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Ilaria Canova Calori,Monica Divitini
Pág. pp. 33 - 39
In this paper we investigate collaborative learning that takes place in a city with the support of mobile and wireless technology. Based on a literature review, we identify and discuss four main roles that technology can play in supporting (1) performanc...
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Nagella Uday Bhaskar,Paladugu Govindarajulu
Pág. pp. 9 - 13
The ability to support students/learners to learn on the move at any place and at any time is new task to be addressed by using the mobile devices of the learners. Mobile technology support has given birth to the concept of mobile learning possessing a w...
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Zhou Fang, Xiaoyong Wang, Liang Zhang and Bo Jiang
Currently, deep learning is extensively utilized for ship target detection; however, achieving accurate and real-time detection of multi-scale targets remains a significant challenge. Considering the diverse scenes, varied scales, and complex backgrounds...
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Pietros André Balbino dos Santos, Felipe Schwerz, Luiz Gonsaga de Carvalho, Victor Buono da Silva Baptista, Diego Bedin Marin, Gabriel Araújo e Silva Ferraz, Giuseppe Rossi, Leonardo Conti and Gianluca Bambi
Reference evapotranspiration (ET0) is one important agrometeorological parameter for hydrological studies and climate risk zoning. ET0 calculation by the FAO Penman?Monteith method requires several input data. However, the availability of climate data ha...
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Feifei Tao, Yanling Pi, Menghua Deng, Yongjun Tang and Chi Yuan
With the rise of artificial intelligence and big data technologies, it is increasingly significant to apply these emerging technologies to scientific decision-making in water conservancy project construction management in the face of many problems in the...
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Guangming Ling, Xiaofeng Mu, Chao Wang and Aiping Xu
Address parsing is a crucial task in natural language processing, particularly for Chinese addresses. The complex structure and semantic features of Chinese addresses present challenges due to their inherent ambiguity. Additionally, different task scenar...
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Nagella Uday Bhaskar,Surya Narayana Raju,Govindarajulu Paladugu,VenkataRamana Reddy
Pág. pp. 29 - 37
Mobile leaning application development has been influenced by the e-learning models, methods and a variation of these for the better understanding and accommodation of additional elements that prop up in m-learning scenarios and applications. Here unique...
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Sonia Castelo, Moacir Ponti and Rosane Minghim
Multiple-instance learning (MIL) is a paradigm of machine learning that aims to classify a set (bag) of objects (instances), assigning labels only to the bags. This problem is often addressed by selecting an instance to represent each bag, transforming a...
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Haidi Badr, Nayer Wanas and Magda Fayek
Unsupervised domain adaptation (UDA) presents a significant challenge in sentiment analysis, especially when faced with differences between source and target domains. This study introduces Weighted Sequential Unsupervised Domain Adaptation (WS-UDA), a no...
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Siyuan Yang, Mondher Bouazizi, Tomoaki Ohtsuki, Yohei Shibata, Wataru Takabatake, Kenji Hoshino and Atsushi Nagate
In this paper, we propose a novel Deep Reinforcement Learning Evolution Algorithm (DRLEA) method to control the antenna parameters of the High-Altitude Platform Station (HAPS) mobile to reduce the number of low-throughput users. Considering the random mo...
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Zheng Li, Xinkai Chen, Jiaqing Fu, Ning Xie and Tingting Zhao
With the development of electronic game technology, the content of electronic games presents a larger number of units, richer unit attributes, more complex game mechanisms, and more diverse team strategies. Multi-agent deep reinforcement learning shines ...
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Jianwei Geng, Hengpeng Li, Wenfei Luan, Yunjie Shi, Jiaping Pang and Wangshou Zhang
The tea plant (Camellia sinensis), as a major, global cash crop providing beverages, is facing major challenges from droughts and water shortages due to climate change. The accurate estimation of the actual evapotranspiration (ETa) of tea plants is essen...
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Riana Steen, Geir Haakonsen and Trygve Jakobsen Steiro
Crisis-induced learning (CIL), as a concept, has an ancient history. Although the academic literature offers a range of sophisticated approaches to address CIL, it is still not quite clear how we learn, how we know we have learned, and what challenges an...
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Eleonora Grilli and Fabio Remondino
The use of machine learning techniques for point cloud classification has been investigated extensively in the last decade in the geospatial community, while in the cultural heritage field it has only recently started to be explored. The high complexity ...
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Yuh-Shihng Chang, Chao-Nan Chen and Chia-Ling Liao
In non-English-speaking countries, students learning EFL (English as a Foreign Language) without a ?real? learning environment mostly shows poor English-learning performance. In order to improve the English-learning effectiveness of EFL students, we prop...
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Kai Zhang, Shoushan Luo, Yang Xin, Hongliang Zhu and Yuling Chen
In this paper, an influence model is proposed to tackle the sequence data analysis problems such as disordering, element missing and random noises. The proposed method can be used for mining intrusion patterns from the intrusion action sequence extracted...
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Cuong Ngyuen Pham,Serge Garlatti,Simon Lau,Benjamin Barbry,Thomas Vantroys
Pág. pp. 25 - 32
We are interested in learning and working scenarios integrating web service retrieval and orchestration in pervasive TEL systems in a learning situation at workplace. This paper proposes a context-aware model of corporate learning and working scenarios i...
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Yuansheng Dai, Yingyi Liu, Haoyu Song, Bing He, Haiwen Yuan and Boyang Zhang
Classification tasks are pivotal across diverse applications, yet the burgeoning amount of data, coupled with complicating factors such as noise, exacerbates the challenge of classifying complex data. For algorithms that require a large amount of data, t...
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Maxim Kolomeets, Olga Tushkanova, Vasily Desnitsky, Lidia Vitkova and Andrey Chechulin
This paper aims to test the hypothesis that the quality of social media bot detection systems based on supervised machine learning may not be as accurate as researchers claim, given that bots have become increasingly sophisticated, making it difficult fo...
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Zuopeng Li, Hengshuai Ju and Zepeng Ren
The existing research on dependent task offloading and resource allocation assumes that edge servers can provide computational and communication resources free of charge. This paper proposes a two-stage resource allocation method to address this issue. I...
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