Titlebook: Intelligent Systems and Applications; Proceedings of the 2 Kohei Arai Conference proceedings 2024 The Editor(s) (if applicable) and The Aut

健談的人

,A Feature-based Approach on?Automatic Stopword Detection,chnique for automatic detection of stopwords. We have tested the validity of the proposed technique with extensive experiments and compared the results with a general English stopword list. Furthermore, we have evaluated the proposed technique with both formal written and social media text. The resu

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,Phrase-Based Topic Discovery from?Spanish Social Media Texts,This approach introduces an analysis based on phrase level as entries for LDA and BTM topic discovery algorithms. An evaluation process has been performed using the coherence topics metric and relevant phrases obtained for discovered topics. The results show encouraging 0.7463 coherence for COVID te

agonist

,Topic Segmentation of?Semi-structured and?Unstructured Conversational Datasets Using Language Modelalance in unstructured conversational datasets. Our empirical evaluation indicates that Focal Loss function is a robust alternative to Cross-Entropy and re-weighted Cross-Entropy loss function when segmenting unstructured and semi-structured chats.

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annexation

Improvement in the Mechanical Design of Mechatronic Devices with Therapeutic Operating Systems,designs that allow us to approach children, easy to transport and manipulate; without affecting the benefits and quality of therapies, i.e. improving hardware in a mechanical-electronic-ICT interaction.

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SPELTRA Focused on Therapies for Children with Special Educational Needs,one; at the same time, identifying the capacities and deficiencies of each of the students; monitors their evolution and reports on their condition and progress, which would guide teachers to inclusive teaching indicating the collective activity to be applied; helping to improve, develop and overcom

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Unmanned Ground Vehicle Navigation Using Artificial Neural Networks,or while simultaneously recording the motor signals. The collected data was sent to the Raspberry Pi through a serial communication port and saved in a file. Second, the collected input-output data was used in MATLAB to train a feed-forward ANN to classify the action of the motors based on the input

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