Group size and ranging patterns of Queen Elizabeth National Park elephants by Eve Abe

“… Outlines results from an ongoing study focussing on the changes in group size and ranging patterns of elephants subsequent to the elimination of large scale poaching which took place in the area in the 1970s. …”
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Divergent altitudinal distributions of bird and bat species richness in a Mediterranean mountain range: patterns and prospects by E. Tena, J. L. Tellería

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Effects of 3D Stimuli With Frequency Ranges, Patterns, and Shapes on SSVEP-BCI Performance in Virtual Reality by Zihao Wei, Yanfei Lin, Jiayi Chen, Shuo Pan, Xiaorong Gao

“…This study investigated the effects of 3D stimuli with frequency ranges, patterns, and shapes on the performance and user experiences of VR-SSVEP. …”
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Ranging patterns of a large western Gorilla group at Dipikar Island in the Campo—Ma’an National Park, Cameroon by Nadege Wangue, Chloé Cipollettta, Shelly Masi, David Greer

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The Activity and Ranging Patterns of Gelada Monkeys as Behavioral Responses to the Effects of Livestock Grazing in the Simien Mountains National Park, Ethiopia by Belayneh Abebe, Mezgebu Ashagrie, Eshetu Moges

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The status of elephants in Uganda: Queen Elizabeth National Park by Eve Abe

“…The present study involves fitting animals with radio collars to monitor the ranging patterns of the three major groups now occupying the Queen Elizabeth National Park area. …”
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Global positioning system (GPS) collar data shows variations in distribution, ranging area and habitat selection of the African savannah elephant in a semi-arid protected area by Nobert Tafadzwa Mukomberanwa, Phillip Taru, Beaven Utete, Patmore Ngorima

“…This study aimed to: (i) investigate the seasonal ranging patterns of the African savannah elephants and (ii) model the preferred habitat of the African savannah elephants in Mana Pools National Park (MNP) in Zimbabwe. …”
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Dingo movement depends on sex, social status and litter size by Brendan F. Alting, Benjamin J. Pitcher, Michelle Campbell-Ward, Neil R. Jordan

“…In common with other carnivores, these results suggest that ranging patterns depend on the sex and breeding status of the individual and potentially on levels of competition. …”
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Behaviour and habitat preferences of translocated rhinos (Rhinoceros unicornis) at Manas National Park, Assam, India by Deba Kumar Dutta

“…Overall, however, the translocated rhinos did not exhibit significant differences in their behaviour and ranging patterns compared to wild rhino populations documented in previous studies. …”
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Hybrid Deep Learning Framework for Continuous User Authentication Based on Smartphone Sensors by Bandar Alotaibi, Munif Alotaibi

“…Unlike many existing approaches that directly apply these techniques for specific recognition tasks, our method reshapes raw motion signals into ViT-like patches to capture short-range patterns, employs multi-head attention to emphasize the most discriminative temporal segments, and then processes these enhanced embeddings through a bidirectional LSTM to integrate broader contextual information. …”
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From Image to Sequence: Exploring Vision Transformers for Optical Coherence Tomography Classification by Amirali Arbab, Aref Habibi, Hossein Rabbani, Mahnoosh Tajmirriahi

“…The synergy between CNNs, which excel at extracting detailed localized features, and ViT, adept at recognizing long-range patterns, enables a more effective and comprehensive analysis of OCT images. …”
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Phytosociology, ecology, and distribution of Gymnospermium odessanum in Romania by Simona Dumitrița Chirilă, Mihai Doroftei, Marian Mierlă

“…The population’s conservation status and changes in the range pattern of the habitat type are unfavourable-inadequate. …”
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A Novel Hybrid Approach Using an Attention-Based Transformer + GRU Model for Predicting Cryptocurrency Prices by Esam Mahdi, Carlos Martin-Barreiro, Xavier Cabezas

“…By combining the Transformer’s strength in capturing long-range patterns with GRU’s ability to model short-term and sequential trends, the hybrid model provides a well-rounded approach to time series forecasting. …”
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A Hybrid Framework Integrating Traditional Models and Deep Learning for Multi-Scale Time Series Forecasting by Zihan Liu, Zijia Zhang, Weizhe Zhang

“…The core of our approach is a novel multi-scale prediction mechanism that combines the strengths of both model types to better capture short-range patterns and long-range dependencies. We design a dual-stage forecasting process, where a classical time series component first models transparent linear trends and seasonal patterns, and a deep neural network then learns complex nonlinear residuals and long-term contexts. …”
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