithms can continuosly create great amount of content, using lesser space in disk. This procedure is already used in games to create different levels, maps, missions or, less common, to change the game engine or the NPCs (Non-Player Character) behaviour.Even though most games already use music, it is mostly used as a way of supporting the game and create all the needed environment to enhance the user experience. Games that use music as an input source to create playable content are still rare and, commonly, they have their content generated before and in a static way. Naturally, new games are becoming popular in this process by using the chosen songs to generate different content automatically.The goal of this disseration is to develop a game, in a complete procedural way, through music segments, so it would be possible to distinguish significantly different levels, as well as being able to create an opinion about the usage of music as a procedural content generation. This game will be consisted in different stealth missions where the player has to cross the entire level using the available resources in order to not being seen/caught by the enemies. So, the game will receive a music or a segment of it as an input and through a unique analysys it will collect some important features that will allow each segment to be different. After this process, each level will be generated following these features, allowing it to create diversity in each mission, mainly to change the way the game is meant to be played

MAMMALS IN PORTUGAL : A data set of terrestrial, volant, and marine mammal occurrences in P ortugal

Mammals are threatened worldwide, with 26% of all species being includedin the IUCN threatened categories. This overall pattern is primarily associatedwith habitat loss or degradation, and human persecution for terrestrial mam-mals, and pollution, open net fishing, climate change, and prey depletion formarine mammals. Mammals play a key role in maintaining ecosystems func-tionality and resilience, and therefore information on their distribution is cru-cial to delineate and support conservation actions. MAMMALS INPORTUGAL is a publicly available data set compiling unpublishedgeoreferenced occurrence records of 92 terrestrial, volant, and marine mam-mals in mainland Portugal and archipelagos of the Azores and Madeira thatincludes 105,026 data entries between 1873 and 2021 (72% of the data occur-ring in 2000 and 2021). The methods used to collect the data were: live obser-vations/captures (43%), sign surveys (35%), camera trapping (16%),bioacoustics surveys (4%) and radiotracking, and inquiries that represent lessthan 1% of the records. The data set includes 13 types of records: (1) burrowsjsoil moundsjtunnel, (2) capture, (3) colony, (4) dead animaljhairjskullsjjaws, (5) genetic confirmation, (6) inquiries, (7) observation of live animal (8),observation in shelters, (9) photo trappingjvideo, (10) predators dietjpelletsjpine cones/nuts, (11) scatjtrackjditch, (12) telemetry and (13) vocalizationjecholocation. The spatial uncertainty of most records ranges between 0 and100 m (76%). Rodentia (n=31,573) has the highest number of records followedby Chiroptera (n=18,857), Carnivora (n=18,594), Lagomorpha (n=17,496),Cetartiodactyla (n=11,568) and Eulipotyphla (n=7008). The data setincludes records of species classified by the IUCN as threatened(e.g.,Oryctolagus cuniculus[n=12,159],Monachus monachus[n=1,512],andLynx pardinus[n=197]). We believe that this data set may stimulate thepublication of other European countries data sets that would certainly contrib-ute to ecology and conservation-related research, and therefore assisting onthe development of more accurate and tailored conservation managementstrategies for each species. There are no copyright restrictions; please cite thisdata paper when the data are used in publications.info:eu-repo/semantics/publishedVersio

Mammals in Portugal: a data set of terrestrial, volant, and marine mammal occurrences in Portugal

Mammals are threatened worldwide, with ~26% of all species being included in the IUCN threatened categories. This overall pattern is primarily associated with habitat loss or degradation, and human persecution for terrestrial mammals, and pollution, open net fishing, climate change, and prey depletion for marine mammals. Mammals play a key role in maintaining ecosystems functionality and resilience, and therefore information on their distribution is crucial to delineate and support conservation actions. MAMMALS IN PORTUGAL is a publicly available data set compiling unpublished georeferenced occurrence records of 92 terrestrial, volant, and marine mammals in mainland Portugal and archipelagos of the Azores and Madeira that includes 105,026 data entries between 1873 and 2021 (72% of the data occurring in 2000 and 2021). The methods used to collect the data were: live observations/captures (43%), sign surveys (35%), camera trapping (16%), bioacoustics surveys (4%) and radiotracking, and inquiries that represent less than 1% of the records. The data set includes 13 types of records: (1) burrows | soil mounds | tunnel, (2) capture, (3) colony, (4) dead animal | hair | skulls | jaws, (5) genetic confirmation, (6) inquiries, (7) observation of live animal (8), observation in shelters, (9) photo trapping | video, (10) predators diet | pellets | pine cones/nuts, (11) scat | track | ditch, (12) telemetry and (13) vocalization | echolocation. The spatial uncertainty of most records ranges between 0 and 100 m (76%). Rodentia (n =31,573) has the highest number of records followed by Chiroptera (n = 18,857), Carnivora (n = 18,594), Lagomorpha (n = 17,496), Cetartiodactyla (n = 11,568) and Eulipotyphla (n = 7008). The data set includes records of species classified by the IUCN as threatened (e.g., Oryctolagus cuniculus [n = 12,159], Monachus monachus [n = 1,512], and Lynx pardinus [n = 197]). We believe that this data set may stimulate the publication of other European countries data sets that would certainly contribute to ecology and conservation-related research, and therefore assisting on the development of more accurate and tailored conservation management strategies for each species. There are no copyright restrictions; please cite this data paper when the data are used in publications