scholarly journals Detecting and Influencing Driver Emotions Using Psycho-Physiological Sensors and Ambient Light

2019 ◽  
pp. 721-742
Author(s):  
Mariam Hassib ◽  
Michael Braun ◽  
Bastian Pfleging ◽  
Florian Alt
Keyword(s):  
Ambient Light ◽  
Physiological Sensors

Recent Developments of Ambulatory Assessment Methods

2014 ◽  
Vol 25 (4) ◽  
pp. 279-287 ◽  
Author(s):  
Stefan Hey ◽  
Panagiota Anastasopoulou ◽  
André Bideaux ◽  
Wilhelm Stork
Keyword(s):  
Real Time ◽  
Information And Communication Technologies ◽  
New Technologies ◽  
Psychological Research ◽  
Ambulatory Assessment ◽  
Emotional States ◽  
Recent Developments ◽  
Potential Applications ◽  
Information And Communication ◽  
Physiological Sensors

Ambulatory assessment of emotional states as well as psychophysiological, cognitive and behavioral reactions constitutes an approach, which is increasingly being used in psychological research. Due to new developments in the field of information and communication technologies and an improved application of mobile physiological sensors, various new systems have been introduced. Methods of experience sampling allow to assess dynamic changes of subjective evaluations in real time and new sensor technologies permit a measurement of physiological responses. In addition, new technologies facilitate the interactive assessment of subjective, physiological, and behavioral data in real-time. Here, we describe these recent developments from the perspective of engineering science and discuss potential applications in the field of neuropsychology.

Design, Development and Practical Realization of a VLC Supportive Indoor Lighting System

2020 ◽  
pp. 87-97
Author(s):  
Sourish Chatterjee ◽  
Biswanath Roy
Keyword(s):  
Data Communication ◽  
Cost Effective ◽  
Ambient Light ◽  
Lighting System ◽  
Design Development ◽  
Led Driver ◽  
Communication Performance ◽  
Good Communication ◽  
Simulink Model ◽  
Light Interference

In an office space, an LED-based lighting system allows you to perform the function of a data transmitter. This article discusses the cost-effective design and development of a data-enabled LED driver that can transmit data along with its receiving part. In addition, this paper clearly outlines the application of the proposed VLC system in an office environment where ambient light interference is a severe issue of concern. The result shows satisfactory lighting characteristics in general for this area in terms of average horizontal illuminance and illuminance uniformity. At the same time, to evaluate real-time and static communication performance, Arduino interfaced MATLAB Simulink model is developed, which shows good communication performance in terms of BER (10–7) even in presence of ambient light noise with 6 dB signal to interference plus noise ratio. Our designed system is also flexible to work as a standalone lighting system, whenever data communication is not required.

Integrated Ambient Light Sensor with an LTPS Noise-Robust Circuit and a-Si Photodiodes for AMLCDs

2010 ◽  
Vol E93-C (11) ◽  
pp. 1583-1589
Author(s):  
Fumirou MATSUKI ◽  
Kazuyuki HASHIMOTO ◽  
Keiichi SANO ◽  
Fu-Yuan HSUEH ◽  
Ramesh KAKKAD ◽  
...  
Keyword(s):  
Ambient Light ◽  
Light Sensor ◽  
Noise Robust

An LTPS Ambient Light Sensor System with Sensitivity Correction Methods in LCD

2019 ◽  
Vol E102.C (7) ◽  
pp. 558-564
Author(s):  
Takashi NAKAMURA ◽  
Masahiro TADA ◽  
Hiroyuki KIMURA
Keyword(s):  
Sensor System ◽  
Ambient Light ◽  
Light Sensor

scholarly journals CorrNet: Fine-Grained Emotion Recognition for Video Watching Using Wearable Physiological Sensors

Sensors ◽  
2020 ◽  
Vol 21 (1) ◽  
pp. 52
Author(s):  
Tianyi Zhang ◽  
Abdallah El Ali ◽  
Chen Wang ◽  
Alan Hanjalic ◽  
Pablo Cesar
Keyword(s):  
Emotion Recognition ◽  
Electrodermal Activity ◽  
Short Form ◽  
Recognition Performance ◽  
Binary Classification ◽  
Wearable Sensors ◽  
Recognition Algorithm ◽  
Fine Grained ◽  
Physiological Sensors ◽  
Valence And Arousal

Recognizing user emotions while they watch short-form videos anytime and anywhere is essential for facilitating video content customization and personalization. However, most works either classify a single emotion per video stimuli, or are restricted to static, desktop environments. To address this, we propose a correlation-based emotion recognition algorithm (CorrNet) to recognize the valence and arousal (V-A) of each instance (fine-grained segment of signals) using only wearable, physiological signals (e.g., electrodermal activity, heart rate). CorrNet takes advantage of features both inside each instance (intra-modality features) and between different instances for the same video stimuli (correlation-based features). We first test our approach on an indoor-desktop affect dataset (CASE), and thereafter on an outdoor-mobile affect dataset (MERCA) which we collected using a smart wristband and wearable eyetracker. Results show that for subject-independent binary classification (high-low), CorrNet yields promising recognition accuracies: 76.37% and 74.03% for V-A on CASE, and 70.29% and 68.15% for V-A on MERCA. Our findings show: (1) instance segment lengths between 1–4 s result in highest recognition accuracies (2) accuracies between laboratory-grade and wearable sensors are comparable, even under low sampling rates (≤64 Hz) (3) large amounts of neutral V-A labels, an artifact of continuous affect annotation, result in varied recognition performance.

scholarly journals Performance of a Handheld Chlorophyll-a Fluorometer: Potential Use for Rapid Algae Monitoring

Water ◽  
2021 ◽  
Vol 13 (10) ◽  
pp. 1409
Author(s):  
Hamdhani Hamdhani ◽  
Drew E. Eppehimer ◽  
David Walker ◽  
Michael T. Bogan
Keyword(s):  
Chlorophyll A ◽  
Surface Waters ◽  
Harmful Algal Blooms ◽  
Algal Blooms ◽  
Water Quality Monitoring ◽  
Ambient Light ◽  
Calibration Equation ◽  
Field Samples ◽  
Potential Use

Chlorophyll-a measurements are an important factor in the water quality monitoring of surface waters, especially for determining the trophic status and ecosystem management. However, a collection of field samples for extractive analysis in a laboratory may not fully represent the field conditions. Handheld fluorometers that can measure chlorophyll-a in situ are available, but their performance in waters with a variety of potential light-interfering substances has not yet been tested. We tested a handheld fluorometer for sensitivity to ambient light and turbidity and compared these findings with EPA Method 445.0 using water samples obtained from two urban lakes in Tucson, Arizona, USA. Our results suggested that the probe was not sensitive to ambient light and performed well at low chlorophyll-a concentrations (<25 µg/L) across a range of turbidity levels (50–70 NTU). However, the performance was lower when the chlorophyll-a concentrations were >25 µg/L and turbidity levels were <50 NTU. To account for this discrepancy, we developed a calibration equation to use for this handheld fluorometer when field monitoring for potential harmful algal blooms in water bodies.

Traffic and speed characteristics on two-lane highways: field study

2003 ◽  
Vol 30 (6) ◽  
pp. 1042-1054 ◽  
Author(s):  
Yasser Hassan
Keyword(s):  
Light Condition ◽  
Operating Speed ◽  
Ambient Light ◽  
Horizontal Curve ◽  
Vehicle Class ◽  
Rural Highways ◽  
Horizontal Alignment ◽  
Heavy Truck ◽  
Traffic Composition ◽  
Rural Highway

Many models have been developed to evaluate the operating speeds on two-lane rural highways. However, provided information usually lacks details essential to assess their applicability at locations other than where they were developed. This paper presents a procedure to interpret raw data collected on three horizontal curve sites of different two-lane rural highway classes in Ontario. The speed observations were categorized into three vehicle classes (passenger car, light truck, and multi-axle heavy truck) and four light condition categories (day, night, and two transition periods). The minimum headway and percentile value to define the operating speed were examined, and a revision of the current practice deemed not warranted. The findings also indicated that operating speeds do not depend on the time or vehicle class. Finally, the horizontal alignment affects the operating speed, but the speeds of the two travel directions on a horizontal curve may differ even with little contribution of the vertical alignment.Key words: highway geometric design, operating speed, traffic composition, traffic counters, ambient light, acceleration, deceleration.

scholarly journals ShadingNet: Image Intrinsics by Fine-Grained Shading Decomposition

2021 ◽  
Author(s):  
Anil S. Baslamisli ◽  
Partha Das ◽  
Hoang-An Le ◽  
Sezer Karaoglu ◽  
Theo Gevers
Keyword(s):  
Neural Network ◽  
Large Scale ◽  
State Of The Art ◽  
Image Decomposition ◽  
Natural Environments ◽  
Decomposition Algorithms ◽  
Ambient Light ◽  
Fine Grained ◽  
Large Scale Dataset ◽  
Direct Illumination

AbstractIn general, intrinsic image decomposition algorithms interpret shading as one unified component including all photometric effects. As shading transitions are generally smoother than reflectance (albedo) changes, these methods may fail in distinguishing strong photometric effects from reflectance variations. Therefore, in this paper, we propose to decompose the shading component into direct (illumination) and indirect shading (ambient light and shadows) subcomponents. The aim is to distinguish strong photometric effects from reflectance variations. An end-to-end deep convolutional neural network (ShadingNet) is proposed that operates in a fine-to-coarse manner with a specialized fusion and refinement unit exploiting the fine-grained shading model. It is designed to learn specific reflectance cues separated from specific photometric effects to analyze the disentanglement capability. A large-scale dataset of scene-level synthetic images of outdoor natural environments is provided with fine-grained intrinsic image ground-truths. Large scale experiments show that our approach using fine-grained shading decompositions outperforms state-of-the-art algorithms utilizing unified shading on NED, MPI Sintel, GTA V, IIW, MIT Intrinsic Images, 3DRMS and SRD datasets.

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