DNN-Based Approach for Recognition of Human Activity Raw Data in Non-Controlled Environment

2017 ◽  
Author(s):  
Hamdi Amroun ◽  
Mhamed Temkit ◽  
Mehdi Ammi
Keyword(s):  
Human Activity ◽  
Controlled Environment ◽  
Raw Data

scholarly journals AN ADVANCED APPROACH TO RECOGNIZE HUMAN ACTIVITIES VIA DEEP LEARNING

2021 ◽  
Vol 6 (1) ◽  
Author(s):  
Aryan Karn ◽  
Dharm Raj Maurya
Keyword(s):  
Deep Learning ◽  
Human Activity ◽  
Human Activities ◽  
Service Architecture ◽  
Data Set ◽  
Raw Data ◽  
Proposed Model ◽  
Public Data

The study of wearable and handheld sensors recognizing human activity improved our understanding of human behaviours and human objectives. Many academics seek to identify the activities of a user from raw data using the fewest necessary resources. In this article, we propose a network of profound beliefs, a full-service architecture for the recognition of activities (DBN-LSTM). This DBN-LSTM method improves the human predictability of raw data and reduces the complexity of the model as well as the requirement for comprehensive workmanship. A geographically and temporally rich network is CNN-LSTM. Our proposed model for the UCI HAR Public Data Set can achieve 99% accuracy and 92% precision.

scholarly journals Science walks on two legs, but social sciences try to hop on one

2017 ◽  
Vol 39 (1) ◽  
pp. 145-159 ◽  
Author(s):  
Rein Taagepera
Keyword(s):  
Social Sciences ◽  
Social Science ◽  
Human Activity ◽  
The Other ◽  
Individual Factors ◽  
Raw Data ◽  
Logical Models ◽  
Straight Line ◽  
Science Methodology ◽  
Social Science Methodology

Science walks on two legs. One leg consists of asking: How things are? This leads to observation, measurement, graphing, and statistical description. The other leg consists of asking: How things should be, on logical grounds? This leads to logical models that should become quantitatively predictive. Science largely consists of such models, tested with data. Developed science establishes not only connections among individual factors but also connections among these connections. As an illustration, I use laws about human activity I have found. But social sciences often take the lazy road of fitting raw data with a straight line or some fashionable format, unaware of the need to think and build models based on logic, as stressed by Karl Deutsch. As expounded in my Making Social Sciences More Scientific (2008) and Logical Models and Basic Numeracy in Social Sciences, www.psych.ut.ee/stk/Beginners_Logical_Models.pdf , I call for a major widening in social science methodology.

Performance-based validation of the human activity profile

2007 ◽  
Author(s):  
Luci Fuscaldi Teixeira-Salmela ◽  
Sandra J. Olney ◽  
Revathy Devaraj
Keyword(s):  
Human Activity ◽  
Activity Profile

Responsibility for Raw Data.

1962 ◽  
Vol 17 (9) ◽  
pp. 657-658 ◽  
Author(s):  
Leroy Wolins
Keyword(s):  
Raw Data

Ice-free area expansion compounds the non-native species threat to Antarctic terrestrial biodiversity

2019 ◽  
Author(s):  
Grant Duffy ◽  
Jasmine R Lee
Keyword(s):  
Human Activity ◽  
Native Species ◽  
Climate Scenario ◽  
Climatic Environment ◽  
Species Establishment ◽  
Suitable Habitats ◽  
Terrestrial Biodiversity ◽  
A Site ◽  
Area Expansion ◽  
Free Area

Warming across ice-covered regions will result in changes to both the physical and climatic environment, revealing new ice-free habitat and new climatically suitable habitats for non-native species establishment. Recent studies have independently quantified each of these aspects in Antarctica, where ice-free areas form crucial habitat for the majority of terrestrial biodiversity. Here we synthesise projections of Antarctic ice-free area expansion, recent spatial predictions of non-native species risk, and the frequency of human activities to quantify how these facets of anthropogenic change may interact now and in the future. Under a high-emissions future climate scenario, over a quarter of ice-free area and over 80 % of the ~14 thousand km2 of newly uncovered ice-free area could be vulnerable to invasion by one or more of the modelled non-native species by the end of the century. Ice-free areas identified as vulnerable to non-native species establishment were significantly closer to human activity than unsuitable areas were. Furthermore, almost half of the new vulnerable ice-free area is within 20 km of a site of current human activity. The Antarctic Peninsula, where human activity is heavily concentrated, will be at particular risk. The implications of this for conservation values of Antarctica and the management efforts required to mitigate against it are in need of urgent consideration.

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