Spatiotemporal Characterization of VIIRS Night Light

The Visible Infrared Imaging Radiometer Suite (VIIRS) Day Night Band (DNB) on board the Suomi NPP satellite now provides almost a decade of daily observations of night light. The temporal frequency of sampling, without the degree of temporal averaging of annual composites, makes it necessary to consider the distinction between apparent temporal changes of night light related to the imaging process and actual changes in the underlying sources of the night light being imaged. The most common approach to night light change detection involves direct attribution of observed changes to the phenomenon of interest. Implicit in this approach is the assumption that other forms of actual and apparent change in the light source are negligible or non-existent. An alternative approach is to characterize the spatiotemporal variability prior to deductive attribution of causation so that the attribution can be made in the context of the full range of spatial and temporal variation. The primary objective of this study is to characterize night light variability over a range of spatial and temporal scales to provide a context for interpretation of night light changes observed on both subannual and interannual time scales. This analysis is based on a combination of temporal moments, spatial correlation and Empirical Orthogonal Function (EOF) analysis. A key result of this study is the pervasive heteroskedasticity of VIIRS monthly mean night light. Specifically, the monotonic decrease of variability with increasing mean brightness. Anthropogenic night light is remarkably stable on subannual time scales while background luminance varies considerably. The variance partition from the eigenvalues of the spatiotemporal covariance matrix are 88, 2 and 2% for spatial, seasonal and interannual variance (respectively) in the most diverse region on Earth (Eurasia). Heteroskedasticity is pervasive in the monthly composites; present in all areas for all months of the year, suggesting that much, if not most, of the month-to-month variability may be related to luminance of otherwise stable sources subjected to multiple aspects of the imaging process varying in time. Given the skewed distribution of all night light arising from radial peripheral dimming of bright sources subject to atmospheric scattering, even aggregate metrics using thresholds must be interpreted in light of the fact that much larger numbers of more variable low luminance pixels may statistically overwhelm smaller numbers of stable higher luminance pixels and cause apparent changes related to the imaging process to be interpreted as actual changes in the light sources.

Research on Multimodal Music Emotion Recognition Method Based on Image Sequence

The work of music performance system is to control the light change by identifying the emotional elements of music. Therefore, once the identification error occurs, it will not be able to create a good stage effect. Therefore, a multimodal music emotion recognition method based on image sequence is studied. The emotional characteristics of music are analyzed, including acoustic characteristics, melody characteristics, and audio characteristics, and the feature vector is constructed. The recognition and classification model based on neural network is trained, the weight and threshold of each layer are adjusted, and then the feature vector is input into the trained model to realize the intelligent recognition and classification of multimodal music emotion. The threshold of the starting point range of a specific humming note is given by the center clipping method, which is used to eliminate the low amplitude part of the humming note signal, extract the short-time spectral structure features and envelope features of the pitch, and complete the multimodal music emotion recognition. The results show that the calculated kappa coefficient k is greater than 0.75, which shows that the recognition and classification results are in good agreement with the actual results, and the classification and recognition accuracy is high.

The use of optical fiber for the creation of security systems for electrical cables of distribution networks of 0.4 kV

The article presents the results of research aimed at solving important production issues related to the theft of power cables and reducing the reliability of electrical networks with a voltage of 0.4 kV. To implement the security system, a single-mode optical fiber and a hardware and software complex for data processing were used. The results of the work can be used in security systems for various purposes, including telecommunications and construction systems. During the experiments, it was found that the photoelasticity effect occurs during mechanical action on the optical fiber, which causes changes in the refractive indices of the shell and core, while the properties of light change. In contrast to the known security systems and methods of fixing violations, a high-resolution television matrix is used, and not a photodetector device that records only changes in intensity. The television matrix is installed at the output of the optical fiber and records all changes in the light spot, and the hardware and software complex converts these changes into numerical values.

Semiotic Interpretation of the Traffic Light System: A Way to Influence Road Accidents

This work is part of a larger research that involves the science of semiotics in order to study road infrastructure (road devices) in road crossings, using the theoretical contributions of Ferdinand de Saussure, Umberto Eco and Charles Sanders Peirce, with the purpose to support the safe mobility of citizens. Pedestrians use the roads for work, study, recreation, and other activities of daily living providing a harmonious and safe way for people to move either on foot, by car, bicycle, public or private transport services. One of these road devices is the traffic light system used to control road traffic at an intersection or road junction. This system's optimal and safe operation is related to the infrastructure of the urban space, which results in safe or unsafe mobility for pedestrians. In this sense, the semiotic interpretation of the state transition diagram for a traffic light system (green-amber-red / red-amber-green light change) is being proposed to recognize whether the road may be a dangerous place for users. The research aims to propose an improvement in pedestrians' conditions to reduce traffic accidents in the most conflictive and dangerous road intersections. These places were determined by the Secretaría de Salud (2012) and disclosed in its Second Report on the Situation of Road Safety in Mexico City.

Improved Algorithm of the Video Moving Object Detection Based on ViBE

Background: ViBE (Visual Background Extractor) is an algorithm with a variety of advantages in video moving object detection which utilizes a pixel-level background modeling. However, it is not suitable for distinguishing the scene of drastic change, adapts poorly to the sudden change of the illumination and may lost the object easily, because this algorithm uses a fixed threshold to distinguish the background from the foreground. Methods: In this paper, an improved ViBE algorithm is proposed, which an adaptive dynamic threshold method is introduced for classification of the foreground and the background in the changing scenes. When reconstructing the model it required for drastic change of illumination, Otsu algorithm is used to judge the threshold and select the appropriate frame to complete the reconstruction to achieve quick adapt to the light. Results: Experimental results show that the proposed algorithm has higher recall value, better precision and F value comparing to the original algorithm. The improved algorithm has the highest classification accuracy among other similar algorithms and therefore the improved algorithm significantly improves the detection results. Conclusion: After analyzing the principle of ViBE algorithm, this paper proposed improvements to it from two aspects to aim at its deficiency. Taking into account of the dynamic changes of different environments, the change factor was proposed to measure the dynamic degree of background. According to the value of the factor, adaptive clustering was obtained and clustering threshold was updated to improve the adaptability of the algorithm to the dynamic environments. The improved ViBE algorithm can find the appropriate frame to reconstruct model structure in the case of abrupt light change, which can quickly adapt itself to the light change and be more accurate in the object detection.

Global Nighttime Light Change from 1992 to 2017: Brighter and More Uniform

Nighttime light images record the brightness of the Earth surface, indicating the scope and intensity of human activities. However, there are few studies on the long-term changes in global nighttime lights. In this paper, the authors constructed a long time series (1992~2017) nighttime light dataset combining the Defense Meteorological Satellites Program/Operational Linescan System (DMSP-OLS) and the Suomi National Polar-Orbiting Partnership Visible Infrared Imaging Radiometer Suite (NPP-VIIRS) data sources and observed the following: (1) Global nighttime lights have become brighter. The global nighttime brightness in 2017 was 2.2 times that of 1992. Approximately 40.3% of the lighted area was significantly brightened, and an area of 1.3 × 107 km2 transitioned from an unlighted area to a lighted area. (2) Approximately 85.7% of the nighttime light increase occurred in the low-brightness zone (LBZ). Therefore, global brightness has become more uniform than before. (3) China, India, and the United States have led the global lighting trend. The increase in Chinese nighttime lights is the largest, with an average annual growth of 6.48%, followed by the light growth in India, while the United States has the largest brightened area. (4) The changes in nighttime lights in developing countries (e.g., China and India) are closely and positively related to their electricity consumption, industrial added value and gross domestic product (GDP). The shift of the LBZ center from Asia to Africa indicates the intercontinental transition of poverty.

Repetitive mild traumatic brain injury alters diurnal locomotor activity and response to the light change in mice

Mild traumatic brain injury (mTBI) is a common cause of brain damage with a high incidence of multiple mTBIs found among athletes and soldiers. The purpose of this study is to examine the diurnal behavioral changes after multiple mTBIs. Adult mice were anesthetized; mTBI was conducted by dropping a 30-g weight to the right temporal skull once (mTBI1) or three times (mTBI3) over 3-week. Open-field motor behavior was recorded for 3 days after the last mTBI. In the first 4-hour exploratory phase, mTBI1 or mTBI3 equally reduced locomotor activity. A significant reduction of locomotor activity was found in the dark cycle between 4–72 hour in mTBI1 or mTBI3 mice; higher motor activity was seen after mTBI3 compared to mTBI1. In the light cycle, mTBI3 mice demonstrated an earlier immobilization followed by hyperactivity. The response to light change significantly correlated with the number of impacts. The IBA1 and BAX protein levels were equally increased in the lesioned cortex after mTBI1 and mTBI3. mTBI3 selectively upregulated the expression of circadian clock gene Per1 in hypothalamus and hippocampus as well as iNOS expression in the lesioned side cortex. Our data suggest multiple mTBIs alter diurnal locomotor activity and response to the change of light, which may involve Per1 expression in the lesioned brain.

Photonic Crystal Characterization of the Cuticles of Chrysina chrysargyrea and Chrysina optima Jewel Scarab Beetles

A unified description involving structural morphology and composition, dispersion of optical constants, modeled and measured reflection spectra and photonic crystal characterization is devised. Light reflection spectra by the cuticles of scarab beetles (Chrysina chrysargyrea and Chrysina optima), measured in the wavelength range 300–1000 nm, show spectrally structured broad bands. Scanning electron microscopy analysis shows that the pitches of the twisted structures responsible for the left-handed circularly polarized reflected light change monotonically with depth through the cuticles, making it possible to obtain the explicit depth-dependence for each cuticle arrangement considered. This variation is a key aspect, and it will be introduced in the context of Berreman’s formalism, which allows us to evaluate reflection spectra whose main features coincide in those displayed in measurements. Through the dispersion relation obtained from the Helmholtz’s equation satisfied by the circular components of the propagating fields, the presence of a photonic band gap is established for each case considered. These band gaps depend on depth through the cuticle, and their spectral positions change with depth. This explains the presence of broad bands in the reflection spectra, and their spectral features correlate with details in the variation of the pitch with depth. The twisted structures consist of chitin nanofibrils whose optical anisotropy is not large enough so as to be approached from modeling the measured reflection spectra. The presence of a high birefringence substance embedded in the chitin matrix is required. In this sense, the presence of uric acid crystallites through the cuticle is strongly suggested by frustrated attenuated total reflection and Raman spectroscopy analysis. The complete optical modeling is performed incorporating the wavelength-dependent optical constants of chitin and uric acid.

A Face Tracking Method in Videos Based on Convolutional Neural Networks

Face tracking in surveillance videos is one of the important issues in the field of computer vision and has realistic significance. In this paper, a new face tracking framework in videos based on convolutional neural networks (CNNs) and Kalman filter algorithm is proposed. The framework uses a rough-to-fine CNN to detect faces in each frame of the video. The rough-to-fine CNN method has a higher accuracy in complex scenes such as face rotation, light change and occlusion. When face tracking fails due to severe occlusion or significant rotation, the framework uses Kalman filter to predict face position. The experimental results show that the proposed method has high precision and fast processing speed.