A system for gravitytable separation including a gravitytable for separating materials and a detector operatively associated with the gravitytable for detecting the movement of control particles with respect to the gravitytable during its operation. The control particles are of a known characteristic. By calibrating the desired movement of the control particles through the table, any misalignment or deviance of that movement during operation is detected, and adjustments can be made to the operation of the table to bring the control particles back to the desired movement. The separation process can then be controlled to bring about optimum efficiency. Also, the detector can be interfaced with a control component which can automatically adjust the operation of the table in response to whether the control particles are following the desired movement through the table.
WSN consist of hundreds of thousands of small and cost effective sensor nodes. Sensor nodes are used to sense the environmental or physiological parameters like temperature, pressure, etc. For the connectivity of the sensor nodes, they use wireless transceiver to send and receive the inter-node signals. Sensor nodes, because connect their selves wirelessly, use routing process to route the packet to make them reach from source to destination. These sensor nodes run on batteries and they carry a limited battery life. Clustering is the process of creating virtual sub-groups of the sensor nodes, which helps the sensor nodes to lower routing computations and to lower the size routing data. There is a wide space available for the research on energy efficient clustering algorithms for the WSNs. LEACH, PEGASIS and HEED are the popular energy efficient clustering protocols for WSNs. In this research, we are working on the development of a hybrid model using LEACH based energy efficient and K-means based quick clustering algorithms to produce a new cluster scheme for WSNs with dynamic selection of the number of the clusters automatically. In the proposed method, finding an optimum „k‟ value is performed by Elbow method and clustering is done by k-means algorithm, hence routing protocol LEACH which is a traditional energy efficient protocol takes the work ahead of sending data from the cluster heads to the base station. The results of simulation show that at the end of some certain part of running the proposed algorithm, at some point the marginal gain will drop dramatically and gives an angle in the graph. The correct „k‟ i.e. number of clusters is chosen at this point, hence the "elbow criterion".
We investigate, theoretically and empirically, the effectiveness of kernel K-means++ samples as landmarks in the Nystr¨om method for low-rank approximation of kernel matrices. Previous em- pirical studies (Zhang et al., 2008; Kumar et al., 2012) observe that the landmarks obtained using (kernel) K -means clustering define a good low- rank approximation of kernel matrices. However, the existing work does not provide a theoretical guarantee on the approximation error for this ap- proach to landmark selection. We close this gap and provide the first bound on the approxima- tion error of the Nystr¨om method with kernel K - means ++ samples as landmarks. Moreover, for the frequently used Gaussian kernel we provide a theoretically sound motivation for performing Lloyd refinements of kernel K-means++ land- marks in the instance space. We substantiate our theoretical results empirically by comparing the approach to several state-of-the-art algorithms.
A means and method for camera space manipulation includes a manipulator arm extending from a base to an outward end. The arm is movable through a workspace to accomplish various tasks. One or more cameras are movably oriented towards the arm and work space to capture the arm and work space in what will be called camera space or camera vision. A visual cue is associated with the outward end of the manipulator arm. Additionally, a visual cue is associated with an object which is desired to be engaged by the manipulator arm or by what is held by the manipulator arm. A control device is connected to the camera or cameras and to the manipulator. According to identification and tracking of the visual cues in the camera space, the control device instructs appropriate motors to move the manipulator arm according to estimations for engagement
This article describes a combination of experimental and mathematical methods for the determination of undissolved air content in hydraulic oil. The experimental part consists of the determination of the oil bulk modulus, considering the influence of undissolved air by means of a volume compression method in a steel pipe. A multiphase model of an oil/undissolved air mixture is subsequently defined using Matlab SimHydraulics software. The multiphase model permits the volume compression of oil and air bubbles independently of each other. Furthermore, time dependencies of pressures are mathematically simulated during the compression of the multiphase mixture of oil and undissolved air for different concentrations of the latter. The undissolved air content is determined by comparing the mathematically simulated and experimentally measured time dependencies of pressure increases.
Table 4 is the experimental results of piecewise point’s method. It is obvious that the ranking order for student 207 and 241 after the standardization. For coefficient adjustment method, it needs the initial entrance examination score. So these two methods will not be used for the evaluation in this part. For the rest methods mentioned in this paper, the relative comparison of experimental results will be talked about below.
Throughout the whole area the desertification phenomenon has occurred with different degrees. No area was classified as low class or normal. Of the 45600 hectares of land under study, 35.2% has low class (II), 31.99% has average class (III and 32.75 has high class IV. Although the area under study has three classes (IV, II, II) it is found with a little attention to the table and graphs obtained from the analysis of desertification processes. That some of the unit works were progressing to ward higher classes. This will intend to warn the increase of desertification severity in future (Figure 8, Table 5).
comprised of one or more charged analytes which displace fluorescing ions where its constituent components separate to. Fluorescing ions of the same charge as the charged analyte components cause a displacement. The displacement results in the location of the separated components having a reduced fluorescence intensity to the remainder of the background. Detection of the lower fluorescence intensity areas can be visually, by photographic means and methods, or by automated laser scanning.
Filtering the simulated data sets that have been tested has proven to be beneficial. It could be clearly seen that the number of false rejections has been reduced, where this was not necessarily the case for the total number of rejections. This leads to the conclusion that more correct rejections have been made, hence more precise detections have been achieved. What could improve the detection of a wanted signal even more is applying the Holm-Bonferroni method  on the simulated data. Briefly explained, this method is used for multiple-hypothesis testing to control the family-wise error rate - meaning the probability that one or more errors of Type I will occur. Since this paper was dealing with multiple-hypothesis testing for simulated data, and further on the Kepler data, this method could have been useful.
A method for controlling odor in a waste water lagoon comprises the steps of aerating a top horizontal layer of a lagoon adjacent its upper surface at a depth of approximately 12 to 24 inches by introducing air through a plurality of nozzles submerged in the layer to create a plurality of air bubbles in the layer. The nozzles are moved horizontally through the layer. A device for controlling the odor in waste water lagoons includes a support structure with an elongated boom operatively secured to the support structure and extending
In the present paper, we would like to introduce a simple transformation for bivariate means from which we derive a lot of new means. Relationships between the standard means are also obtained. A simple link between the Stolarsky mean and the Gini mean is given. As applications, this transformation allows us to extend some means from two to three or more arguments.
For example,if PV module has to be placed far away from charge controller and battery, its wire size must be very large to reduce voltage drop. With a MPPT solar charge controller, users can wire PV module for 24 or 48 V (depending on charge controller and PV modules) and bring power into 12 or 24 V battery system. This means it reduces the wire size needed while retaining full output of PV module.
Machine vision is an important boost for automation in various industrial manufacturing fields in the future. Laser scanning ranging radar is an important part of machine vision and an important means for machine perception of the surrounding environment. In the driverless industry, laser radar is used to identify road boundaries ; in the power industry, laser radar can be used to obtain coordinate data of electric towers and terrain surfaces, and inspection circuits [2, 3]; in forestry, laser radar It is used to simulate vegetation density, generate digital terrain, etc. [4-6]; Laser radar is also widely used in highways, waterways, railway surveys, digital model generation, etc. [7-10].
In Fig. 10, the horizontal driving torque on the gravity un- loading facility is nearly the same with the one in space en- vironment except the first one has a slight offset down. The offset is cause by the asymmetry of the artificial load of hori- zontal axis especially after the application of air bearing and other connection parts. Though the balance with the counter- weight is considered, the offset still exist because of the pre- cision of software model. In the simulation, the offset can be eliminated by applying an extra force on the counterweight which means that when the real gravity unloading facility is established, the offset can be eliminated by adjusting the counterweight carefully. Besides, to imitate the fundamental modal frequency, the artificial load has a low fundamental frequency which means a low stiffness in the tangential di- rection of the horizontal axis. So the torque of horizontal axis has fluctuations at the acceleration and deceleration points. The fluctuations attenuate quickly, so the gravity unloading facility works stably.
Unlike in ( ¨Ozbal and Strapparava, 2011), where we did not enforce any constraints for selecting the keywords, in this case we applied a more so- phisticated filtering and ranking strategy. We re- quire at least one keyword in each pair to be a content word; then, we require that at least one keyword has length ≥ 3; finally, we discard pairs containing at least one proper noun. We allowed the keyword generation module to consider all the entries in the CMU dictionary, and rank the key- word pairs based on the following criteria in de- creasing order of precedence: 1) Keywords with a smaller orthographic/phonetic distance are pre- ferred; 2) Keywords consisting of a single word are preferred over two words (e.g., for the target word lavagna, which means blackboard, lasagna takes precedence over love and onion); 3) Key- words that do not contain stop words are preferred (e.g., for the target word pettine, which means comb, the keyword pair pet and inn is ranked higher than pet and in, since in is a stop word); 4) Keyword pairs obtained with orthographic similar- ity are preferred over those obtained with phonetic similarity, as learners might be unfamiliar with the phonetic rules of the target language. For example, for the target word forbice, which means scissors,
Abstract. Time variable gravity fields, reflecting variations of mass distribution in the system Earth is one of the key parameters to understand the changing Earth. Mass variations are caused either by redistribution of mass in, on or above the Earth’s surface or by geophysical processes in the Earth’s interior. The first set of observations of monthly variations of the Earth gravity field was provided by the US / German GRACE satellite mission beginning in 2002. This mission is still providing valuable information to the science community. However, as GRACE has outlived its expected lifetime, the geoscience community is currently seeking suc- cessor missions in order to maintain the long time series of climate change that was begun by GRACE. Several studies on science requirements and technical feasibility have been conducted in the recent years. These studies required a realistic model of the time variable gravity field in order to perform simulation studies on sensitivity of satellites and their instrumentation. This was the primary reason for the European Space Agency (ESA) to initiate a study on “Monitoring and Modelling individual Sources of Mass Distribution and Transport in the Earth System by Means of Satellites”. The goal of this interdisciplinary study was to create as realistic as possible simulated time variable gravity fields based on coupled geophysical models, which could be used in the simulation processes in a controlled environment. For this purpose global atmosphere, ocean, continental hydrology and ice models were used. The coupling was performed by using consistent forcing throughout the models and by including water flow between the di ff erent domains of the Earth system. In addition gravity field changes due to solid Earth processes like continuous glacial isostatic adjustment (GIA) and a sudden earth- quake with co-seismic and post-seismic signals were modelled. All individual model results were combined and converted to gravity field spherical harmonic series, which is the quantity commonly used to describe the Earth’s global gravity field. The result of this study is a twelve-year time-series of 6-hourly time variable gravity field spherical harmonics up to degree and order 180 corresponding to a global spatial resolution of 1 degree in latitude and longitude. In this paper, we outline the input data sets and the process of combining these data sets into a coherent model of temporal gravity field changes. The resulting time series was used in some follow-on studies and is available to anybody interested.