Oscillation control of a pendulum structure using an inverted pendulum-type tuned mass damper

In reality, a pendulum structure can be used to model many real structures as a ropeway carrier, crane, balloon basket or ships in waves, etc, which often hung on moving points such as cables, wavefronts and balloons, etc. To the best knowledge of the author, however, there is no study to control oscillation of the pendulum structure excited by the hanging point. Therefore, this article deals with the oscillation control of the pendulum structure by using an inverted pendulum-type tuned mass damper, in which the system is subjected to the motion of the hanging point. In particular, the optimal parameters are determined in clear analytical solutions, making it easy for scientists to determine the optimal parameters to suppress the oscillation for the pendulum structure.

Greedy Dynamic Blocking for Rumour Detection on Live Twitter Using Machine Learning

We propose a community multi-Trends assessment grouping way to deal with train notion classifiers for numerous tweets at the same time. In our methodology, the assessment data in various tweets is shared to prepare more exact and vigorous estimation classifiers for each Trends when marked information is scant. In particular, we decay the opinion classifier of each Trends into two segments, a worldwide one and a Trends-explicit one. Various customer surveys of subjects are currently accessible on the Internet. Naturally distinguishes the significant parts of themes from online shopper surveys. The significant item angles are recognized dependent on two perceptions. With the point of arranging patterns from the get-go. This would permit to give a separated subset of patterns to end clients. We investigate and explore different avenues regarding a bunch of direct language-autonomous highlights dependent on the social spread of patterns to classify them into the presented typology. Our strategy gives an effective method to precisely arrange moving points without need of outer information, empowering news associations to find breaking news progressively, or to rapidly recognize viral images that may improve promoting choices, among others. The examination of social highlights additionally uncovers designs related with each sort of pattern, for example, tweets about continuous occasions being more limited the same number of were likely sent from cell phones, or images having more retweets starting from a couple of innovators. The worldwide model can catch the overall conclusion information and is shared by different tweets. The Trends-explicit Greedy and Dynamic Blocking Algorithms model can catch the particular assessment articulations in each Trend. Likewise, we remove Trends-explicit feeling information from both marked and unlabeled examples in each Trend and use it to improve the learning of Trends-explicit notion classifiers.

Early recognizing of a hurricanes from public satellite images

One of the key tasks associated with the fast identification of powerful tropical hurricanes, the assessment of the growth of their power, is the formation of such an input dataset, which is based on data that are technically easy and accurately recorded and calculated using existing sources located in the open accessibility. The presented work is based on the analysis of satellite images as the main data sources, and on weather data as peripheral. An obvious advantage of satellite images in comparison with other sources of data on weather conditions is their high spatial resolution, as well as the ability to obtain data from various satellites, which increases the timeliness and accuracy of retrieving primary information. The developed approach consists in performing the following main interconnected iteratively performed groups of subtasks: calculation of feature points describing the location of individual cloud areas at different points in time by using different descriptors; comparison of the same cloud areas at specified times to analyze the local directions of cloud movements; tracking of cloudiness for specified time intervals; calculation of local features for selected points of cloudiness to recognize the origin and analyze turbulence; the formation of the dynamics of changes in the local area near the trajectory of the point; recognition of primary characteristic features characterizing the transformation of local turbulences into a stable vortex formation; identification of signs of the growing of a hurricane and assessment of the primary dynamics of the increase in its power; generalization and refinement of a priori given features by analyzing similar features of known cyclones. To detect points, a modified algorithm for finding them has been introduced. To describe the points, additional descriptors are introduced based on the normalized gradient measured for the neighborhood of neighboring points and cyclically changing in the polar coordinate system. A comparative analysis of the results of applying the created method and algorithm when compared with known similar solutions revealed the following distinctive features: introduction of additional invariant orientations of features when describing characteristic points and greater stability of detecting characteristic points when analyzing cloudiness, identification of cloudiness turbulence and analysis of changes in their local characteristics and movement parameters, formation of a set of generalizing distributions when analyzing a set of moving points for the subsequent recognition of the signs of a hurricane at its initial stages of formation. The developed approach was tested experimentally in the analysis of hurricanes video recordings and their movement in the Atlantic region for the period from 2010 to 2020. The developed general approach and a specific algorithm for estimating hurricane parameters based on cloud analysis are presented. The approach is applicable for practical implementation and allows accumulating data for detecting hurricanes in real time based on publicly available data for the development of a physical and mathematical model.

Effect of Precipitation Characteristics on Spatial and Temporal Variations of Landslide in Kermanshah Province in Iran

Landslide can be defined as the mass movement of sloping slopes under the influence of mass gravity and its stimuli such as earthquakes, floods and flood plains. This phenomenon is one of the natural hazards that every year causes a lot of financial and financial losses in mountainous, rain-fed and seismic areas. Detection of time and the magnitude of landslides are necessary to understand the causes of landslide and to warn potential hazards. In this research, the amount of landslide displacement in Kermanshah province was evaluated by the characteristics of rainfall. To this end, a network of fixed points in and out of the slipping mass of 20 points was created to monitor the amount of displacement on different slip load users and the amount of displacement of each point in 5 time intervals using the Global Positioning System for two-dimensional GPS measurement. The results of the 511-day follow-up showed that the total horizontal displacement of the moving points in the 5 intervals measured at 1658 mm has a monthly displacement rate of 112 mm. Also, the total vertical displacement of moving points at the same time is 899 mm, with a monthly movement rate of 71 mm. Then, precipitation variances such as rainfall, rainfall, precipitation duration, maximum rainfall intensity in the intervals of 10, 20, 30 and 60 minutes and the average rainfall intensity were calculated and extracted for each of the 5 time periods. The drawing of the vectors of points on the topographic map of the area indicated that the direction of mass movement is in the direction of elevation gradient of the region. The results showed that only the precipitation severity with the landslide had a good correlation. The landslide movement had the highest correlation with average rainfall intensity (R = 0.85) and with maximum 30 minutes rainfall (R = 0.67), respectively, and other rainfall characteristics like amount, duration, and type of rainfall had not significantly correlated with movement of landslides.

Moving Object Detection and Tracking with Doppler LiDAR

In this paper, we present a model-free detection-based tracking approach for detecting and tracking moving objects in street scenes from point clouds obtained via a Doppler LiDAR that can not only collect spatial information (e.g., point clouds) but also Doppler images by using Doppler-shifted frequencies. Using our approach, Doppler images are used to detect moving points and determine the number of moving objects followed by complete segmentations via a region growing technique. The tracking approach is based on Multiple Hypothesis Tracking (MHT) with two extensions. One is that a point cloud descriptor, Oriented Ensemble of Shape Function (OESF), is proposed to evaluate the structure similarity when doing object-to-track association. Another is to use Doppler images to improve the estimation of dynamic state of moving objects. The quantitative evaluation of detection and tracking results on different datasets shows the advantages of Doppler LiDAR and the effectiveness of our approach.

Finite Position Synthesis of 5-SS Platform Linkages Including Partially Specified Joint Locations

A 5-SS platform linkage generates a one-degree-of-freedom motion of a moving platform such that each of five moving points on the platform is constrained on a sphere, or in its degenerated case, on a plane. It has been well established a 5-SS platform linkage can be made to guide though seven positions exactly. This paper investigates the cases when the number of given positions are less than seven that allows for partial specification of locations of the moving points. A recently developed novel algorithm with linear structure in the design equations has been extended for the solution of the problem. The formulation of this expanded motion generation problem unifies the treatment of the input positions and constraints on the moving and fixed joints associated with the 5-SS platform linkage. Numerical examples are provided to show the effectiveness of the unified algorithm.