Top PDF Method and means for gravity table automation

Method and means for gravity table automation

Method and means for gravity table automation

Method and means for gravity table automation Abstract A system for gravity table separation including a gravity table for separating materials and a detector operatively associated with the gravity table for detecting the movement of control particles with respect to the gravity table 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.
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Calcium. Table 1: Difference between method means in percent

Calcium. Table 1: Difference between method means in percent

The differences among group means range from -0.2% to 2.8%, with the methods using cresolphthalein complexone and ion selective electrodes having the closest agreement (Table 1). The difference between these two methods meets the suggested bias criterion for 3 out of the 4 samples, while the difference between the other methods’ means is two to three times higher than the suggested measurement bias. Across all four samples, the differences among method means appear similar, which suggests that these differences are mainly due to variances in assay calibration rather than assay specificity. Further studies are needed to verify these assertions.
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Means and method for soil testing

Means and method for soil testing

Means and method for soil testing Abstract An inexpensive device which is easily operated to accurately measure the Coulomb parameters of the soil. The Coulomb parameters are used in Coulomb's equation to calculate the shearing stresses along a failure surface of the soil. The device includes an instrument to test soil shear strength to which several weights have been added. To obtain the Coulomb parameters, the instrument is placed on the soil to be tested and weights are incrementally added to it. The instrument is rotated at each weight increment and the shearing stresses are read from its calibrated dial. The stresses are plotted on a graph from which the Coulomb parameters are determined. The shearing stress of the soil with any known force applied to it can then be determined.
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Method and means for testing soil samples

Method and means for testing soil samples

Method and means for testing soil samples Abstract A device for testing soil samples is comprised of a closed container having an interior compartment with upper and lower portions. A valve is provided for introducing into the closed container a liquid having the general properties of butane, and a second valve is provided in the container for allowing gas in the closed container to exit therefrom. A soil sample filter container is suspended within the container above the bottom portion thereof. A condensation element is mounted in the closed container and positioned above the filter container to cause gas evaporating from the liquid in the container to liquefy as condensate on the
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Means and method of camera space manipulation

Means and method of camera space manipulation

Means and method of camera space manipulation Abstract 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.

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II. THE K-MEANS CLUSTERING METHOD

II. THE K-MEANS CLUSTERING METHOD

A Wireless Sensor Network (WSN) is a network of small sensor nodes which are energy constraint devices and have limited data transmission and computational power. Clustering is an important mechanism in large multi-hop wireless sensor networks for obtaining scalability, reducing energy consumption and achieving better network performance. Most of the research in this area has focused on energy-efficient solutions, but has not thoroughly analyzed the network performance, e.g. in terms of data collection rate and time. In this paper we are presenting the clustering of wireless sensor network by using k-means approach, over a large dynamic network. As it is the oldest and simplest method of clustering. This method requires only local communication and synchronization. Due to growing in area of peer to peer and mobile sensor networks, data analysis in large, dynamic network in large garner importance in the near future. Our algorithm shows best result for the large dynamic network. We tested our algorithm in a simulated environment up to 100 nodes in a dynamic environment and analyze its behavior with good accuracy.
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A Smoothed Analysis of the k-means Method

A Smoothed Analysis of the k-means Method

6. CONCLUDING REMARKS In this paper, we settled the smoothed running time of the k-means method for ar- bitrary k and d. The exponents in our smoothed analysis are constant but large. We did not make a huge effort to optimize the exponents as the arguments are intricate enough even without trying to optimize constants. Furthermore, we believe that our approach, which is essentially based on bounding the smallest possible improvement in a single step, is too pessimistic to yield a bound that matches experimental obser- vations. A similar phenomenon occurred already in the smoothed analysis of the 2-opt heuristic for the TSP [Englert et al. 2007]. There it was possible to improve the bound for the number of iterations by analyzing sequences of consecutive steps rather than single steps. It is an interesting question if this approach also leads to an improved smoothed analysis of k-means.
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How Fast is the k-means Method

How Fast is the k-means Method

We present polynomial upper and lower bounds on the number of iterations per- formed by the k-means method (a.k.a. Lloyd’s method) for k-means clustering. Our upper bounds are polynomial in the number of points, number of clusters, and the spread of the point set. We also present a lower bound, showing that in the worst case the k-means heuristic needs to perform Ω(n) iterations, for n points on the real line and two centers. Surprisingly, the spread of the point set in this construction is poly- nomial. This is the first construction showing that the k-means heuristic requires more than a polylogarithmic number of iterations. Furthermore, we present two alternative algorithms, with guaranteed performance, which are simple variants of the k-means method. Results of our experimental studies on these algorithms are also presented.
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EBK Means: A Clustering Technique based on Elbow Method and K Means in WSN

EBK Means: A Clustering Technique based on Elbow Method and K Means in WSN

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‟
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Improved smoothed analysis of the $k$-means method

Improved smoothed analysis of the $k$-means method

The goal of this paper is to bound the smoothed running-time of the k-means method. There are ba- sically two reasons why the smoothed running-time of the k-means method is a more realistic measure than its worst-case running-time: First, data obtained from measurements is inherently noisy. So even if the original data were a bad instance for k-means, the data mea- sured is most likely a slight perturbation of it. Second, if the data possesses a meaningful k-clustering, then slightly perturbing the data should preserve this clus- tering. Thus, smoothed analysis might help to obtain a faster k-means method: We take the data measured, perturb it slightly, and then run k-means on the per-
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Means and method of detection in chemical separation procedures

Means and method of detection in chemical separation procedures

Means and method of detection in chemical separation procedures Abstract A means and method for indirect detection of constituent components of a mixture separated in a chemical separation process. Fluorescing ions are distributed across the area in which separation of the mixture will occur to provide a generally uniform background fluorescence intensity. For example, the mixture is

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Means and method for ultrasonic measurement of material properties

Means and method for ultrasonic measurement of material properties

Means and method for ultrasonic measurement of material properties Abstract The system for field measurement of texture, stress and related material properties such as formability parameters using ultrasonic velocity measurements through crystalline plate or sheet. Electromagnetic acoustic transducers are utilized to generate, transmit, and receive ultrasonic bursts through the plate at different angular orientations with respect to the plane of the plate. Two of the transducers are driven in series when generating the ultrasonic bursts. Time measurements between transmission and reception of the bursts are precisely derived and converted into velocities. Information regarding stress, texture, and other related material properties such as formability parameters can be derived from these velocity measurements. The system is adjustable to be used for both ferrous and nonferrous crystalline plate. Alteration of the types of ultrasonic waves utilized, and the methods of generating the waves allows different properties such as texture and stress to be derived.
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On a method of construction of new means with applications

On a method of construction of new means with applications

However, the extension of the logarithm, identric and Seiffert means from two to three or more variables does not appear to be obvious from the above expressions of these means. In this sense, we refer the reader to [, –] for some extensions about the logarithmic and identric means. Here, we will derive other extensions of these latter means from our above study. In fact, the above transformation for means with two variables can be imme- diately stated in a similar manner for means involving several variables. For instance, we can define
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A NEW METHOD OF INTEGRATION BY MEANS OF ORTHOGONALITY FOCI*

A NEW METHOD OF INTEGRATION BY MEANS OF ORTHOGONALITY FOCI*

A. A. POPOFF Automechanical Institute, Moscow, U.S.S.R. 1. Introduction. This paper contains a new method of integration which is partly graphical, partly analytical.1 It permits a simple determination of integrals of the form J<t>i{x)<t>k{x)dx, where 4>i(x) is given graphically and tf>k(x) is given either graphi- cally or analytically. The method requires the construction of certain diagrams, called scales, showing the abscissae of the centroids of certain areas associated with <t>kix), and is based on some properties of the so-called orthogonality foci. Finally, the method is applied to interpolation, Fourier analysis, and the evaluation of Mohr in- tegrals in the theory of structures.
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Detection of exoplanets by means of the Bump Detection Method

Detection of exoplanets by means of the Bump Detection Method

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 [8] 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.
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System identification by means of a digital computer method.

System identification by means of a digital computer method.

This online database contains the full-text of PhD dissertations and Masters’ theses of University of Windsor students from 1954 forward. These documents are made available for personal[r]

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INVESTIGATION OF CRUSTAL STRUCTURE OF TURKEY BY MEANS OF GRAVITY DATA

INVESTIGATION OF CRUSTAL STRUCTURE OF TURKEY BY MEANS OF GRAVITY DATA

The surficial waves of the 1999 Turkish earth- quakes obtained from the seismic stations located in western Greece were studied mainly for diffractions of Love waves and the crustal thickness of the northwestern Anatolia was calculated as about 33 km (Novotny et al., 2001). By application of experimental relations to gravity anomaly data, it was determined that the crustal thickness values for Anatolia varies between 26.4 km and 49.5 km (Maden et al., 2005). Later on, two dimensional radial mean power spectrum technique was applied to ano- maly map to find the average regional depth as 47 km. At the second stage, the one dimen- sional sliding window power spectrum method was applied to the same map to investigate the
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Automation and Evaluation of the Keyword Method for Second Language Learning

Automation and Evaluation of the Keyword Method for Second Language Learning

Hummel, 2010; Shen, 2010; Tavakoli and Gerami, 2013). In this method, a target word in a foreign language L2 can be learned by a native speaker of another language L1 in two main steps: 1) one or more L1 words, possibly referring to a concrete entity, are chosen based on orthographic or pho- netic similarity with the target word; 2) an L1 sen- tence is constructed in which an association be- tween the translation of the target word and the keyword(s) is established, so that the learner, when seeing or hearing the word, immediately recalls the keyword(s). To illustrate, for teaching the Ital- ian word cuore which means heart in English, the learner might be asked to imagine “a lonely heart with a hard core”.
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On the Use of Model Transformations for the Automation of the 4SRS Transition Method

On the Use of Model Transformations for the Automation of the 4SRS Transition Method

The problem this paper addresses is the automation of transition methods, particularly those modeled with the SPEM. The 4SRS was modeled with the SPEM in order to formalize it as a software process. It had to be automated so that it could be enlivened by means of a tool. The SPEM was chosen because it is standard, therefore it would be possible to benefit from the advantages of using a standard that is available to every professional of process modeling. Assuming that disciplines are sets of tasks that can be grouped according to their particular relevance in specific phase(s) from large software development processes into which small dedicated software development processes can be plugged into, transition methods are methods that describe how to transform artifacts from one discipline of a large software development process into artifacts from another discipline of such a process.
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A Tanker Port Positioning Method of Quantitative Loading Automation

A Tanker Port Positioning Method of Quantitative Loading Automation

The height data H in the matrix S are filtered to obtain the minimum distance dis to obtain the corresponding angle value β, and the deflection angle θ is obtained by the equation (9). In this experiment, the ideal angle is 180 degrees. The actual shortest distance corresponds to an angle of 182.5 degrees, which means the laser scanning ranging radar coordinate system is deflected by 2.5 degrees in the counterclockwise direction relative to the world coordinate system. Then, in the point of the laser scanning ranging radar coordinate system, the coordinates in the world coordinate system can be obtained by the homogeneous rotation transformation and the homogeneous translation transformation.
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