Problem Of Insufficient Information Research Articles

Learning a Deep Attention Dilated Residual Convolutional Neural Network for Landslide Susceptibility Mapping in Hanzhong City, Shaanxi Province, China

The analysis and evaluation of landslide susceptibility are of great significance in preventing and managing geological hazards. Aiming at the problems of insufficient information caused by the limited number of landslide datasets, complex information of landslide evaluation factors, and low prediction accuracy of landslide susceptibility, a landslide susceptibility evaluation method based on the deep attention dilated residual convolutional neural network (DADRCNN) is proposed. First, the dilated convolution unit (DCU) is used to increase the network receptive field, aggregate multi-scale information, and enhance the model ability to capture the characteristics of landslide evaluation factors. Second, the deep residual module (DRM) is used to solve the issue of gradient disappearance and better extract data features by overlaying the residual function mapping layer and increasing the network depth. Finally, the channel attention residual module (CARM) is introduced to learn the varying importance of different landslide evaluation factors, and assign different weights to improve the susceptibility prediction accuracy. The experimental results show that the DADRCNN method can extract features around the sample points, expand the receptive field, and deeply mine the information. It mitigates the lack of sample information in training, focuses on important feature information, and significantly improves the prediction accuracy.

A grey comprehensive evaluation model for wheat quality incorporating PCA-EWM

The objective and accurate evaluation of wheat quality is the key to ensuring the safety of wheat storage. Due to the complexity and variability of wheat quality, traditional methods, such as the evaluation of single physical and chemical index, have the problems of insufficient information and poor differentiation of fuzzy intervals. Based on grey systems theory, this paper proposes a new comprehensive wheat quality grading model. Firstly, eight physical and chemical indices are selected as the factor set of the evaluation model, and the key quality indices are analyzed and screened by principal component analysis (PCA). The entropy weight method (EWM) is then used to measure the importance of the contribution of selected indices to wheat quality information. Finally, the grey evaluation model is then used to determine the grey correlation of the evaluation levels of different batches of wheat, and to rank the superiority and inferiority. The model is applied to the comprehensive analysis and evaluation of wheat samples, verifying the feasibility and validity of the model and providing some theoretical guidance for the evaluation of wheat quality.

Mapping of Rill Erosion of the Middle Volga (Russia) Region Using Deep Neural Network

Soil erosion worldwide is an intense, poorly controlled process. In many respects, this is a consequence of the lack of up-to-date high-resolution erosion maps. All over the world, the problem of insufficient information is solved in different ways, mainly on a point-by-point basis, within local areas. Extrapolation of the results obtained locally to a more extensive territory produces inevitable uncertainties and errors. For the anthropogenic-developed part of Russia, this problem is especially urgent because the assessment of the intensity of erosion processes, even with the use of erosion models, does not reach the necessary scale due to the lack of all the required global large-scale remote sensing data and the complexity of considering regional features of erosion processes over such vast areas. This study aims to propose a new methodology for large-scale automated mapping of rill erosion networks based on Sentinel-2 data. A LinkNet deep neural network with a DenseNet encoder was used to solve the problem of automated rill erosion mapping. The recognition results for the study area of more than 345,000 sq. km were summarized to a grid of 3037 basins and analyzed to assess the relationship with the main natural-anthropogenic factors. Generalized additive models (GAM) were used to model the dependency of rill erosion density to explore complex relationships. A complex nonlinear relationship between erosion processes and topographic, meteorological, geomorphological, and anthropogenic factors was shown.

ИССЛЕДОВАНИЕ ВЛИЯНИЯ АНИЗОТРОПИИ ПРОНИЦАЕМОСТИ НА РАЗРАБОТКУ МОДЕЛЬНОГО БЛОКА ТЕРРИГЕННОГО НЕФТЕНАСЫЩЕННОГО КОЛЛЕКТОРА В ХОДЕ ГИДРОДИНАМИЧЕСКИХ РАСЧЁТОВ

Актуальность исследования состоит в существовании проблемы недостаточности информации при сборе и анализе геологических и физико-химических свойств разрабатываемых залежей. В частности, такая проблема касается анизотропии проницаемости, значение которой можно узнать первоначально лишь на основе керновых данных, получаемых в результате бурения с керноотборниками. Зачастую данная операция является затратной для недропользователя. Однако при построении геолого-гидродинамической модели величина анизотропии проницаемости является одной из ключевых характеристик пласта и значительно влияет на его поведение. В цели данной работы входило провести подбор оптимального значения вертикальной анизотропии на основе доступных данных и предложить варианты по улучшению существующей системы разработки в ходе гидродинамических расчётов анизотропной модели. Объектом исследования является одно из нефтяных месторождений Томской области, состоящее из терригенных отложений. Особенностью месторождения является его месторасположение в системе сложных локальных поднятий разного порядка. Основной продуктивный коллектор представлен юрскими отложениями, сформировавшимися в регрессивно-трансгрессивную серию осадконакопления и имеющими сложное распределение фильтрационно-емкостных свойств. Методы: изучение особенностей течения флюидов в пористой среде, измерение и подбор значения вертикальной анизотропии проницаемости, а также проведение гидродинамических вычислений с учётом предлагаемых улучшений системы разработки. В результате исследования удалось узнать, что повышение значения вертикальной анизотропии не всегда приводит к увеличению выработки запасов в зоне работы скважины. Так, при значении вертикальной анизотропии 0,5 величина накопленной добычи нефти составила 1,968 млн м3, в то время как для значения 0,86 эта величина равнялась 1,913. Такой результат связан с геологическими особенностями продуктивного пласта и подчеркивает важность влияния анизотропии проницаемости. Кроме этого, выполнены гидродинамические расчёты на изотропной и анизотропной моделях, позволившие выделить оптимальные варианты оптимизации текущей системы разработки. Коэффициент извлечения нефти для изотропной модели составил 23,4 %, а для анизотропной модели – 22,8 % относительно размера извлекаемых геологических запасов. Таким образом, полученная разница в 0,6 % вновь показывает важность явления анизотропии проницаемости и необходимость как можно бо́льшего количества данных.

Computer-assisted Fracture Reduction and Fixation Simulation for Pelvic Fractures

Pelvic disruption is among the most complex injuries in orthopedic surgery because of the complex fracture patterns in the pelvic structure. Traditional preoperative planning using two-dimensional medical images usually encounters the problem of insufficient information for accurate assessment. In our previous work, a preoperative planning system that uses three-dimensional (3D) medical images and models was developed for the pre-surgical assessment, planning, and simulation of pelvic surgery. In this study, two additional functions, namely semi-automatic bone reduction and several types of fixation simulation are proposed to enhance the integrality of the proposed system for clinical applications. Ten clinical cases are presented for feasibility verification. For some of the cases, the surgeon carries out the simulation first, and then performs the surgery using procedures very similar to those in the simulation. The primary contribution of the proposed system is that the surgeon can go through the critical part of the surgery with the proposed 3D planning and simulation to fully understand the fracture pattern and make an appropriate surgical plan beforehand.

Belief systems today

My purpose is to offer an assessment of the scientific legacy of Converse's “Belief Systems” by reviewing five productive lines of research stimulated by his authoritative analysis and unsettling conclusions. First I recount the later life history of Converse's notion of “nonattitudes,” and suggest that as important as nonattitudes are, we should be paying at least as much attention to their opposite: attitudes held with conviction. Second, I argue that the problem of insufficient information that resides at the center of Converse's analysis has not gone away, and that newly fashioned models of information processing offer only partial remedies. Third, I suggest that the concept of the “average voter” is a malicious fiction, as it blinds us to the enormous variation in political attention, interest, and knowledge that characterizes mass publics, in Converse's time as in our own. Fourth, I develop an affirmative aspect of Converse's analysis that has mostly been overlooked: namely, that if ideological reasoning is beyond most citizens’ capacity and interest, they might fall back on a simple and reasonable alternative, which I will call “group‐centrism.” And fifth, I consider the possibility that while the majority of individual citizens falls short of democratic standards, the public as a whole might do rather well.