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Machine Learning

This is a fictional data set, provided by the IBM. These data set contains atmost 30 features of categorical and discreet data. These data are kind of both numerical and text values which help in analysing the employee data from hiring to firing and on boarding to attrition. 

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The main objective of this project is to design and develop a collaborative framework which facilitates real-time tracking of a target person even when GPS signal is not available, while collecting motion data to infer his or her lifestyle and health status. The framework orchestrates a wide range of technologies such as localization technologies, machine learning and AI, sensor data analytics and cloud computing. The overall framework design also takes into consideration the culture, lifestyles, behaviours and infrastructures of ASEAN countries.

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The dataset analyzed in this study is the result of a systematic literature review and a crowdsourced mini-project that aimed to identify and validate metrics relevant to maternal and neonatal healthcare examinations. The study involved a diverse group of participants, including 193 registered medical personnel from reputable institutions and 161 non-medical individuals who were active on various social media platforms related to maternal and neonatal healthcare.

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This dataset is made of the Channel Impulse Response (CIR) data collected in 9 different environments in Ghent city, Belgium. These environments include:

1.  Fourth floor at iGent Tower in the premises of Gent University

2. Zwijnaarde Open Area

3. Stadhuis Street and Nearby

4. Zuid Mall

5. Portus Ganda

6. Sint-Pieters Railway Station

7. Krook library

8. Citadel Park

9. Graffiti Straat

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We build a large-scale dataset for term name generation, which contains the GO terms about Homo sapiens (humankind and yeast). We collect the term ID, term name and the corresponding genes’ ID from \href{http://geneontology.org/}{Gene Ontology Consortium}.

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Cars, mobile phones, and smart home devices already provide automatic speech recognition (ASR) by default. However, human machine interfaces (HMI) in industrial settings, as opposed to consumer settings, operate under different conditions and thus, present different design challenges. Voice control, arguably the most natural form of communication, has the potential to shorten complex command sequences and menu structures in order to directly execute a final command.

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