Effect of composite preforms weaving parameters on weaving capability based on vibration characteristics

In terms of the composite preforms weaving process, the influence of the length, width, height and speed of the weaving needle on the weaving capacity is analyzed. According to the calculated kinetic energy, potential energy, and virtual work of the weaving needle and the guide array, the system dynamic equation is established based on Hamilton’s principle, and the discrete processing is performed. According to the state equation, the Runge-Kutta method is used to solve the vibration response of the weaving needle free end. The correctness of the theoretical model is verified with ADAMS by analyzing the system dynamics. The variation of the free end vibration response was studied with time under different parameters. It is found that the velocity, length, and height parameters of the weaving needle have a greater influence on the vibration amplitude and the deflection of the equilibrium position. The comprehensive influence of velocity and size parameters on the weaving capability is discussed. Based on the above results, the analysis concludes that the width of the weaving needle has the smallest influence on weaving capability. The short-high weaving needles have great weaving capability. The increase in velocity can reduce the vibration amplitude and improve the weaving efficiency, but there is a limit to the improvement of the weaving capability.

Engineering of a toy model of the universe based on information and memory from an ICT perspective

How could we describe spacetime and all the information within it? What information are we considering? Where and how the information is stored and evolves? Which assumptions should we make on space and time to even imagine possible answers? The aim of this contribution is to investigate these open questions proposing a set of assumptions for the description of a toy-model of the universe in which phenomena could be described through information from an ICT perspective. Spacetime fabric is considered through finite, discrete and logical consistent information emerging as a probabilistic space (described as an imaginary distance ict) from a quantum memory (called Tk) that stores the non-local hidden information of spatial correlation (entanglement among spacetime events). Evolution is considered in discrete processing cycles of the spacetime memory, which are related to a universal beat of reference. After defining the context in which spacetime is considered, the contribution focuses on elementary particles and on how to describe their behavior in the proposed toy-model. The relativistic energy and the wave function are interpreted from the point of view of a momentum in ict (as spatial momentum) and a momentum in Tk (connected to the particle mass, memory and beat in respect to the universal beat of reference), that are elaborated in each cycle. Following the assumptions, a physical interpretation of the wave-particle duality is suggested in the context of memory, entanglement and information. The last section addresses the cosmological scales, looking for a possible physical realization of the model and proposing how the different arrows of time should emerge in the corresponding toy-universe. Additional elaboration on the geometry of the proposed interpretation and on how metric could be described through the variables introduces is provided in the Annex.Further developments are needed for a complete description of spacetime from information. With the proposal of a coherent toy model of the universe, from the engineering hypotheses on spacetime to a possible implementation, the author would like to highlight the importance of logical consistency in all quantum theories that approach Information Science and, eventually, offer a point of view that restores the value of time and memory in the physics narrative.

Discussion on Disaster Education and Prevention Strategies Based on SPSS Analysis - Taking disaster prevention research of Chengdu as an example

Post-disaster prevention strategies and education affect and shape the future development pattern and behavior of disaster prevention and reduction. Chengdu has made great achievements in disaster prevention education after the Wenchuan earthquake. Data from several dimensions has been analyzed through SPSS to explore the reasons for its success. The first dimension is disaster prevention education, including disaster research, disaster educational institution bases and disaster prevention education halls, etc. The second one is legal strategies for disasters, including current disaster-related policies and regulations of Chengdu. The disaster education in Chengdu over the ten years has been reviewed based on the weighted processing of historical data by SPSS. Though achievements have been made, there is room for improvement in the cultivation of a legal cultural concept for disasters and the establishment of a disaster accountability mechanism. Therefore, this paper reviewed the past legal education experience of Chengdu and made targeted suggestions based on the discrete processing analysis of multiple factors of post-disaster education so as to provide more thoughts on future disaster prevention strategies and legal education for disasters.

Music as Epistemic Construct: From Sonic Experience to Musical Sense-Making

Taking an epistemological stance towards music in a real-time listening situation entails a definition of music as a temporal and sounding art. This means that music cannot be described in abstract and detached terms as something “out there” in a virtual space but rather as something that impinges upon our senses in an actual “here and now.” Musical sense-making, therefore, should be considered a kind of ongoing knowledge construction with a dynamic tension between actual sensation and mental representation of sounding events. Four major dichotomies may be considered in this regard: the focal versus synoptic overview of the sounding music, the continuous/discrete processing of the sounds, the distinction between sensory experience versus cognitive economy, and the in-time/outside-of-time distinction. The author argues that a deliberate combination of these diverging approaches makes the musical experience a richer one.

Novel nonlinear reconstruction method with grey-level quantisation units for electron tomography

We report a new computed tomography reconstruction method, named quantisation units reconstruction technique (QURT), applicable to electron and other fields of tomography. Conventional electron tomography methods such as filtered back projection, weighted back projection, simultaneous iterative reconstructed technique, etc. suffer from the ‘missing wedge’ problem due to the limited tilt-angle range. QURT demonstrates improvements to solve this problem by recovering a structural image blurred due to the missing wedge and substantially reconstructs the structure even if the number of projection images is small. QURT reconstructs a cross-section image by arranging grey-level quantisation units (QU pieces) in three-dimensional image space via unique discrete processing. Its viability is confirmed by model simulations and experimental results. An important difference from recently developed methods such as discrete algebraic reconstruction technique (DART), total variation regularisation—DART, and compressed sensing is that prior knowledge of the conditions regarding the specimen or the expected cross-section image is not necessary.

On the Boundaries between Decision and Action: Effector-selective Lateralization of Beta-frequency Power Is Modulated by the Lexical Frequency of Printed Words

Current computational and neuroscientific models of decision-making posit a discrete, serial processing distinction between upstream decisional stages and downstream processes of motor-response implementation. We investigated this framework in the context of two-alternative forced-choice tasks on linguistic stimuli, words and pseudowords. In two experiments, we assessed the impact of lexical frequency and action semantics on two effector-selective EEG indexes of motor-response activation: the lateralized readiness potential and the lateralization of beta-frequency power. This allowed us to track potentially continuous streams of processing progressively mapping the evaluation of linguistic stimuli onto corresponding response channels. Whereas action semantics showed no influence on EEG indexes of motor-response activation, lexical frequency affected the lateralization of response-locked beta-frequency power. We argue that these observations point toward a continuity between linguistic processing of word input stimuli and implementation of corresponding choice in terms of motor behavior. This interpretation challenges the commonly held assumption of a discrete processing distinction between decisional and motor-response processes in the context of decisions based on symbolic stimuli.

Parasagittal Meningioma Brain Tumor Classification System Based on Mri Images and Multi Phase Level Set Formulation

The most common type of brain tumor known as Meningioma arises from the meninges and encloses the spine and the brain inside the skull. It accounts for 30% of all types of brain tumor. Meningioma’s can occur in many parts of the brain and accordingly it is named. In this paper, we propose Meningioma brain tumor classification system using MRI image is developed . Firstly, based on the characteristics of MRI image and Chan-Vese model, we use multiphase level set method to get the interesting region. Therefore, we obtain two matrixes, in which one contains the whole cell's boundary, and the other contains the boundary of some cells. Secondly, with respect to the cells' boundary, it is necessary to further processing, which ensures the boundary of some cells is a discrete region. Mathematical Morphology brings a fancy result during the discrete processing. At last, we consider every discrete region according to the tumor's features to judge whether a tumor appears in the image or not. Our method has a desirable performance in the presence of common tumors. For some non-convex tumors, we utilized a traditional way (SVM and LBP) as a second processing, which increased the coverage and accuracy. Experiments show that our method has a high coverage without any learning-based classifiers for most common tumors, which saves a lot time and reduces a lot workload. Therefore, the proposed method has a good practical application for assisting physicians in detecting Meningiom tumors using MRI images.

Three-stage flow-shop scheduling model with batch processing machine and discrete processing machine

This study discusses the model development of three-stage flow-shop scheduling involving Batch Processing Machine (BPM) and Discrete Processing Machine (DPM). Each job passes several stages of the production process from the first stage in DPM-a, the second stage in BPM, to the third stage in DPM-b. Each job is sequentially processed in DPM-a and DPM-b. in BPM; every job is handled simultaneously at the same time. The maximum weight determines the capacity of BPM. This study uses mathematic modeling approach. The result model produced in this study is Mixed Integer Linear Programming (MILP) Model. Purpose function model is minimizing total completion time. Model testing is done by using numerical examples with several data scenarios. The results showed that the model produced was the optimum model and provided a unique schedule pattern. In the future research can be formulated the heuristic model.