RRWKV: Capturing Long-range Dependencies in RWKV

Owing to the impressive dot-product attention, the Transformers have been the dominant architectures in various natural language processing (NLP) tasks. Recently, the Receptance Weighted Key Value (RWKV) architecture follows a non-transformer architecture to eliminate the drawbacks of dot-product attention, where memory and computational complexity exhibits quadratic scaling with sequence length. Although RWKV has exploited a linearly tensor-product attention mechanism and achieved parallelized computations by deploying the time-sequential mode, it fails to capture long-range dependencies because of its limitation on looking back at previous information, compared with full information obtained by direct interactions in the standard transformer. Therefore, the paper devises the Retrospected Receptance Weighted Key Value (RRWKV) architecture via incorporating the retrospecting ability into the RWKV to effectively absorb information, which maintains memory and computational efficiency as well

Field Experimental Study on Corrosion Mechanism of Well Lai 14-9

Casing corrosion is serious and the injection efficiency is considerably low due to high injecting water corrosion in Well Lai 14-9. Casing corrosion mechanism is retrieved through SEM observation, energy spectrum analysis, XRD analysis spectrum, TGA analysis of corrosion fouling. The results show casing corrosion mechanism varies with depths; casing corrosion is the result of the combined action of carbon dioxide, dissolved oxygen, sulfate-reducing bacteria and high salinity. To extend the life of casing, appropriate casing protection measures should be adopted, which can reduces the cost of production of the oilfield.Key words: Corrosion mechanism; Fouling; SEM observation; XRD analysis spectrum; TGA analysi

Hybrid graded element model for nonlinear functionally graded materials

A hybrid graded element model is developed in this article for solving the heat conduction problem of nonlinear functionally graded materials (FGMs), whose material properties not only vary spatially but also are temperature dependent. In the proposed approach, both Kirchhoff transformation and iterative method are introduced to deal with the nonlinear term in the heat conduction equation of nonlinear FGMs. Then, the graded element is formulated based on two sets of independent temperature fields. One is the intra-element temperature field, which is defined within the element domain and constructed by a linear combination of fundamental solutions; the other is the frame field, which is defined on the element boundary only and used as the boundary interpolation functions of the element to ensure the field continuity over the inter-element boundary. This model can simulate the graded material properties naturally due to the inherent properties of fundamental solutions, which are employed in constructing the graded element. Moreover, a multi-subdomain method is developed to deal with the problem with different materials. Finally, the performance of the proposed method is assessed by several benchmark examples. The results are in excellent agreement with the analytical solutions

A Theory of Complex Adaptive Learning Based on an Intelligent Trading Probability Wave Equation

Complex adaptive learning is intelligent and crucial in living and inanimate complex systems. A complex system comprises many interacting individuals or units, shows hidden patterns as they interact, and widely occurs in almost every traditional discipline, from natural to social sciences. A recent study has demonstrated a so-called architected material capable of learning. It stimulates scientists to explore the mechanism of complex systems formulation. However, it is very challenging. Here the authors attempt to extract a universal rule or a law of complex adaptive learning subject to local dynamic equilibrium in complex systems from a trading volume-price probability wave equation and apply it to complex quantum systems as its application. It proves particles capable of intelligence-like properties in interactive coherence if the momentum force exerted on the complex quantum systems is non-localized. It is the cumulative probability of the moving particles observed in a time interval. Thus, it assumes that particles in complex quantum systems have a complex adaptive learning- or intelligence-like property in a reinforced coordinate, governed by the exact complex adaptive learning mechanism as that of traders in the complexity of the financial markets. With this assumption, the authors propose an innovative interpretation of entanglement in quantum mechanics. It concludes that quantum entanglement is not a state of the superposition of coherent states as the mainstream Copenhagen school of thought maintains. It is a coherent state in the interaction between two opposite, complementary, and variable forces. The authors look forward to the experimental results to examine its validity and further improve the theory until it is perfect, suggesting industrial production of entanglement resources in new technical routes availableComment: 22 pages in total (double spaces and including a title page and a popular summary), 2 figures, and 20 reference

The effects of cognitive style and emotional trade-off difficulty on information processing in decision-making

This study investigated the effects of cognitive style and emotional trade‐off difficulty (ETOD) on information processing in decision‐making. Eighty undergraduates (73.75% female, M = 21.90), grouped according to their cognitive style (field‐dependent or field‐independent), conducted an Information Display Board (IDB) task, through which search time, search depth and search pattern were measured. Participants' emotional states were assessed both before and after the IDB task. The results showed that participants experienced significantly more negative emotion under high ETOD compared to those under low ETOD. While both cognitive style and ETOD had significant effects on search time and search depth, only ETOD significantly influenced search pattern; individuals in both cognitive style groups tended to use attribute‐based processing under high ETOD and to use alternative‐based processing under low ETOD. There was also a significant interaction between cognitive style and ETOD for search time and search depth. We propose that these results are best accounted for by the coping behaviour framework under high ETOD, and by the negative emotion hypothesis under low ETOD

Ultimate boundary estimations and topological horseshoe analysis of a new 4D hyper-chaotic system

In this paper, we first estimate the boundedness of a new proposed 4-dimensional (4D) hyper-chaotic system with complex dynamical behaviors. For this system, the ultimate bound set Ω1 and globally exponentially attractive set Ω2 are derived based on the optimization method, Lyapunov stability theory and comparison principle. Numerical simulations are presented to show the effectiveness of the method and the boundary regions. Then, to prove the existence of hyper-chaos, the hyper-chaotic dynamics of the 4D nonlinear system is investigated by means of topological horseshoe theory and numerical computation. Based on the algorithm for finding horseshoes in three-dimensional hyper-chaotic maps, we finally find a horseshoe with two-directional expansions in the 4D hyper-chaotic system, which can rigorously prove the existence of the hyper-chaos in theory

La conmutación cognitiva afecta la selección de estrategia aritmética: Evidencia de patrones de mirada y medidas conductuales

Although many studies of cognitive switching have been conducted, little is known about whether and how cognitive switching affects individuals’ use of arithmetic strategies. We used estimation and numerical comparison tasks within the operand recognition paradigm and the choice/no-choice paradigm to explore the effects of cognitive switching on the process of arithmetic strategy selection. Results showed that individuals’ performance in the baseline task was superior to that in the switching task. Presentation mode and cognitive switching clearly influenced eye-gaze patterns during strategy selection, with longer fixation duration in the number presentation mode than in the clock presentation mode. Furthermore, the number of fixation was greater in the switching task than it was in the the baseline task. These results indicate that the effects of cognitive switching on arithmetic strategy selection are clearly constrained by the manner in which numbers are presented. Aunque se han realizado muchos estudios sobre el cambio cognitivo, se sabe poco acerca de si el cambio cognitivo afecta el uso de las estrategias aritméticas por parte de las personas y cómo lo hace. Utilizamos las tareas de estimación y comparación numérica dentro del paradigma de reconocimiento de operandos y el paradigma de elección / no elección para explorar los efectos del cambio cognitivo en el proceso de selección de estrategia aritmética. Los resultados mostraron que el rendimiento de los individuos en la tarea de referencia fue superior al de la tarea de cambio. El modo de presentación y la conmutación cognitiva influyeron claramente en los patrones de la mirada durante la selección de estrategia, con duraciones de fijación más largas en el modo de presentación numérica que en el modo de presentación de reloj. Además, el número de fijaciones fue mayor en la tarea de conmutación que en la tarea de línea de base. Estos resultados indican que los efectos del cambio cognitivo en la selección de la estrategia aritmética están claramente limitados por la forma en que se presentan los números

Self-optimizing Feature Generation via Categorical Hashing Representation and Hierarchical Reinforcement Crossing

Feature generation aims to generate new and meaningful features to create a discriminative representation space.A generated feature is meaningful when the generated feature is from a feature pair with inherent feature interaction. In the real world, experienced data scientists can identify potentially useful feature-feature interactions, and generate meaningful dimensions from an exponentially large search space, in an optimal crossing form over an optimal generation path. But, machines have limited human-like abilities.We generalize such learning tasks as self-optimizing feature generation. Self-optimizing feature generation imposes several under-addressed challenges on existing systems: meaningful, robust, and efficient generation. To tackle these challenges, we propose a principled and generic representation-crossing framework to solve self-optimizing feature generation.To achieve hashing representation, we propose a three-step approach: feature discretization, feature hashing, and descriptive summarization. To achieve reinforcement crossing, we develop a hierarchical reinforcement feature crossing approach.We present extensive experimental results to demonstrate the effectiveness and efficiency of the proposed method. The code is available at https://github.com/yingwangyang/HRC_feature_cross.git

SoccerDB: A Large-Scale Database for Comprehensive Video Understanding

Soccer videos can serve as a perfect research object for video understanding because soccer games are played under well-defined rules while complex and intriguing enough for researchers to study. In this paper, we propose a new soccer video database named SoccerDB, comprising 171,191 video segments from 346 high-quality soccer games. The database contains 702,096 bounding boxes, 37,709 essential event labels with time boundary and 17,115 highlight annotations for object detection, action recognition, temporal action localization, and highlight detection tasks. To our knowledge, it is the largest database for comprehensive sports video understanding on various aspects. We further survey a collection of strong baselines on SoccerDB, which have demonstrated state-of-the-art performances on independent tasks. Our evaluation suggests that we can benefit significantly when jointly considering the inner correlations among those tasks. We believe the release of SoccerDB will tremendously advance researches around comprehensive video understanding. {\itshape Our dataset and code published on https://github.com/newsdata/SoccerDB.}Comment: accepted by MM2020 sports worksho