Estimation of nonparametric probability density functions with applications to automatic speech recognition

Magdeburg, Univ., Fak. für Elektrotechnik und Informationstechnik, Diss., 2007

Molecular determinants for the subcellular distribution of the synapto-nuclear protein messenger Jacob

Magdeburg, Univ., Fak. für Naturwiss., Diss., 2010

A determinação dos números de indivíduos mínimos necessários na experimentação genética

The main object of the present paper consists in giving formulas and methods which enable us to determine the minimum number of repetitions or of individuals necessary to garantee some extent the success of an experiment. The theoretical basis of all processes consists essentially in the following. Knowing the frequency of the desired p and of the non desired ovents q we may calculate the frequency of all possi- ble combinations, to be expected in n repetitions, by expanding the binomium (p-+q)n. Determining which of these combinations we want to avoid we calculate their total frequency, selecting the value of the exponent n of the binomium in such a way that this total frequency is equal or smaller than the accepted limit of precision n/pª{ 1/n1 (q/p)n + 1/(n-1)| (q/p)n-1 + 1/ 2!(n-2)| (q/p)n-2 + 1/3(n-3) (q/p)n-3... < Plim - -(1b) There does not exist an absolute limit of precision since its value depends not only upon psychological factors in our judgement, but is at the same sime a function of the number of repetitions For this reasen y have proposed (1,56) two relative values, one equal to 1-5n as the lowest value of probability and the other equal to 1-10n as the highest value of improbability, leaving between them what may be called the "region of doubt However these formulas cannot be applied in our case since this number n is just the unknown quantity. Thus we have to use, instead of the more exact values of these two formulas, the conventional limits of P.lim equal to 0,05 (Precision 5%), equal to 0,01 (Precision 1%, and to 0,001 (Precision P, 1%). The binominal formula as explained above (cf. formula 1, pg. 85), however is of rather limited applicability owing to the excessive calculus necessary, and we have thus to procure approximations as substitutes. We may use, without loss of precision, the following approximations: a) The normal or Gaussean distribution when the expected frequency p has any value between 0,1 and 0,9, and when n is at least superior to ten. b) The Poisson distribution when the expected frequecy p is smaller than 0,1. Tables V to VII show for some special cases that these approximations are very satisfactory. The praticai solution of the following problems, stated in the introduction can now be given: A) What is the minimum number of repititions necessary in order to avoid that any one of a treatments, varieties etc. may be accidentally always the best, on the best and second best, or the first, second, and third best or finally one of the n beat treatments, varieties etc. Using the first term of the binomium, we have the following equation for n: n = log Riim / log (m:) = log Riim / log.m - log a --------------(5) B) What is the minimun number of individuals necessary in 01der that a ceratin type, expected with the frequency p, may appaer at least in one, two, three or a=m+1 individuals. 1) For p between 0,1 and 0,9 and using the Gaussean approximation we have: on - ó. p (1-p) n - a -1.m b= δ. 1-p /p e c = m/p } -------------------(7) n = b + b² + 4 c/ 2 n´ = 1/p n cor = n + n' ---------- (8) We have to use the correction n' when p has a value between 0,25 and 0,75. The greek letters delta represents in the present esse the unilateral limits of the Gaussean distribution for the three conventional limits of precision : 1,64; 2,33; and 3,09 respectively. h we are only interested in having at least one individual, and m becomes equal to zero, the formula reduces to : c= m/p o para a = 1 a = { b + b²}² = b² = δ2 1- p /p }-----------------(9) n = 1/p n (cor) = n + n´ 2) If p is smaller than 0,1 we may use table 1 in order to find the mean m of a Poisson distribution and determine. n = m: p C) Which is the minimun number of individuals necessary for distinguishing two frequencies p1 and p2? 1) When pl and p2 are values between 0,1 and 0,9 we have: n = { δ p1 ( 1-pi) + p2) / p2 (1 - p2) n= 1/p1-p2 }------------ (13) n (cor) We have again to use the unilateral limits of the Gaussean distribution. The correction n' should be used if at least one of the valors pl or p2 has a value between 0,25 and 0,75. A more complicated formula may be used in cases where whe want to increase the precision : n (p1 - p2) δ { p1 (1- p2 ) / n= m δ = δ p1 ( 1 - p1) + p2 ( 1 - p2) c= m / p1 - p2 n = { b2 + 4 4 c }2 }--------- (14) n = 1/ p1 - p2 2) When both pl and p2 are smaller than 0,1 we determine the quocient (pl-r-p2) and procure the corresponding number m2 of a Poisson distribution in table 2. The value n is found by the equation : n = mg /p2 ------------- (15) D) What is the minimun number necessary for distinguishing three or more frequencies, p2 p1 p3. If the frequecies pl p2 p3 are values between 0,1 e 0,9 we have to solve the individual equations and sue the higest value of n thus determined : n 1.2 = {δ p1 (1 - p1) / p1 - p2 }² = Fiim n 1.2 = { δ p1 ( 1 - p1) + p1 ( 1 - p1) }² } -- (16) Delta represents now the bilateral limits of the : Gaussean distrioution : 1,96-2,58-3,29. 2) No table was prepared for the relatively rare cases of a comparison of threes or more frequencies below 0,1 and in such cases extremely high numbers would be required. E) A process is given which serves to solve two problemr of informatory nature : a) if a special type appears in n individuals with a frequency p(obs), what may be the corresponding ideal value of p(esp), or; b) if we study samples of n in diviuals and expect a certain type with a frequency p(esp) what may be the extreme limits of p(obs) in individual farmlies ? I.) If we are dealing with values between 0,1 and 0,9 we may use table 3. To solve the first question we select the respective horizontal line for p(obs) and determine which column corresponds to our value of n and find the respective value of p(esp) by interpolating between columns. In order to solve the second problem we start with the respective column for p(esp) and find the horizontal line for the given value of n either diretly or by approximation and by interpolation. 2) For frequencies smaller than 0,1 we have to use table 4 and transform the fractions p(esp) and p(obs) in numbers of Poisson series by multiplication with n. Tn order to solve the first broblem, we verify in which line the lower Poisson limit is equal to m(obs) and transform the corresponding value of m into frequecy p(esp) by dividing through n. The observed frequency may thus be a chance deviate of any value between 0,0... and the values given by dividing the value of m in the table by n. In the second case we transform first the expectation p(esp) into a value of m and procure in the horizontal line, corresponding to m(esp) the extreme values om m which than must be transformed, by dividing through n into values of p(obs). F) Partial and progressive tests may be recomended in all cases where there is lack of material or where the loss of time is less importent than the cost of large scale experiments since in many cases the minimun number necessary to garantee the results within the limits of precision is rather large. One should not forget that the minimun number really represents at the same time a maximun number, necessary only if one takes into consideration essentially the disfavorable variations, but smaller numbers may frequently already satisfactory results. For instance, by definition, we know that a frequecy of p means that we expect one individual in every total o(f1-p). If there were no chance variations, this number (1- p) will be suficient. and if there were favorable variations a smaller number still may yield one individual of the desired type. r.nus trusting to luck, one may start the experiment with numbers, smaller than the minimun calculated according to the formulas given above, and increase the total untill the desired result is obtained and this may well b ebefore the "minimum number" is reached. Some concrete examples of this partial or progressive procedure are given from our genetical experiments with maize.

Estudo comparativo entre métodos de contrôle quantitativo da produção leiteira

This paper deals with the estimation of milk production by means of weekly, biweekly, bimonthly observations and also by method known as 6-5-8, where one observation is taken at the 6th week of lactation, another at 5th month and a third one at the 8th month. The data studied were obtained from 72 lactations of the Holstein Friesian breed of the "Escola Superior de Agricultura "Luiz de Queiroz" (Piracicaba), S. Paulo, Brazil), being 6 calvings on each month of year and also 12 first calvings, 12 second calvings, and so on, up to the sixth. The authors criticize the use of "maximum error" to be found in papers dealing with this subject, and also the use of mean deviation. The former is completely supersed and unadvisable and latter, although equivalent, to a certain extent, to the usual standard deviation, has only 87,6% of its efficiency, according to KENDALL (9, pp. 130-131, 10, pp. 6-7). The data obtained were compared with the actual production, obtained by daily control and the deviations observed were studied. Their means and standard deviations are given on the table IV. Inspite of BOX's recent results (11) showing that with equal numbers in all classes a certain inequality of varinces is not important, the autors separated the methods, before carrying out the analysis of variance, thus avoiding to put together methods with too different standard deviations. We compared the three first methods, to begin with (Table VI). Then we carried out the analysis with the four first methods. (Table VII). Finally we compared the two last methods. (Table VIII). These analysis of variance compare the arithmetic means of the deviations by the methods studied, and this is equivalent to compare their biases. So we conclude tht season of calving and order of calving do not effect the biases, and the methods themselves do not differ from this view point, with the exception of method 6-5-8. Another method of attack, maybe preferrable, would be to compare the estimates of the biases with their expected mean under the null hypothesis (zero) by the t-test. We have: 1) Weekley control: t = x - 0/c(x) = 8,59 - 0/ = 1,56 2) Biweekly control: t = 11,20 - 0/6,21= 1,80 3) Monthly control: t = 7,17 - 0/9,48 = 0,76 4) Bimonthly control: t = - 4,66 - 0/17,56 = -0,26 5) Method 6-5-8 t = 144,89 - 0/22,41 = 6,46*** We denote above by three asterisks, significance the 0,1% level of probability. In this way we should conclude that the weekly, biweekly, monthly and bimonthly methods of control may be assumed to be unbiased. The 6-5-8 method is proved to be positively biased, and here the bias equals 5,9% of the mean milk production. The precision of the methods studied may be judged by their standard deviations, or by intervals covering, with a certain probability (95% for example), the deviation x corresponding to an estimate obtained by cne of the methods studied. Since the difference x - x, where x is the mean of the 72 deviations obtained for each method, has a t distribution with mean zero and estimate of standard deviation. s(x - x) = √1+ 1/72 . s = 1.007. s , and the limit of t for the 5% probability, level with 71 degrees of freedom is 1.99, then the interval to be considered is given by x ± 1.99 x 1.007 s = x ± 2.00. s The intervals thus calculated are given on the table IX.

Improving TCP Performance on CSMA/CA Connections

In IP networks, most of packets, that have been dropped, are recovered after the expiration of retransmission timeouts. These can result in unnecessary retransmissions and needless reduction of congestion window. An inappropriate retransmission timeout has a huge impact on TCP performance. In this paper we have proved that CSMA/CA mechanism can cause TCP retransmissions due to CSMA/CA effects. For this we have observed three wireless connections that use CSMA/CA: with good link quality, poor link quality and in presence of cross traffic. The measurements have been performed using real devices. Through tracking of each transmitted packet it is possible to analyze the relation between one-way delay and packet loss probability and the cumulative distribution of distances between peaks of OWDs. The distribution of OWDs and the distances between peaks of OWDs are the most important parameters of tuning TCP retransmission timeout on CSMA/CA networks. A new perspective through investigating the dynamical relation between one-way delay and packet loss ratio depending on the link quality to enhance the TCP performance has been provided.

Breakage probability of repeated stressing of granules by configuring the stressing points

Magdeburg, Univ., Fak. für Verfahrens- und Systemtechnik, Diss., 2014

Doses and methods of distribution of potassium chloride on soybean crop (Glycine max (L.) Merrill) in a red latosol, affecting soil salinity, grain production and chemical composition of leaves

The present work deal t wi th an experiment under field conditions and a laboratory test of soil incubation the objectives were as follows: a. to study effects on soybean grain product ion and leaf composition of increasing doses of potassium chloride applied into the soil through two methods of distribution; b. to observe chemical modifications in the soils incubated with increasing doses of potassium chloride; and, c. to correlate field effects with chemical alterations observed in the incubation test, The field experiment was carried out in a Red Latosol (Haplustox) with soybean cultivar UFV - 1. Potassium chloride was distributed through two methods: banded (5 cm below and 5 cm aside of the seed line) and broadcasted and plowed-down. Doses used were: 0; 50; 100 and 200 kg/ha of K2O. Foliar samples were taken at flowering stage. Incubation test were made in plastic bags with 2 kg of air dried fine soil, taken from the arable layer of the field experiment, with the following doses of KC1 p,a. : 0; 50; 100; 200; 400; 800; 1,600; 3.200; 6,400 and 12,800 kg/ha of K(2)0. In the conditions observed during the present work, results allowed the following conclusions: A response by soybean grain production for doses of potassium chloride, applied in both ways, banded or broadcasted, was not observed. Leaf analysis did not show treatment influence over the leaf contents for N, P, K, Ca, Mg, and CI, Potassium chloride salinity effects in both methods of distribution for all the tested closes were not observed.

The cassava mite complex: III - new distribution records, mainly from Colombia and Africa. References to other plants

Uma lista de novas referências e ocorrências para ácaros tetraniquídeos da mandioca é apresentada.

The distribution of fishes found below a depth of 2000 meters.

v.36:no.2(1956)

Histoire naturelle des animaux sans vertèbres : présentant les caractères généraux et particuliers de ces animaux, leur distribution, leurs classes, leurs familles, leurs genres, et la citation des principales espèces qui s'y rapportent : précédée d'une introduction offrant la détermination des caractères essentiels de l'animal, sa distinction du végétal et des autres corps naturels, enfin, l'exposition des principes fondamentaux de la zoologie /

t.4 (1835)

Systematics and distribution of the Mexican and Central American rainfrogs of the Eleutherodactylus gollmeri group (Amphibia: Leptodactylidae) : a contribution in celebration of the distinguished scholarship of Robert F. Inger on the occasion of his sixty-fifth brithday / Jay M. Savage.

n.s. no.33(1987)

The blennioid fishes of Belize and Honduras, Central America, with comments on their systematics, ecology, and distribution (Blenniidae, Chaenopsidae, Labrisomidae, Tripterygiidae) / David W. Greenfield, Robert Karl Johnson.

n.s. no.8(1981)

Distribution and morphometrics of Natalus stramineus from South America (Chiroptera, Natalidae)

Morphometric and distributional data and some observations on the biology of Natalus stramineus Gray, 1838 collected in eastern Bolivia and in northern, northeastern, central, and southeastern Brazil are presented. All new records, combined with the records of the species from Paraguay and Mato Grosso, significantly change the known distribution of N. stramineus in South America. The specimens from northeastern Brazil (Rio Grande do Norte, Ceará, Bahia) are smaller than those found in the northern (Pará), eastern (Espírito Santo, São Paulo) and central regions of the country (Distrito Federal, Goiás, Mato Grosso do Sul). Natalus stramineus specimens from the three latter regions are about the same size, but are larger than those from Santa Cruz, Bolivia. Their size is intermediate between those of central samples and northeastern Brazil samples. The type locality of this species is discussed.

Sewage impact on the composition and distribution of Polychaeta associated to intertidal mussel beds of the Mar del Plata rocky shore, Argentina

The polychaete composition and distribution within mussel beds were studied in order to assess organic pollution due to domestic sewage in a rocky shore of Mar del Plata (Argentina) during 1997. Four stations and a control site were randomly sampled around the local effluent. Quantitative data on polychaetes, as well as sediment accumulated among mussels and its organic carbon content were measured. Polychaete distribution patterns are related to the organic matter gradient, being Capitella cf. capitata, Neanthes succinea (Frey & Leuckart, 1847) and Boccardia polybranchia (Haswell, 1885) the dominant indicator species close to the effluent. At medial distances, the cirratulids Caulleriella alata (Southern, 1914) and Cirratulus cirratus (Müller, 1776) are very important in abundance. The syllids Syllis prolixa Ehlers, 1901 and S. gracilis Grube, 1840 are distributed along the study area, but dominate at the medial stations and at the control site. The orbiniid Protoariciella uncinata Hartmann-Schröder, 1962 is subdominant at the control station.