Twitter Data Collection Using Tools for Classification of fake Data: A Survey

Data could be a piece of information that’s needed to create helpful information. Getting data is required by people to analyzers. From this angle, data assortment is a vital step once doing any research or experiment. Knowledge collection may be outlined because the method of gathering and process the data to gauge the outcomes and use them for the researches. On-line Social Networking sites (OSN) are one in all the most effective sources of data. We have a tendency to be attending to introduce the advantages of exploitation the social network sites for data collection and also the totally different techniques which will be used. Based mostly on those data, a network of trust created exploitation the relationships among users. The methods the information being collected is totally different in term of potency and being useful. Be that as it may, the information mining applications in the web-based media are as yet crude and require more exertion by the scholarly world and industry to sufficiently play out the work. Client created content via online media destinations, for example, Twitter and Facebook gives freedom to specialists in different fields to comprehend human practices and social marvels. From one viewpoint, these human practices and social marvels are unpredictable in nature hence need top to bottom subjective investigation. On the other, the size of online media data requires colossal degree data assessment strategies. Automated information assortment of interpersonal interaction Web locales assumes a significant part in dynamic. Realize that the Web destinations like Twitter, Facebook, YouTube, Pin interest, and so on are turning out to be indispensable parts of public activity as of now. In any examination issue the mass effect on different issues can be investigated by breaking down the information produced from these Web locales. Also, these social stages are open and generally utilized for see sharing. Here different devices and systems have been assessed to gather the information from these Web locales. The capacities of conclusion investigation stretch out to the quantity of genuine choices like medical problems in the public eye, or the client responses, and so forth in this paper information assortment procedures have been shown with the assistance of live execution.

Microbial Depolymerization of Epoxy Resins: A Novel Approach to a Complex Challenge

The objective of this project is evaluating the potential of microbes (fungi and bacteria) for the depolymerization of epoxy, aiming at the development of a circular management of natural resources for epoxy in a long-term prospective. For depolymerization, epoxy samples were incubated for 1, 3, 6 and 9 months in soil microcosms inoculated with Ganoderma adspersum. Contact angle data revealed a reduction in the hydrophobicity induced by the fungus. Environmental scanning electron microscopy on epoxy samples incubated for more than 3 years in microbiological water revealed abundant microbiota. This comprised microbes of different sizes and shapes. The fungi Trichoderma harzianum and Aspergillus calidoustus, as well as the bacteria Variovorax sp. and Methyloversatilis discipulorum, were isolated from this environment. Altogether, these results suggest that microbes are able to colonize epoxy surfaces and, most probably, also partially depolymerize them. This could open promising opportunities for the study of new metabolisms potentially able depolymerize epoxy materials.

Hydrophobic Properties of CuO Thin Films Obtained by Sol-Gel Spin Coating Technique-Annealing Temperature Effect

The adhesive characteristics of sol-gel copper oxide (CuO) film surfaces at annealing temperatures ranging from 350 to 550°C were examined in this work. Hydrophobic properties of these oxide film surfaces were studied by contact angle measurements. The surface energy was calculated from contact angle data using harmonic mean method. The structural, morphological and chemical analysis of the samples were characterized by X-ray diffraction (XRD), scanning electron microscopy (SEM) and Fourier transform infrared (FTIR). The increase in annealing temperature induces a reduction in the hydrophilic properties of the films (adhesive properties). The rise in the hydrophobicity of the CuO surface has been claimed to be explained by a change in interfacial tension. The FTIR spectroscopy analysis revealed that the increase in the annealing temperature eliminates activated neutral species (hydroxyl groups) reacting with the surface of the sample responsible for the wettability. SEM analysis showed that the morphology of the samples is nanostructured containing agglomerates of various forms, a few hundred nanometers in size, randomly dispersed across the surface. The enhanced roughness of the produced film is primarily responsible for the increased hydrophobicity of the films. The XRD data reveal that the films are highly textured and that increasing the annealing temperature induces better layer crystallization and confirms the development of copper oxide CuO.

Intelligent System for Training and Assessment of Basketball Referee in Sports Event Using Intelligent Sensor

Aiming at the problem of the fairness of the judgment results in the traditional basketball referee training and evaluation process affected by external factors, an intelligent system for training and assessment of basketball referees in sports events based on intelligent sensors is proposed. We collect the judged poses of basketball referees by wearing intelligent sensor devices, store the collected information in the database using the converter, and analyze the pose data with the quaternion pose solution method based on complementary filters. According to the comparator, the analysis result is compared with the standard judgment information, and the action is judged whether the action conforms to the basketball judgment rules of the sports event. The judge’s action pose score is evaluated according to the judgment result, and the training assessment result is outputted. The results show that the system can clearly simulate the acceleration and pose angle data of the referee’s complex actions, the recognition rate of various basketball penalty poses is high, and the error of the pitch, yaw, and roll pose calculations is small. The response time of this system is 4 ms, when the number of requests sent by the client is 200 which is unanimously approved by the referees.

Coordinated intelligent manipulator based on exoskeleton

Manipulators have a wide range of applications in telemedicine, deep-sea exploration, remote explosive-removal and prosthesis for the disabled. Based on exoskeleton and voice control, a coordinated intelligent manipulator was proposed in this paper. The main design scheme, attitude angle data acquisition and data processing methods were given, and the final test results were obtained.

Research Self-balancing UAV Takeoff and Landing Control System Based on Quadruped Robot

Aiming at the advantages of UAVs in field survey and search as well as their difficulties in taking off and landing in poor ground environment in the field, a simple self-balancing UAV take-off and landing control system based on a quadruped robot is proposed. Firstly, the simple physical model of the system is established and the mathematical analysis is carried out. Secondly, the inverse kinematics of the single leg model is derived. Thirdly, the attitude sensor is used to measure the attitude angle data of the system platform, and the Kalman filter is used in the software design to filter the attitude angle data, and the PID control algorithm is used to control each leg joint. Finally, The design is simulated by MATLAB and experimentally analyzed, and the test results meet the design requirements.

Abnormal Data Detection of Guidance Angle Based On SMP-SVDD For Seeker

The accuracy of the pitch angle deviation directly affects the guidance accuracy of the laser seeker. During the guidance process, the abnormal pitch angle deviation data will be produced when the seeker is affected by interference sources. In this paper, aiming to detect abnormal data in seeker pitch angle deviation data, a method based on Smooth Multi-Kernel Polarization Support Vector Data Description (SMP-SVDD) is proposed to detect abnormal data in guidance angle data. On the one hand, the polarization value is used to determine the weight of the multi-kernel combination coefficient to obtain the multi-kernel polarization function, and the particle swarm optimization is used to find the optimal kernel, which improves the detection accuracy. On the other hand, the constrained quadratic programming problem is smooth and differentiable, and the conjugate gradient method can be applied to reduce the complexity of problem solving. Through simulation experiments, it is verified that the SMP-SVDD method has higher detection accuracy and faster calculation speed compared with different detection methods in different guidance stages.

Short-Arc Association and Orbit Determination for New GEO Objects with Space-Based Optical Surveillance

For Geosynchronous Earth Orbit (GEO) objects, space-based optical surveillance has advantages over regional ground surveillance in terms of both the timeliness and space coverage. However, space-based optical surveillance may only collect sparse and short orbit arcs, and thus make the autonomous arc association and orbit determination a challenge for new GEO objects without a priori orbit information. In this paper, a three-step approach tackling these two critical problems is proposed. First, under the near-circular orbit assumption, a multi-point optimal initial orbit determination (IOD) method is developed to improve the IOD convergence rate and the accuracy of the IOD solution with angles-only observations over a short arc. Second, the Lambert equation is applied to associate two independent short arcs in an attempt to improve accuracy of the single-arc IOD semi-major axis (SMA) with the use of virtual ranges between the optical sensor and GEO object. The key idea in the second step is to generate accurate ranges at observation epochs, which, along with the real angle data, are then used to achieve much improved SMA accuracy. The third step is basically the repeated application of the second step to three or more arcs. The high success rate of arc associations and accurate orbit determination using the proposed approach are demonstrated with simulated space-based angle data over short arcs, each being only 3 min. The results show that the proposed approach is able to determine the orbit of a new GEO at a three-dimensional accuracy of about 15 km from about 10 arcs, each having a length of about 3 min, thus achieving reliable cataloguing of uncatalogued GEO objects. The IOD and two-arc association methods are also tested with the real ground-based observations for both GEO and LEO objects of near-circular orbits, further validating the effectiveness of the proposed methods.

Identifying resonances of the Galactic bar in Gaia DR2: II. Clues from angle space

The Milky Way disk exhibits intricate orbit substructure of still-debated dynamical origin. The angle variables (θφ, θR)—which are conjugates to the actions (Lz, JR), and describe a star’s location along its orbit—are a powerful diagnostic to identify l:m resonances via the orbit shape relation ΔθR/Δθφ = −m/l. In the past, angle signatures have been hidden by survey selection effects (SEs). Using test particle simulations of a barred galaxy, we demonstrate that Gaia should allow us to identify the Galactic bar’s Outer Lindblad Resonance (l = +1, m = 2, OLR) in angle space. We investigate strategies to overcome SEs. In the angle data of the Gaia DR2 RVS sample, we independently identify four candidates for the OLR and therefore for the pattern speed Ωbar. The strongest candidate, Ωbar ∼ 1.4Ω0, positions the OLR above the ‘Sirius’ moving group, agrees with measurements from the Galactic center, and might be supported by higher-order resonances around the ‘Hercules/Horn’. But it misses the classic orbit orientation flip, as discussed in the companion study on actions. The candidate Ωbar ∼ 1.2Ω0 was also suggested by the action-based study, has the OLR at the ‘Hat’, is consistent with slow bar models, but still affected by SEs. Weaker candidates are Ωbar = 1.6 and 1.74Ω0. In addition, we show that the stellar angles do not support the ‘Hercules/Horn’ being created by the OLR of a fast bar. We conclude that—to resolve if ‘Sirius’ or ‘Hat’ are related to the bar’s OLR—more complex dynamical explanations and more extended data with well-behaved SEs are required.

A Parameter-Free Approach for Fault Section Detection on Distribution Networks Employing Gated Recurrent Unit

Faults in distribution networks can result in severe transients, equipment failure, and power outages. The quick and accurate detection of the faulty section enables the operator to avoid prolonged power outages and economic losses by quickly retrieving the network. However, the occurrence of diverse fault types with various resistances and locations and the highly non-linear nature of distribution networks make fault section detection challenging for numerous conventional techniques. This study presents a cutting-edge deep learning-based algorithm to distinguish fault sections in distribution networks to address these issues. The proposed gated recurrent unit model utilizes only two samples of the angle between the voltage and current on either side of the feeders, which record by smart feeder meters, to detect faulty sections in real time. When a network fault occurs, the protection relays trigger the trip command for the breakers. Immediately, the angle data are obtained from all smart feeder meters of the network, which comprises a pre-fault sample and a post-fault sample. The data are then employed as an input to the pre-trained gated recurrent unit model to determine the faulted line. The performance of this novel algorithm was validated through simulations of various fault types in the IEEE-33 bus system. The model recognizes the faulty section with competitive performance in terms of accuracy.