Multi scale switchable atrous convolution for target detection based on feature pyramid

Repeated observation mechanism can effectively solve the problem of low efficiency of feature extraction. By extracting features for many times to strengthen target features, this paper proposed a multi-scale switchable atrous convolution based on feature pyramid, SPC. The head of the detector adopted pyramid convolution mode, constructs 3-D convolution in the feature pyramid, and detected the same target in different pyramid levels by using the shared convolution with different stride changes, which realized the repeated observation of target features on multi-scale. The module optimized the convolution layer, extracted the features of the same image by convolution check of different sizes, and then selected and integrated the extracted results by using switch function, which effectively expanded the field of view of convolution kernel. In this paper, we choosed retinanet as the baseline network, and improved the loss function of focal loss proposed by retinanet to further solved the problem of unbalanced number of samples and sample distribution in the network model. The proposed method performed well on MS coco data set, improved the average accuracy of 9.8% on the basis of retinanet to 48.9%, and achieved FPS of 5.1 in 1333 * 800 images.

Robust Estimation Method Based on Function Model of Successive Approximation

In measurement practice, the residuals in least squares adjustment usually show various abnormal discrete distributions, including outliers, which is not conducive to the optimization of final measured values. Starting with the physical mechanism of dispersion and outlier of repeated observation errors, this paper puts forward the error correction idea of using the approximate function model of error to approach the actual function model of error step by step, gives a new theoretical method to optimize the final measured values, and proves the effectiveness of the algorithm by the ability of responding to the true values. This new idea is expected to be the ultimate answer of robust estimation theory.

Time Banks as Transient Civic Organizations? Exploring the Dynamics of Decline

Time banks have become a popular type of civic organization constructed to facilitate egalitarian economic exchange through a community-bounded currency. Especially after the recent economic crises in Europe, the rise in the number of time banks has been accompanied by relative transience and sometimes short lifespans. We adopt a relational perspective to explore the dynamics of decline in the civic engagement of a time bank in southern Germany. Using methods of longitudinal social network analysis, we analyze the relational processes and individual trajectories of members within the emerging transaction network over a period of eight years. Rather than explaining why, we have found how relational trajectories of members through a structure of core and periphery have led to creeping decline in activity and membership. Given the repeated observation that time banks and other types of alternative economic practices are often characterized by considerable volatility and potential collapse, relational thinking and network analysis are especially suited to unpacking the underlying relational mechanisms that shape these outcomes of volatility and demise.

Studies on Three-Dimensional (3D) Accuracy Optimization and Repeatability of UAV in Complex Pit-Rim Landforms As Assisted by Oblique Imaging and RTK Positioning

Unmanned Aerial Vehicles (UAVs) are a novel technology for landform investigations, monitoring, as well as evolution analyses of long−term repeated observation. However, impacted by the sophisticated topographic environment, fluctuating terrain and incomplete field observations, significant differences have been found between 3D measurement accuracy and the Digital Surface Model (DSM). In this study, the DJI Phantom 4 RTK UAV was adopted to capture images of complex pit-rim landforms with significant elevation undulations. A repeated observation data acquisition scheme was proposed for a small amount of oblique-view imaging, while an ortho-view observation was conducted. Subsequently, the 3D scenes and DSMs were formed by employing Structure from Motion (SfM) and Multi-View Stereo (MVS) algorithms. Moreover, a comparison and 3D measurement accuracy analysis were conducted based on the internal and external precision by exploiting checkpoint and DSM of Difference (DoD) error analysis methods. As indicated by the results, the 3D scene plane for two imaging types could reach an accuracy of centimeters, whereas the elevation accuracy of the orthophoto dataset alone could only reach the decimeters (0.3049 m). However, only 6.30% of the total image number of oblique images was required to improve the elevation accuracy by one order of magnitude (0.0942 m). (2) An insignificant variation in internal accuracy was reported in oblique imaging-assisted datasets. In particular, SfM-MVS technology exhibited high reproducibility for repeated observations. By changing the number and position of oblique images, the external precision was able to increase effectively, the elevation error distribution was improved to become more concentrated and stable. Accordingly, a repeated observation method only including a few oblique images has been proposed and demonstrated in this study, which could optimize the elevation and improve the accuracy. The research results could provide practical and effective technology reference strategies for geomorphological surveys and repeated observation analyses in sophisticated mountain environments.

Parameter Design and Performance Evaluation of a Large-Swath and High-Resolution Space Camera

A rotary-scan space camera with an area sensor can achieve large width and high-resolution imaging. Designing system parameters properly is important for the application of the rotary-scan space camera. We model the swath, resolution, and overlap rate between frames for such a camera. An optimum algorithm combining the linear weighting method and the Monte Carlo method for system parameter design is proposed based on the model. Then, the performance of the designed system is evaluated using the grid point method. The designed systems can achieve swaths of more than 1000 km and less than 1 m resolution without leakage during the imaging. In the evaluation, the designed system can cover 82.13% of the observation region at the height of 500 km in 6.5 min, and the average repeated observation frequency is 3.26 times per 118 s. The design method is simple and effective in the initial design of the rotary-scan space camera’s system parameters. The system designed can provide “no-leakage and wide coverage by quick scan” and “high-frequency repeated observation over a long visibility period.” This will greatly improve earth observation ability in wide-area search and rescue missions.

Introduction to the Study of Animals

Because the objective of a study will largely determine the methods used, it is essential to define the objectives at the outset. Very broadly, studies may be defined as either extensive and intensive. Extensive studies are carried out over larger areas or longer time periods than intensive studies, and are frequently used to provide information on distribution and abundance for conservation or management programmes. Intensive studies involve the repeated observation of the population of an animal. The different types of population estimates—absolute, relative, and intensity—are described. The estimation of error and confidence intervals, including jackknife and bootstrap techniques, is described.

The GALAH survey: characterization of emission-line stars with spectral modelling using autoencoders

ABSTRACT We present a neural network autoencoder structure that is able to extract essential latent spectral features from observed spectra and then reconstruct a spectrum from those features. Because of the training with a set of unpeculiar spectra, the network is able to reproduce a spectrum of high signal-to-noise ratio that does not show any spectral peculiarities, even if they are present in an observed spectrum. Spectra generated in this manner were used to identify various emission features among spectra acquired by multiple surveys using the HERMES spectrograph at the Anglo-Australian telescope. Emission features were identified by a direct comparison of the observed and generated spectra. Using the described comparison procedure, we discovered 10 364 candidate spectra with varying intensities (from partially filled-in to well above the continuum) of the Hα/Hβ emission component, produced by different physical mechanisms. A fraction of these spectra belong to the repeated observation that shows temporal variability in their emission profile. Among the emission spectra, we find objects that feature contributions from a nearby rarefied gas (identified through the emission of [N ii] and [S ii] lines) that was identified in 4004 spectra, which were not all identified as having Hα emission. The positions of identified emission-line objects coincide with multiple known regions that harbour young stars. Similarly, detected nebular emission spectra coincide with visually prominent nebular clouds observable in the red all-sky photographic composites.

A common explanation of the Hubble tension and anomalous cold spots in the CMB

ABSTRACT The standard cosmological paradigm narrates a reassuring story of a universe currently dominated by an enigmatic dark energy component. Disquietingly, its universal explaining power has recently been challenged by, above all, the ∼4σ tension in the values of the Hubble constant. Another, less studied anomaly is the repeated observation of integrated Sachs–Wolfe (ISW) imprints ∼5× stronger than expected in the Lambda cold dark matter (ΛCDM) model from $R_{\rm v}\gtrsim 100\,\rm {\mathit{ h}^{-1}Mpc }$ superstructures. Here, we show that the inhomogeneous AvERA (Average Expansion Rate Approximation) model of emerging curvature is capable of telling a plausible albeit radically different story that explains both observational anomalies without dark energy. We demonstrate that while stacked imprints of $R_{\rm v}\gtrsim 100\,\rm {\mathit{ h}^{-1}Mpc }$ supervoids in cosmic microwave background (CMB) temperature maps can discriminate between the AvERA and ΛCDM models, their characteristic differences may remain hidden using alternative void definitions and stacking methodologies. Testing the extremes, we then also show that the CMB Cold Spot can plausibly be explained in the AvERA model as an ISW imprint. The coldest spot in the AvERA map is aligned with multiple low-z supervoids with $R_{\rm v}\gtrsim 100\,\rm {\mathit{ h}^{-1}Mpc }$ and central underdensity δ0 ≈ −0.3, resembling the observed large-scale galaxy density field in the Cold Spot area. We hence conclude that the anomalous imprint of supervoids may well be the canary in the coal mine, and existing observational evidence for dark energy should be reinterpreted to further test alternative models.

Evolutionary Response to Resource Deprivation: Parallelism and Nonmonotonicity

Establishing reliable frameworks for predicting unknown outcomes from empirical observations is of great interest to ecologists and evolutionary biologists. Strong predictability in evolutionary responses has been previously demonstrated by the repeated observation of similar phenotypes or genotypes across multiple natural or experimental populations in analogous environments. However, the degree to which evolutionary outcomes can be predicted across environmental gradients, or in fluctuating environments, remains largely unexplored. Presumably, the phenotypic evolution in an intermediate environment could be interpolated from the evolved phenotypes observed in two extreme environments, but this assumption remains to be fully tested. Here, we report on the experimental evolution of Escherichia coli under three nutritional transfer periods: every day, every 10 days, and every 100 days, representing increasing severity in feast/famine cycles. After 900 days of experimental evolution, populations experiencing intermediate durations of starvation had evolved longer times to reach maximum growth rate, smaller colony sizes, higher biofilm formation, and higher mutation rates than populations evolving in the other environmental extremes. Because the intermediately starved populations exhibit significantly high molecular parallelism, these distinct phenotypes are likely due to non-monotonic deterministic forces instead of increased stochastic forces commonly associated with fluctuating environments. Our results demonstrate novel complexities associated with evolutionary predictability across environmental gradients and highlight the risk of using interpolation in evolutionary biology.

Population parameter Population parameters and bio-exploitation status of Indian Mackerel (Rastrelliger kanagurta Cuvier, 1816) in Mayalibit Bay, Raja Ampat, Indonesia

Oktaviani D, Triharyuni S, Nugroho D. Population parameters and bio-exploitation status of Indian mackerel (Rastrelliger kanagurta Cuvier, 1816) in Mayalibit Bay, Raja Ampat, Indonesia. Biodiversitas 20: 3545-3552. A small-scale fishery in Mayalibit bay, Raja Ampat is one among rare fisheries systems existing in Indonesia. The area already designated as a conservation zone, and Indian mackerel is the main target species by fishers. This species plays a significant role in supplying domestic food. Fisher harvest with a small wooden boat, no engine, one-night fishing using Petro-lamp, and harvested with a scoop net. Monthly based biological observations on population parameters were carried out from March 2011 to April 2012. The result shows that the fish landed with size from 10.0 to 27.0 cm, and 70% of the sample is within 21-23 cm length. Monthly length-weight relationships indicate b value statistically equal to 3. The average unsexed Fulton condition factor index is 1.516 + 0.13 and illustrates the fishes were in suitable environmental conditions. The growth rate (K) is estimated at 0.97, while length infinity (L∞) is 28.4 cm. To evaluate the fishery, repeated observation of fishing in Mayalibit bay conducted in 2016. A productivity and susceptibility analysis was applied to predict its bio-exploitation status, and the results indicate that harvest levels are relatively at low-to-medium risk. Nevertheless, most of the fish caught in the bay by traditional knowledge consisted of mature cohorts while limited desk study to semi-industrial fishing targetted the same species in surrounding waters indicated that a significant proportion of undersize or immature individuals are in their landing. This phenomenon suggested that managing the existing local knowledge could significantly contribute to maintaining sustainable spawning stocks in the conservation zone.