Application of Maximum Probability Approach to the Fault Diagnosis of a Servo System

In an actual control system, it is often difficult to find out where the faults are if only based on the outside fault phenomena, acquired frequently from a fault system. So the fault diagnosis by outside fault phenomena is considered. Based on the theory of fuzzy recognition and fault diagnosis, this method only depends on experience and statistical data to set up fuzzy query relationship between the outside phenomena (fault characters) and the fault sources (fault patterns). From this relationship the most probable fault sources can be obtained, to attain the goal of quick diagnosis. Based on the above approach, the standard fuzzy relationship matrix is stored in the computer as a system database. And experiment data are given to show the fault diagnosis results. The important parameters can be on line sampled and analyzed, and when faults occur, faults can be found, the alarm is given and the controller output is regulated.

Homogenized Daily Mean/Maximum/Minimum Temperature Series for China from 1960-2008

Inhomogeneities in the daily mean/maximum/ minimum temperature （Tm/Tmax/Tmin） series from 1960- 2008 at 549 National Standard Stations （NSSs） in China were analyzed by using the Multiple Analysis of Series for Homogenization （MASH） software package. Typical biases in the dataset were illustrated via the cases of Beijing （B J）, Wutaishan （WT）, Urumqi （UR） and Henan （HN） stations. The homogenized dataset shows a mean warming trend of 0.261/0.193/0.344℃/decade for the annual series of Tm/Tmax/Tmin, slightly smaller than that of the original dataset by 0.006/0.009/0.007℃/decade. However, considerable differences between the adjusted and original datasets were found at the local scale. The adjusted Tmin series shows a significant warming trend almost everywhere for all seasons, while there are a number of stations with an insignificant trend in the original dataset. The adjusted Tm data exhibit significant warming trends annually as well as for the autumn and winter seasons in northern China, and cooling trends only for the summer in the middle reaches of the Yangtze River and parts of central China and for the spring in southwestern China, while the original data show cooling trends at several stations for the annual and seasonal scales in the Qinghai, Shanxi, Hebei, and Xinjiang provinces. The adjusted Tmax data exhibit cooling trends for summers at a number of stations in the mid-lower reaches of the Yangtze and Yellow Rivers and for springs and winters at a few stations in southwestern China, while the original data show cooling trends at three/four stations for the annual/autumn periods in the Qinghai and Yunnan provinces. In general, the number of stations with a cooling trend was much smaller in the adjusted Tm and Tmax dataset than in the original dataset. The cooling trend for summers is mainly due to cooling in August. The results of homogenization using MASH appear to be robust; in particular, different groups of stations with consideration of elevation led to minor effects in the results.

Analysis of Sampling Error Uncertainties and Trends in Maximum and Minimum Temperatures in China

In this paper we report an analysis of sampling error uncertainties in mean maximum and minimum temperatures （Tmax and Tmin） carried out on monthly,seasonal and annual scales,including an examination of homogenized and original data collected at 731 meteorological stations across China for the period 1951-2004.Uncertainties of the gridded data and national average,linear trends and their uncertainties,as well as the homogenization effect on uncertainties are assessed.It is shown that the sampling error variances of homogenized Tmax and Tmin,which are larger in winter than in summer,have a marked northwest-southeast gradient distribution,while the sampling error variances of the original data are found to be larger and irregular.Tmax and Tmin increase in all months of the year in the study period 1951-2004,with the largest warming and uncertainties being 0.400℃ （10 yr）-1 ＋ 0.269℃ （10 yr）-1 and 0.578℃ （10 yr）-1 ＋ 0.211℃ （10 yr）-1 in February,and the least being 0.022℃ （10 yr）-1 ＋ 0.085℃ （10 yr）-1 and 0.104℃ （10 yr）-1 ＋0.070℃ （10 yr）-1 in August.Homogenization can remove large uncertainties in the original records resulting from various non-natural changes in China.

THE MAXIMUM AND MINIMUM DEGREES OF RANDOM BIPARTITE MULTIGRAPHS

In this paper the authors generalize the classic random bipartite graph model, and define a model of the random bipartite multigraphs as follows：let m = m（n） be a positive integer-valued function on n and ζ（n,m;{pk}） the probability space consisting of all the labeled bipartite multigraphs with two vertex sets A ={a_1,a_2,...,a_n} and B = {b_1,b_2,...,b_m}, in which the numbers t_（ai）,b_j of the edges between any two vertices a_i∈A and b_j∈ B are identically distributed independent random variables with distribution P{t_（ai）,b_j=k}=pk,k=0,1,2,...,where pk ≥0 and ∞Σk=0 pk=1. They obtain that X_（c,d,A）, the number of vertices in A with degree between c and d of G_（n,m）∈ζ（n, m;{pk}） has asymptotically Poisson distribution, and answer the following two questions about the space ζ（n,m;{pk}） with {pk} having geometric distribution, binomial distribution and Poisson distribution, respectively. Under which condition for {pk} can there be a function D（n） such that almost every random multigraph G_（n,m）∈ζ（n,m;{pk}） has maximum degree D（n）in A？ under which condition for {pk} has almost every multigraph G（n,m）∈ζ（n,m;{pk}） a unique vertex of maximum degree in A？

A mathematical approach to evaluate maximum frost heave of unsaturated silty clay

Maximum frost heave of unsaturated frost-susceptible soils,in conjunction with a high water table,is an important consideration for the design of foundations in seasonally frozen regions.Therefore,it is necessary to evaluate accurately and efficiently the maximum frost heave for a given soil.For this purpose,a series of one-sided freezing experiments was conducted on unsaturated silty clay in an open system.Multistage cooling of sufficient duration was applied to the soil sample's top,while constant above-zero temperatures were maintained at the bottom.Then,a simple methodology for calculating maximum frost heave at a given cooling temperature was derived utilizing information obtained within the limited time allotted for each stage.On this basis,an empirical equation for defining maximum frost heave as a function of cooling temperature and overburden pressure was determined.Overall,this study provides a simple and practical procedure that is applicable to the evaluation of maximum frost heave of unsaturated frost-susceptible soils.

Minimum and Maximum Temperature Trends in Congo-Brazzaville: 1932-2010

Maximum and minimum temperatures time series of Congo-Brazzaville are analyzed for trend and discontinuities over the period 1932 to 2010. Temperatures series show an irregular increase. A total of 8 synoptic stations show positive trends in their annual mean maximum temperature series, and 7 of them are significant, with higher trends for urban stations. Annual mean minimum temperature showed 6 stations having positive trends. This increase is in relation with observations at regional scale. However, the differences are observed between large towns (Brazzaville and Pointe-Noire), and small or rural towns (Dolisie, Sibiti, Impfondo, Djambala). Trends in diurnal temperature range (DTR) are large positive trends in maximum temperature that are mainly observed in cities. The curve of DTR shows a decreasing trend which indicates the increasing of minimum temperatures. The effects of urbanization on temperature trends are investigated. Most stations regarded as urban stations are still useful for trend analysis;being situated on the suburban of the studied cities, they are therefore, not substantially influenced by the urban heat island.

Asymmetrical Change Characteristics of Maximum and Minimum Temperatures in Shangqiu in Recent 50 Years

[Objective] The research aimed to analyze temporal and spatial variation characteristics of temperature in Shangqiu City during 1961-2010.[Method] Based on temperature data in eight meteorological stations of Shangqiu during 1961-2010,by using trend analysis method,the temporal and spatial evolution characteristics of annual average temperature,annual average maximum and minimum temperatures,annual extreme maximum and minimum temperatures,daily range of annual average temperature in Shangqiu City were analyzed.M-K method was used to determine mutation year of temperature.[Result] The annual average temperature,annual average minimum temperature and annual extreme minimum temperature respectively rose at 0.122,0.255 and 0.488 ℃/10 a.The variation trend of annual average maximum temperature wasn’t obvious.The daily range of annual average temperature and annual extreme maximum temperature respectively declined at-0.217 and-0.292 ℃/10 a.Seen from spatial distribution,the increase amplitudes of annual average temperature,annual average minimum temperature and annual extreme minimum temperature were all large in the east and small in the west.The decrease amplitude of daily range of annual average temperature was large in the east and small in the west.The decrease amplitude of annual extreme maximum temperature was large in the west and small in the east.The annual average maximum temperature had trends of increase and decrease.The annual average temperature,annual average minimum temperature and daily range of annual average temperature all mutated in 1997.The annual average maximum temperature didn’t have obvious mutation point.The annual extreme maximum temperature mutated in 1973.The annual extreme minimum temperature respectively mutated in 1989 and 1999.[Conclusion] The research played important guidance significances in adjustment of agricultural production structure,regional climate planning,reasonably using climate resource and replying climate change in Shangqiu City.

Treatment of Skeletal CL II Patient with Maximum Lower Incisor Protrusion and Minimum Overjet with Rahhal Functional Appliance

Treatment of skeletal Cl II includes functional orthopedic treatment, head-gears, extraction of the upper premolars and orthognathic surgery. To treat any patient with functional appliances (bite jumping) an adequate overjet is necessary. In this case an 11 years old female patient has skeletal CLII due to mandibular deficiency with ANB angle 8 degrees, overbite: 3 mm, overjet: 1 mm, extremely convex profile and underdeveloped chin due to the hyper muscle contraction of the lower lip to obtain oral seal. To obtain an adequate overjet lower first premolars were extracted and maximum retraction using mini screws (for maximum anchorage) was applied. Afterwards Rahhal functional appliance was used by the patient 16 hours a day for 6 months and 10 hours a day for another 6 months for retention. After that fixed orthodontic treatment was completed. Lateral cephalometrics were taken, traced and analyzed. In the result Skeletal CLI was obtained (ANB 4 degree), straight facial profile, normal over bite overjet and particular chin development were noticed. As a conclusion, in skeletal CLII malocclusions, lower incisor protrusion will cause a contraindication for functional treatment. Extraction of the lower premolars and retraction of the lower incisors followed by functional orthopedic treatment is an efficient method to treat these cases instead of waiting for orthognathic surgery, also reducing the muscle pressure on the chin will change the development characteristics of it.

The Joint Distribution of the Maximum Excursion and the Minimum Excursion for Brownian Motion with Drift

In this paper, we discuss the problem of extreme value for Brownian motion with positive drift. We obtain the joint distribution of the maximum excursion and the minimum excursion.

Distribution of the Maximum and Minimum of a Random Number of Bounded Random Variables

We study a new family of random variables that each arise as the distribution of the maximum or minimum of a random number N of i.i.d. random variables X1, X2,…, XN, each distributed as a variable X with support on [0, 1]. The general scheme is first outlined, and several special cases are studied in detail. Wherever appropriate, we find estimates of the parameter θ in the one-parameter family in question.

Application of Machine-Learning-Based Objective Correction Method in the Intelligent Grid Maximum and Minimum Temperature Predictions

Post-processing correction is an effective way to improve the model forecasting result. Especially, the machine learning methods have played increasingly important roles in recent years. Taking the meteorological observational data in a period of two years as the reference, the maximum and minimum temperature predictions of Shenyang station from the European Center for Medium-Range Weather Forecasts (ECMWF) and national intelligent grid forecasts are objectively corrected by using wavelet analysis, sliding training and other technologies. The evaluation results show that the sliding training time window of the maximum temperature is smaller than that of the minimum temperature, and their difference is the largest in August, with a difference of 2.6 days. The objective correction product of maximum temperature shows a good performance in spring, while that of minimum temperature performs well throughout the whole year, with an accuracy improvement of 97% to 186%. The correction effect in the central plains is better than in the regions with complex terrain. As for the national intelligent grid forecasts, the objective correction products have shown positive skills in predicting the maximum temperatures in spring (the skill-score reaches 0.59) and in predicting the minimum temperature at most times of the year (the skill-score reaches 0.68).

Minimum Expenses,Maximum Savings:How to Live in China Smartly

For more information,please click www.echinacities.com While it's at least very annoying,and at most woefully erroneous that many Chinese people judge all foreigners to be totally minted,it's not hard to see why,when many foreigners are here living decadent lifestyles,partying on weekends(and weekdays),travelling all over the country and mincing around town with Macbooks,iPods and Ray Bans.But then there are the secret 'squirrelers',who scrimp together just enough cash to

On the Distribution of the Minimum or Maximum of a Random Number of i.i.d. Lifetime Random Variables

Statisticians are usually concerned with the proposition of new distributions. In this paper we point out that a unified and concise derivation procedure of the distribution of the minimum or maximum of a random number N of indepen-dent and identically distributed continuous random variables Yi,{i = 1,2,…,N} is obtained if one compounds the probability generating function of N with the survival or the distribution func-tion of Yi. Expressions are then derived in closed form for the density, hazard and quantile func-tions of the minimum or maximum. The methodology is illustrated with examples of the distributions proposed by Adamidis and Loukas (1998), Kus (2007), Tahmasbi and Rezaei (2008), Barreto-Souza and Cribari-Neto (2009), Cancho, Louzada, and Barriga (2011) and Louzada, Roman and Cancho (2011).

An Optimal DASH Diet Model for People with Hypertension Using Linear Programming Approach

Selecting diets by quantitative techniques is becoming increasingly common. Linear programming is the most popular technique for the selection of least cost mixes of food to meet specific nutritional requirements for a particular group of persons for either general health or disease-related reason. Hypertension is a silent killer and its prevalence rate especially in the developing countries, which has been mostly associated to demographic, environmental and genetic factors, is becoming alarming. The DASH diet has been clinically proven to prevent and control hypertension. In this paper, a model that provides a Daily Optimal (minimum cost) DASH Diet plan for people with hypertension is formulated. The objective is to obtain daily minimum cost diet plans that satisfy the DASH Diets’ nutrients Tolerable Upper and Lower Intake for different daily Calorie Levels. The formulated DASH diet model was further illustrated using real data set with food samples gotten from the DASH eating plan chart. A DASH diet model for a hypertensive person with a 2000-daily-caloric need was formulated and its optimal diet plan for a day obtained with a total cost of 944.41 Naira. Optimal diet plans for other recommended daily calorie levels were also obtained.

Vertex Cover Optimization Using a Novel Graph Decomposition Approach

The minimum vertex cover problem(MVCP)is a well-known combinatorial optimization problem of graph theory.The MVCP is an NP(nondeterministic polynomial)complete problem and it has an exponential growing complexity with respect to the size of a graph.No algorithm exits till date that can exactly solve the problem in a deterministic polynomial time scale.However,several algorithms are proposed that solve the problem approximately in a short polynomial time scale.Such algorithms are useful for large size graphs,for which exact solution of MVCP is impossible with current computational resources.The MVCP has a wide range of applications in the fields like bioinformatics,biochemistry,circuit design,electrical engineering,data aggregation,networking,internet traffic monitoring,pattern recognition,marketing and franchising etc.This work aims to solve the MVCP approximately by a novel graph decomposition approach.The decomposition of the graph yields a subgraph that contains edges shared by triangular edge structures.A subgraph is covered to yield a subgraph that forms one or more Hamiltonian cycles or paths.In order to reduce complexity of the algorithm a new strategy is also proposed.The reduction strategy can be used for any algorithm solving MVCP.Based on the graph decomposition and the reduction strategy,two algorithms are formulated to approximately solve the MVCP.These algorithms are tested using well known standard benchmark graphs.The key feature of the results is a good approximate error ratio and improvement in optimum vertex cover values for few graphs.

Improving Energy and Power Efficiency Using NComputing and Approaches for Predicting Reliability of Complex Computing Systems

Opting to follow the computing-design philosophy that the best way to reduce power consumption and increase energy efficiency is to reduce waste, we propose an architecture with a very simple ready-implementation by using an NComputing device that can allow multi-users but only one computer is needed. This intuitively can save energy, space as well as cost. In this paper, we propose a simple and realistic NComputing architecture to study the energy and power-efficient consumption of desktop computer systems by using the NComputing device. We also propose new approaches to estimate the reliability of k-out-of-n systems based on the delta method. The k-out-of-n system consisting of n subsystems works if and only if at least k-of-the-n subsystems work. More specificly, we develop approaches to obtain the reliability estimation for the k-out-of-n systems which is composed of n independent and identically distributed subsystems where each subsystem （or energy-efficient usage application） can be assumed to follow a two-parameter exponential lifetime distribution function. The detailed derivations of reliability estimation of k-out-of-n systems based on the biased-corrected estimator, known as delta method, the uniformly minimum variance unbiased estimate （UMVUE） and maximum likelihood estimate （MLE） are discussed. An energy-management NComputing application is discussed to illustrate the reliability results in terms of the energy consumption usages of a computer system with qua（t-core, 8 GB of RAM, and a GeForce 9800GX-2 graphics card to perform various complex applications. The estimated reliability values of systems based on the UMVUE and the delta method differ only slightly. Often the UMVUE of reliability for a complex system is a lot more difficult to obtain, if not impossible. The delta method seems to be a simple and better approach to obtain the reliability estimation of complex systems. The results of this study also show that, in practice, the NComputing architecture improves both energy cost saving and energy efficient living spaces.

An Approach to Fault Diagnosis of Rotating Machinery Using the Second-Order Statistical Features of Thermal Images and Simplified Fuzzy ARTMAP

Thermal image, or thermogram, becomes a new type of signal for machine condition monitoring and fault diagnosis due to the capability to display real-time temperature distribution and possibility to indicate the machine’s operating condition through its temperature. In this paper, an investigation of using the second-order statistical features of thermogram in association with minimum redundancy maximum relevance (mRMR) feature selection and simplified fuzzy ARTMAP (SFAM) classification is conducted for rotating machinery fault diagnosis. The thermograms of different machine conditions are firstly preprocessed for improving the image contrast, removing noise, and cropping to obtain the regions of interest (ROIs). Then, an enhanced algorithm based on bi-dimensional empirical mode decomposition is implemented to further increase the quality of ROIs before the second-order statistical features are extracted from their gray-level co-occurrence matrix (GLCM). The highly relevant features to the machine condition are selected from the total feature set by mRMR and are fed into SFAM to accomplish the fault diagnosis. In order to verify this investigation, the thermograms acquired from different conditions of a fault simulator including normal, misalignment, faulty bearing, and mass unbalance are used. This investigation also provides a comparative study of SFAM and other traditional methods such as back-propagation and probabilistic neural networks. The results show that the second-order statistical features used in this framework can provide a plausible accuracy in fault diagnosis of rotating machinery.

Tree Network Formation in Poisson Equation Models and the Implications for the Maximum Entropy Production Principle

This paper presents not only practical but also instructive mathematical models to simulate tree network formation using the Poisson equation and the Finite Difference Method (FDM). Then, the implications for entropic theories are discussed from the viewpoint of Maximum Entropy Production (MEP). According to the MEP principle, open systems existing in the state far from equilibrium are stabilized when entropy production is maximized, creating dissipative structures with low entropy such as the tree-shaped network. We prepare two simulation models: one is the Poisson equation model that simulates the state far from equilibrium, and the other is the Laplace equation model that simulates the isolated state or the state near thermodynamic equilibrium. The output of these equations is considered to be positively correlated to entropy production of the system. Setting the Poisson equation model so that entropy production is maximized, tree network formation is advanced. We suppose that this is due to the invocation of the MEP principle, that is, entropy of the system is lowered by emitting maximal entropy out of the system. On the other hand, tree network formation is not observed in the Laplace equation model. Our simulation results will offer the persuasive evidence that certifies the effect of the MEP principle.

Thailand-Japan＇s Volume of Trade Influencing on Socio-economic and Well-Being Development Using Maximum Entropy Bootstrap

This paper is preliminary information on some empirical findings based on an analysis of Thailand＇s macroeconomic data. The purpose of the study is to quantify social-economic well-being development with special emphasis on poverty. The maximum entropy bootstrap was presented that did not require the property of stationarity. Moreover, the methodology was stratified both the ergodic theorem and the central limit theorem. Thailand＇s GINI index and Thailand-Japan＇s volume of trade data cover the 14-year period from 1998 to 2011. There is a statistically significant negative non-linear relationship between endogenous Thailand＇s GINI index and exogenous Thailand-Japan＇s volume of trade. The results confirmed that every lagged one percent increase in Thailand-Japan＇s volume of trade influenced by a decrease of Thailand＇s GINI index coefficient 0.039 percent with the asymmetric around 0-almost closed to range condition -0.034824348 at 2.5%.

Minimum Cost of Capacity Expansion for Time-Limited Transportation Problem On-Demand

The minimum cost of capacity expansion for time-limited transportation problem on-demand (MCCETLTPD) is to find such a practicable capacity expansion transportation scheme satisfying the time-limited T along with all origins’ supply and all destinations’ demands as well as the expanding cost is minimum. Actually, MCCETLTPD is a balance transportation problem and a variant problem of minimum cost maximum flow problem. In this paper, by creating a mathematical model and constructing a network with lower and upper arc capacities, MCCETLTPD is transformed into searching feasible flow in the constructed network, and consequently, an algorithm MCCETLTPD-A is developed as MCCETLTPD’s solution method basing minimum cost maximum flow algorithm. Computational study validates that the MCCETLTPD-A algorithm is an efficient approach to solving the MCCETLTPD.