AIS Data as Trajectories and Heat Maps

BACKGROUND The 2019 coronavirus pandemic (COVID-19) has led to increase in global awareness of related public health preventive measures. The public awareness can be reflected by online searching trends of major search engines, namely Google Trends. OBJECTIVE This study aims to interpret online searches of COVID-19 related public health preventive measures and to identify possible correlations between early search trends and progression of the pandemic. METHODS Search data from five queries “Mask”, “Hand Washing”, “Social Distancing”, “Hand Sanitizer”, and “Disinfectant” were extracted from Google Trends (GT) in the form of Relative Search Volumes (RSV). Global incidence data of COVID-19 was obtained from January 1st to June 30th 2020. Subsequently, the data were analyzed and illustrated in forms of a global temporal RSV trend diagram, a geographical RSV distribution chart, scatter graphs comparing regional RSV with average daily cases; and heat-maps comparing temporal trend of RSV with average daily cases. RESULTS Global temporal trend revealed multiple surges in RSV, which were temporally associated with certain COVID news events. Geographical distribution showed differences of query interests among regions. Although scatter graphs failed to illustrate strong correlations between regional RSV and average daily cases, the heat-maps were able to demonstrate patterns of early RSV peaks in countries with lower average daily cases, for queries “Mask”, “Hand Sanitizer”, and “Disinfectant”, upon incorporating with the temporal element into analysis. CONCLUSIONS Early public awareness of multiple preventive measures was observed in countries with lower daily average cases. Public health authorities may look into early public awareness as an effective measure for future disease control.

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SEDIMENT DISPERSAL HEAT MAPS FOR INTERPRETING PROVENANCE: INSIGHTS INTO NORTH AMERICAN SEDIMENTATION AND TECTONISM

10.1130/abs/2019am-340740 ◽

2019 ◽

Author(s):

Jordan D. Cruzan ◽

◽

Matthew P. McKay

Keyword(s):

North American ◽

Heat Maps ◽

Sediment Dispersal

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Approximate Cluster Heat Maps of Large High-Dimensional Data

2018 24th International Conference on Pattern Recognition (ICPR) ◽

10.1109/icpr.2018.8545519 ◽

2018 ◽

Cited By ~ 1

Author(s):

Punit Rathore ◽

James C. Bezdek ◽

Dheeraj Kumar ◽

Sutharshan Rajasegarar ◽

Marimuthu Palaniswami

Keyword(s):

High Dimensional Data ◽

High Dimensional ◽

Heat Maps

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Capacity Heat Maps for Millimeter Waves

2020 International Symposium on Networks, Computers and Communications (ISNCC) ◽

10.1109/isncc49221.2020.9297266 ◽

2020 ◽

Author(s):

Gabriela Sobreira de Carvalho ◽

Marcelo Sampaio de Alencar ◽

Raissa Bezerra Rocha

Keyword(s):

Millimeter Waves ◽

Heat Maps

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Hybrid Deep Learning Model Based Indoor Positioning Using Wi-Fi RSSI Heat Maps for Autonomous Applications

Electronics ◽

10.3390/electronics10010002 ◽

2020 ◽

Vol 10 (1) ◽

pp. 2

Author(s):

Alwin Poulose ◽

Dong Seog Han

Keyword(s):

Deep Learning ◽

Signal Strength ◽

Indoor Positioning ◽

Learning Model ◽

Signal Interference ◽

Positioning System ◽

Heat Maps ◽

Positioning Systems ◽

Localization Performance ◽

Deep Learning Model

Positioning using Wi-Fi received signal strength indication (RSSI) signals is an effective method for identifying the user positions in an indoor scenario. Wi-Fi RSSI signals in an autonomous system can be easily used for vehicle tracking in underground parking. In Wi-Fi RSSI signal based positioning, the positioning system estimates the signal strength of the access points (APs) to the receiver and identifies the user’s indoor positions. The existing Wi-Fi RSSI based positioning systems use raw RSSI signals obtained from APs and estimate the user positions. These raw RSSI signals can easily fluctuate and be interfered with by the indoor channel conditions. This signal interference in the indoor channel condition reduces localization performance of these existing Wi-Fi RSSI signal based positioning systems. To enhance their performance and reduce the positioning error, we propose a hybrid deep learning model (HDLM) based indoor positioning system. The proposed HDLM based positioning system uses RSSI heat maps instead of raw RSSI signals from APs. This results in better localization performance for Wi-Fi RSSI signal based positioning systems. When compared to the existing Wi-Fi RSSI based positioning technologies such as fingerprint, trilateration, and Wi-Fi fusion approaches, the proposed approach achieves reasonably better positioning results for indoor localization. The experiment results show that a combination of convolutional neural network and long short-term memory network (CNN-LSTM) used in the proposed HDLM outperforms other deep learning models and gives a smaller localization error than conventional Wi-Fi RSSI signal based localization approaches. From the experiment result analysis, the proposed system can be easily implemented for autonomous applications.

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Eye Movements as a Means to Evaluate Operation Interface of Flat Knitting Machine

Applied Mechanics and Materials ◽

10.4028/www.scientific.net/amm.607.664 ◽

2014 ◽

Vol 607 ◽

pp. 664-668

Author(s):

Zhi Hui Liu ◽

Sheng Ze Wang ◽

Qiong Shen ◽

Jia Jun Feng

Keyword(s):

Eye Movements ◽

Eye Movement ◽

Objective Evaluation ◽

Layout Design ◽

Eye Tracker ◽

Heat Maps ◽

Machine Operation

This study investigates the characteristics of eye movements by operating flat knitting machine. For the objective evaluation purpose of the flat knitting machine operation interface, we arrange participants finish operation tasks on the interface, then use eye tracker to analyze and evaluate the layout design. Through testing of the different layout designs, we get fixation sequences, the count of fixation, heat maps, and fixation length. The results showed that the layout design could significantly affect the eye-movement, especially the fixation sequences and the heat maps, the count of fixation and fixation length are always impacted by operation tasks. Overall, data obtained from eye movements can not only be used to evaluate the operation interface, but also significantly enhance the layout design of the flat knitting machine.

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Heat maps

Nature Methods ◽

10.1038/nmeth.1902 ◽

2012 ◽

Vol 9 (3) ◽

pp. 213-213 ◽

Cited By ~ 39

Author(s):

Nils Gehlenborg ◽

Bang Wong

Keyword(s):

Heat Maps

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Eye tracking and tourism research: A systematic literature review

Journal Of Vacation Marketing ◽

10.1177/13567667211053387 ◽

2021 ◽

pp. 135676672110533

Author(s):

Georgiana-Denisse Savin ◽

Cristina Fleșeriu ◽

Larissa Batrancea

Keyword(s):

Eye Tracking ◽

Tracking Data ◽

Research Papers ◽

Research Directions ◽

Heat Maps ◽

Tourism Research ◽

Dynamic Stimuli ◽

Tracking Technique ◽

The Subject ◽

Practical Implications

In recent years, the number of studies in tourism using the eye tracking technique has increased and started generating valuable information for both academics and the industry. However, there is a gap in the literature concerning systematic reviews focused on recent articles and their findings. Thus, the aim of this study is to close this gap by systematically analysing 70 research papers tackling the subject of eye tracking in tourism and published in highly ranked tourism journals. The study identifies the most popular topics and trends for eye tracking research, as well as the most used types of visual stimuli, such as exhibitions, restaurant menus, promotional pictures or websites. The study also details on measurements specific for the analysis of eye tracking data, including fixations, saccades and heat maps. Results are emphasized along with their theoretical and practical implications. In addition, we highlight the lack of the use of dynamic stimuli in the existing literature and suggest further research directions using the eye tracking technique.

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