Center Of Gravity Method Research Articles

Mapped B-spline basis functions for shape design and isogeometric analysis over an arbitrary parameterization

It is well-known that B-spline surfaces are defined by a regular array of control vertices. In case of models with arbitrary topology, it is extremely difficult to maintain continuity conditions among neighboring surfaces. The scenario is also true for applications in isogeometric analysis (IGA). This paper presents a novel method for shape design and isogeometric analysis from a quadrilateral control mesh of arbitrary topology using mapped B-spline basis functions. Based on an arbitrary input quadrilateral control mesh, a global parameterization of the final surface is first defined through a Gravity Center Method (GCM). A re-parameterization method is then applied to map a B-spline basis function to others that are explicitly defined and are tailored to each of the control vertices which can be either regular or extraordinary ones. The final surface is defined by all the input control vertices with their corresponding mapped basis functions. For practical implementation, the surface can be evaluated patch by patch. Depending on the order of the B-spline basis function used for mapping to others, the global continuity of the resulting surface, including at extraordinary points, can be arbitrary higher order. In the present paper, a uniform cubic B-spline basis function is used and the resulting surface is globally C2 continuous. Several numerical examples are provided to demonstrate the proposed method for both shape design and isogeometric analysis.

Study on Cutting Tool Edge Location in the Process of High-Speed Rotation

Cutting tool will arises the hot transmutation in the process of high-speed rotation, in the paper we use the non-contact image acquisition processing system to fix the position of the cutter blade edge basis on the center of gravity method and quadratic curve fitting, this method get rid of disadvantages of traditional contact measurement, have the advantages of high accuracy and calculation simple.

Effectiveness Evaluation of Information Management System Based on Modified Normal Cloud Model

Effectiveness evaluation of the information management system is very complicated. In order to solve this problem, a modified normal cloud model method is conducted in this paper. This method overcomes the shortcomings of traditional cloud gravity center method. The metrology information management system is taken as an example and the effectiveness of the method is verified. It provides a new way for the effectiveness evaluation of information management system.

A model and comparison of 4-wheel-drive fixed-chassis tractor rollover during Phase I

A general model to predict quasi-static articulated tractor instability on a slope has been derived using kineto-static modelling. Under simplifying assumptions, it is possible to model fixed-chassis tractors and, in particular, include the effect of front axle-wheel mass. The model is therefore used in this paper to investigate the effect of front body mass on tractor stability and behaviour during Phase I rollover. The results are of particular relevance to four-wheel-drive (4WD) tractors. The change in potential energy for fixed-chassis tractors during Phase I rollover is also evaluated. The effects of mass partitioning are displayed graphically. It is shown that the stability of a tractor depends on the position of the centre of gravity (COG) of the main (posterior) body. For tractors with massive front wheels, tyres and beam axles, this COG is likely not to be the same as that found from the standard COG methods currently adopted. • Parametric model of tractor rollover initiation for tractors with front mass. • Mass partition properties of tractors important for stability calculation. • Model predicts effect of front mass is significant in terms of stability. • Application of brakes to all wheels potentially reduces full rollover likelihood.

Study on Locating of Focus Surface Position for Aerial Cameras

A system for locating the focus surface position of aerial cameras is designed, and the working principle, hardware composition and software design of the system are described. In the system, a collimator is used for producing locating information, and CCD camera is used as a photoelectric converter for receiving the images. The data is processed by center of gravity method, and the converter controls the translation of the camera in axial direction precisely. The focus surface was determined by size of the collected images. Defocusing or not is judged based on the distance between the actual image location and focal plane. Tests to a couple of aerial cameras show that the defocusing judgment result is the same as the flight test result. Therefore, the system can be used to judge whether the aerial camera is defocusing, and thus to judge whether it can work normally or not.

Two Methods of Improving the Focus Survey Precision Based on CCD Camera

The principium of measuring focus of aerial camera and the location of the actual image plane with CCD camera are introduced, and the methods to improve survey precision are described. The image is received by area CCD camera. The accuracy of orientation of the imaging central line is improved by means of fit the curve method or by center of gravity method. Therefore, the distance between imaging central lines is refinedly calculated. The experimented turn out that the two methods on measuring focus of aerial camera have high precision, and the survey errors are in accordance with the theoretical ones (0.12%). The two methods on deterministic result of the location of the actual image plane are identical, with their precision reaching 100%.

Fuzzy logic for modeling machining process: a review

The application of artificial intelligence (AI) techniques in modeling of machining process has been investigated by many researchers. Fuzzy logic (FL) as a well-known AI technique is effectively used in modeling of machining processes such as to predict the surface roughness and to control the cutting force in various machining processes. This paper is started with the introduction to definition of FL and machining process, and their relation. This paper then presents five types of analysis conducted on FL techniques used in machining process. FL was considered for prediction, selection, monitoring, control and optimization of machining process. Literature showed that milling contributed the highest number of machining operation that was modeled using FL. In terms of machining performance, surface roughness was mostly studied with FL model. In terms of fuzzy components, center of gravity method was mostly used to perform defuzzification, and triangular was mostly considered to perform membership function. The reviews extend the analysis on the abilities, limitations and effectual modifications of FL in modeling based on the comments from previous works that conduct experiment using FL in the modeling and review by few authors. The analysis leads the author to conclude that FL is the most popular AI techniques used in modeling of machining process.

On fuzzy solutions for partial differential equations

In this study we investigate heat, wave and Poisson equations as classical models of partial differential equations (PDEs) with uncertain parameters, considering the parameters as fuzzy numbers. The fuzzy solution is built from fuzzification of the deterministic solution. The continuity of the Zadeh extension is used to obtain qualitative properties on regular α-cuts of the fuzzy solution. We prove the stability with respect to the initial boundary data, and show that as time goes to zero, the diameter of the fuzzy solution converges to zero and, as a consequence, to the cylindrical surface determined by the curve of the degree of membership. Numerical simulations are used to obtain a graphical representation of the fuzzy solution and a defuzzification of this solution is obtained using the center of gravity method. We theoretically show that the surface obtained by defuzzification with the plane determined by fixing time is indeed the solution of the same initial boundary problem for this time-point for the heat and Poisson equations and, in a particular case, for the wave equation. The deterministic solution and the defuzzified surface intercept are numerically compared using the Euclidean distance.

An Automatic Examining-Focus System to Aerial Cameras with CCD

A system is put forward which can automatically measure focus and estimate whether the aerial camera is off-focus and the situation of the factual image plane is in the focus depth range or not. The principle, the hardware composition and the software design are discussed in detail. The system acquires examining-focus information with the optical collimate system, receives images information with CCD camera which can be regarded as optoelectric conversion apparatus, processes data with the center of gravity method, and realizes the axial flow of the CCD camera translation with the grating displacement sensor and the digital readout together. Then, the optimum image situation and the image size can be fixed on. The optimum image situation can be used to judge whether the camera is off-focus, and the image size can be used to calculate the focus. The accurate rate of examining focus can reach almost99.87% and the estimation of off-focus or not accords with experiment result of flight. Use this system, the focus of the lens and the situation of the actual image plane can be judged to accord with the technical standards or not, so that image of high quality can be get with aerial camera.

Precision Focal Measuring System Based on CCD Aerial Cameras

In view of bigger error (0.24%) of conventional measuring method, this paper focuses on a bigger aperture aerial camera focus measuring system and discusses measuring principle and structure of the system. The image in this system is received by the collimator of long focus and area CCD (Charge Coupled Devices) camera. Using dynamic scanning and center of gravity method, the system measures effectively the location and size of the optimum image. The image resolution of CCD can be up to one tenth of the size of the photosensitive sensor and the precision of 0.1percent of focus measuring can be obtained. The problem of the larger error of conventional measuring method is salved fundamentally. The accurate, real-time and on-line measurement of the focus of aerial camera lens can be realized and the exact determination of the position of the surface can be determined.

Study on Logistics Center Site Selection of Jilin Province

Based on the introduction of the concepts of logistics and logistics center, this paper analyzed the status and problems of Jilin Province’s logistics center, and proposed the steps, principles and factors for site selection of logistics center. Then by listing and comparing nine kinds of logistics center site selection method, including Analytic Hierarchy Process, Cluster Algorithm, Genetic Algorithm, Weight Grade Method, P-Median Method, System Simulation Method, Fuzzy quality function method, Dijkstra Method, we chose the best site selection method, namely the center of gravity method. Finally, this paper found out the exact logistics center location of Jilin Province with the center of gravity method.

EOQ in fuzzy environment and trade credit

Now-a-days, the offer of credit period to the retailer for settling the account for the units purchased by the supplier is considered to be the most beneficial policy. In this article, an attempt is made to formulate an economic order quantity model under fuzzy environment where delay in payment for the retailer is permissible. The demand rate, ordering cost and selling price per item are taken as triangular fuzzy numbers. The α-cut representation method is used to calculate the optimum cycle time and total optimum cost. The optimum cycle time and total optimum cost in fuzzy sense is de-fuzzified using the centre of gravity method.

A fuzzy system for cloacal temperature prediction of broiler chickens

Cloacal temperature (CT) of broiler chickens is an important parameter to classify its comfort status; therefore its prediction can be used as decision support to turn on acclimatization systems. The aim of this research was to develop and validate a system using the fuzzy set theory for CT prediction of broiler chickens. The fuzzy system was developed based on three input variables: air temperature (T), relative humidity (RH) and air velocity (V). The output variable was the CT. The fuzzy inference system was performed via Mamdani's method which consisted in 48 rules. The defuzzification was done using center of gravity method. The fuzzy system was developed using MAPLE® 8. Experimental results, used for validation, showed that the average standard deviation between simulated and measured values of CT was 0.13°C. The proposed fuzzy system was found to satisfactorily predict CT based on climatic variables. Thus, it could be used as a decision support system on broiler chicken growth.

Integrated use of fuzzy c-means and convex programming for capacitated multi-facility location problem

In this study a fuzzy c-means clustering algorithm based method is proposed for solving a capacitated multi-facility location problem of known demand points which are served from capacitated supply centres. It involves the integrated use of fuzzy c-means and convex programming. In fuzzy c-means, data points are allowed to belong to several clusters with different degrees of membership. This feature is used here to split demands between supply centers. The cluster number is determined by an incremental method that starts with two and designated when capacity of each cluster is sufficient for its demand. Finally, each group of cluster and each model are solved as a single facility location problem. Then each single facility location problem given by fuzzy c-means is solved by convex programming which optimizes transportation cost is used to fine-tune the facility location. Proposed method is applied to several facility location problems from OR library (Osman & Christofides, 1994) and compared with centre of gravity and particle swarm optimization based algorithms. Numerical results of an asphalt producer's real-world data in Turkey are reported. Numerical results show that the proposed approach performs better than using original fuzzy c-means, integrated use of fuzzy c-means and center of gravity methods in terms of transportation costs.

Spring phytoplankton phenology - are patterns and drivers of change consistent among lakes in the same climatological region?

1. Advancement of phytoplankton peaks has been reported from a large variety of aquatic systems, attributed mostly to climate warming. Most studies have used chlorophyll a as a proxy for phytoplankton biomass. Here, we investigated phenology of three phytoplankton taxa (Asterionella formosa, Aulacoseira spp. and Cryptomonas spp.) in four lakes of the English Lake District situated within the same catchment over a 58-year period (1945–2003). 2. We used two methods (the centre of gravity method and a fitted Weibull-type function) to quantify the timing of the spring bloom. Both methods gave similar results for the diatoms, but not for Cryptomonas spp.. 3. The timing of the spring bloom advanced over the study period for A. formosa but was delayed for Aulacoseira spp. and Cryptomonas spp.. These changes were consistent in all four lakes. 4. We tested whether surface water temperatures prior to the time of phytoplankton peak abundance, winter soluble reactive phosphorus (SRP) and silicate concentrations, winter taxon inoculum, Schmidt stability or a combination of these affected phytoplankton phenology in the four lakes. Results were remarkably consistent: each driver either advanced or delayed the peak of each taxon in all four lakes. However, the different drivers affected the taxa differently. 5. Contrary to our expectations, the regional driver, temperature, did not have a consis-tent effect on the three phytoplankton taxa, significantly advancing A. formosa and Aulacoseira spp. in the North Basin of Windermere but significantly delaying Cryptomonas spp. peaks in three lakes. Overall, the locally variable driver, SRP concentration, had a more consistent effect upon phenology, affecting all taxa in nearly all lakes.

Subway Train Braking System: A Fuzzy Based Hardware Approach

Problem statement: Automated subway train-braking system require perfection, efficiency and fast response. In order to cope with this conce rns, an appropriate algorithm need to be developed which need to be implemented in hardware for faster response. Approach: In this research, the FPGA realization of fuzzy based subway train braking sys tem has been presented on an Alter FLEX10K device to provide an accurate and increased speed o f convergence of the network. The fuzzy based subway train braking system is comprised of fusilie r, inference, rule selector and defuzzifier modules . Sixteen rules are identified for the rule selector module. After determining the membership functions and its fuzzy variables, the Max-Min Composition method and Madman-Min implication operator are used for the inference module and the Centre of Gra vity method is used for the defuzzification module. Each module is modeled individually using behavioral VHDL. The layers are then connected using structural VHDL. Two 8-bit and one 8-bit unsigned digital signals are used for input and output respectively. Six ROMs are defined in order to decr ease the chances of processing and increasing the throughput of the system. Results: Functional simulations were commenced to verify the functionality of the individual modules and the system as well. W e have validated the hardware implementation of the proposed approach through comparison, verificat ion and analysis. The design has utilized 2372 units of LC with a system frequency of 139.8MHz. Conclusion: In this research, the FPGA realization of fuzzy brake system of subway train has been succ essfully implemented with minimum usage of logic cells. The validation study with C model show s that the hardware model is appropriate and the hardware approach shows faster and accurate response with full automatic control.

Fuzzy Control of an AGV Obstacle Avoidance System in Unknown Environments

An avoiding obstacle fuzzy controller for AGV is presented in this paper. Multi-sensors are used to detect obstacles information. The fuzzy controller processes the distance of obstacles by using a 3×3 rule table. As to convert the fuzzy output into non-fuzzy value, Centre of Gravity Method (COG) is used to calculate an accurate control output. This fuzzy control algorithm can solve the problem of obstacle avoidance in unknown environment. And the AGV running path is smooth and the changing of speed is moderate.

First tests in the application of silicon photomultiplier arrays to dose monitoring in hadron therapy

Abstract A detector head composed of a continuous LaBr3 crystal coupled to a silicon photomultiplier array has been mounted and tested, for its use in a Compton telescope for dose monitoring in hadron therapy. The LaBr3 crystal has 16 mm×18 mm×5 mm size, and it is surrounded with reflecting material in five faces. The SiPM array has 16 (4 ×4) elements of 3 mm×3 mm size. The SPIROC1 ASIC has been employed as readout electronics. The detector shows a linear behavior up to 1275 keV. The energy resolution obtained at 511 keV is 7% FWHM, and it varies as one over the square root of the energy up to the energies tested. The variations among the detector channels are within 12%. A preliminary measurement of the timing resolution gives 7 ns FWHM. The spatial resolution obtained with the center of gravity method is 1.2 mm FWHM. The tests performed confirm the correct functioning of the detector.

Use of center of gravity with the common vector approach in isolated word recognition

In this paper, the subspace based classifier, common vector approach (CVA), with the center of gravity (COG) method is used for isolated word recognition. Since the CVA classifier is sensitive to shifts through the time axis, endpoint detection becomes extremely important for the recognition of isolated words. The COG method eliminates the need for endpoint detection. The effects of the COG method and a classical endpoint detection algorithm on the recognition rates of isolated words are investigated. The experimental results show that the COG method yields slightly higher recognition rates than the endpoint detection method in the TI-digit database when CVA is used.

Rigorous pulse detection from full-waveform airborne laser scanning data

Current discrete airborne laser scanning (ALS) systems suffer from a limited number of multiple returns and the loss of information about range estimation. To improve range resolution and accuracy, latest generation small-footprint, full-waveform laser scanning data were investigated and an approach developed to determine the number of targets within complex waveforms. The approach, termed rigorous Gaussian detection (RGD), is based on the popular Gaussian decomposition method but is implemented with rigorous estimates of initial values and a sophisticated iteration procedure. Second derivatives of waveforms and the number of samples on the edges of visible peaks were analysed to find overlapping targets. Weak pulses were detected where the residuals of Gaussian fitting were high and corresponding pulse widths were close to that of the transmitted pulse. The performance was compared with two other pulse detection techniques from commercial software, namely the centre of gravity (COG) method and the Gaussian pulse fitting (GPF) method with the Levenberg–Marquardt iterative algorithm. The results proved that the developed pulse detection method resolved multi-targets well. For example, in a sample of 201 dual-target waveforms, the RGD method correctly detected two targets in all the samples, considerably outperforming the COG and GPF methods, which achieved 57% and 67% success rates, respectively. When measuring the target heights using the different methods, the RGD method, with a root mean square error (RMSE) of 0.06 m, proved twice as accurate as the next best method, COG. The developed approach therefore compares favourably against the two commercial pulse detection methods considered, where their failure to detect hidden targets within complex waveforms and weak pulses resulted in a decrease of multi-target resolution, unreliable three-dimensional (3D) points, and also the loss of information from weak pulses.