Hierarchical Approach to Identifying Fluid Flow Models in a Heterogeneous Porous Medium

A three-dimensional numerical hydrodynamic model fairly accurately describes the processes of developing oil and gas fields, and has good predictive properties only if there are high-quality input data and comprehensive information about the reservoir. However, under conditions of high uncertainty of the input data, measurement errors, significant time and resource costs for processing and analyzing large amounts of data, the use of such models may be unreasonable and can lead to ill-posed problems: either the uniqueness of the solution or its stability is violated. A well-known method for dealing with these problems is regularization or the method of adding some additional a priori information. In contrast to full-scale modeling, currently there is active development of reduced-physics models, which are used, first of all, in conditions when it is required to make an operational decision, and computational resources are limited. One of the most popular simplified models is the material balance model, which makes it possible to directly capture the relationship between reservoir pressure, flow rates and the integral reservoir characteristics. In this paper, it is proposed to consider a hierarchical approach when solving the problem of oil field waterflooding control using material balance models in successive approximations: first for the field as a whole, then for hydrodynamically connected blocks of the field, then for wells. When moving from one level of model detailing to the next, the modeling results from the previous levels of the hierarchy are used in the form of additional regularizing information, which ultimately makes it possible to correctly solve the history matching problem (identification of the filtration model) in conditions of incomplete input information.

Sterling Brown’s Laughter Out of Hell

Brown’s sense of humor provides guiding principles for real-world action while making the Black tradition of private anti-racist laughter public. Brown examines the violence of traditional superiority humor in poems like “Sam Smiley,” in which Black laughter is silenced by lynching. Rather than simply rejecting such humor, Brown gives readers alternatives: his anti-hierarchical approach in the “Slim Greer” poems inverts Bergson’s logic, making humor a precondition for empathy. The partial resemblance we see between ourselves and the object of laughter can teach us to recognize our commonality even with our enemies. For Brown, the ethical underpinnings of art lie in artists’ awareness of contingency, complexity, and the subjectivities of unlike others. Empathic humor turns laughter from a zero-sum game to a game everyone can win by rejecting not just racism but hierarchical thinking as a whole. Brown shows how empathic laughter can reframe our knowledge of other people and upend the way we systematize that knowledge.

Psychosocial Features for Identifying Hate Speech in Social Media Text

This study uses natural language processing to identify hate speech in social media codeswitched text. It trains nine models and tests their predictiveness in recognizing hate speech in a 50k human-annotated dataset. The article proposes a novel hierarchical approach that leverages Latent Dirichlet Analysis to develop topic models that assist build a high-level Psychosocial feature set we call PDC. PDC organizes words into word families, which helps capture codeswitching during preprocessing for supervised learning models. Informed by the duplex theory of hate, the PDC features are based on a hate speech annotation framework. Frequency-based models employing the PDC feature on tweets from the 2012 and 2017 Kenyan presidential elections yielded an f-score of 83 percent (precision: 81 percent, recall: 85 percent) in recognizing hate speech. The study is notable because it publicly exposes a rich codeswitched dataset for comparative studies. Second, it describes how to create a novel PDC feature set to detect subtle types of hate speech hidden in codeswitched data that previous approaches could not detect.

Customer Co-creation: An Insight on its Influence on Customer Loyalty in the Cosmetic Industry

This article deals with the impact on customer loyalty through the implementation of customer co-creation campaigns in the beauty industry, also referred to as the cosmetic industry; while additionally featuring central points that add to the ability and willingness of a customer to partake in these co-creation campaigns. Co-creation refers to the practice deviced by organizations to team up with their stakeholders during the planning, advancing, and implementing stages of their products and services. “It replaces the hierarchical approach to management and the linear approach to innovation, affording all stakeholders the possibility to influence and bring forth meaningful and relevant solutions in a collaborative environment” (Kirah, A 2009). An exploratory survey was conducted to collect data from 229 respondents, through questionnaires. All the respondents were users of cosmetic products, irrespective of gender; living in the cities of Bangalore and Mysore. Mean, Standard Deviation, Correlation and Factor Analysis were used to analyse the acquired data, and study the outcomes. The findings of the study suggest that the customer co-creation campaigns have a favorable impact on customer loyalty, ultimately resulting in higher customer retention rates. The study also confirms various factors contributing to a customer’s participation in the co-creation campaign.

Coordination of Movements of Two-Handed 12-DOF Robot Manipulators at Their Joint Manipulation

The study focuses on a two-handed robot with twelve degrees of freedom, six for each arm, and gives an example of calculating generalized coordinates for the two-armed robot limbs at their joint manipulation. The initial data for obtaining generalized coordinates are represented by the location of the work object, which is a cube. When solving the problem, the last arm links reach the faces of the work object with a given orientation. To obtain generalized coordinates, we used a hierarchical approach, which is based on an algorithm for solving the inverse problem of kinematics, and developed a control flow chart. The values ??of generalized robot coordinates were obtained for each location of the object of work, taking into account the kinematic constraints in the joints of the robot actuator. Findings of research show that it is possible to obtain generalized coordinates for the coordinated movement of the robot actuators with tree-like kinematic scheme.

COVID-19: a decision-making approach for evaluating the economic sectors of india during pandemic

The advent of COVID-19 has escalated into a pandemic and, as a result of infected cases and human fatalities, it tends to rise day by day across the globe. This also ignited concerns of a looming fiscal slump and recession on the different economic sectors as well. The effect of this pandemic is much more significant in developing countries like India due to the already declining growth rate, inadequate health services, and a growing population residing in severe poverty. This paper attempts to understand the impact of COVID‐19 pandemic on the Indian economic sectors by employing a hierarchical approach, based on multi-criteria analysis to understand the impact on primary, secondary, tertiary and quaternary sectors by concerning the political, economic, socio‐cultural and technology consequences of COVID‐19. A process-based multi-criteria hierarchical approach has been used to determine the effect of the same and has been prioritized in the sequential sequence.