نتایج جستجو برای: k frame

تعداد نتایج: 474336  

پایان نامه :وزارت علوم، تحقیقات و فناوری - دانشگاه صنعتی شریف 1369

مدلهای مختلفی برای شبیه سازی برجهای تقطیر در مراجع وجود دارند. این مدلها را می توان به دو دسته مهم تقسیم کرد : دسته اول براساس حل همزمان کلیه معادلات مدل قرار دارد. دسته دوم براساس دسته بندی معادلات مدل و حل جداگانه هر دسته از معادلات برای بدست آوردن متغیرهای خاص در چند حلقه تکرار قرار دارد. بررسیهای پژوهشگران نشان داده است که مشخصات همگرایی روشهای دسته دوم از یک مساله به مساله دیگر تغییر می کن...

2006
M. G. Vincter

ν = q · P M = E − E′ is the lepton’s energy loss in the nucleon rest frame (in earlier literature sometimes ν = q · P ). Here, E and E′ are the initial and final lepton energies in the nucleon rest frame. Q2 = −q2 = 2(EE′−−→k · −→k ′)−m2 −m2 ′ where m (m ′) is the initial (final) lepton mass. If EE′ sin2(θ/2) m2 , m2 ′ , then ≈ 4EE′ sin2(θ/2), where θ is the lepton’s scattering angle with respe...

2000
Marcus Kracht Oliver Kutz

We introduce a new semantics for modal predicate logic, with respect to which a rich class of first-order modal logics is complete, namely all normal first-order modal logics that are extensions of free quantified K. This logic is defined by combining positive free logic with equality PFL . = and the propositional modal logic K. We then uniformly construct—for each modal predicate logic L—a can...

2010
M. G. Vincter

ν = q · P M = E − E′ is the lepton’s energy loss in the nucleon rest frame (in earlier literature sometimes ν = q · P ). Here, E and E′ are the initial and final lepton energies in the nucleon rest frame. Q2 = −q2 = 2(EE′−−→k · −→k ′)−m2 −m2 ′ where m (m ′) is the initial (final) lepton mass. If EE′ sin2(θ/2) m2 , m2 ′ , then ≈ 4EE′ sin2(θ/2), where θ is the lepton’s scattering angle with respe...

2009
Shannon Bishop

This paper uses frame techniques to characterize the Schatten class properties of integral operators. The main result shows that if the coefficients {〈k,Φm,n〉} of certain frame expansions of the kernel k of an integral operator are in l, then the operator is Schatten p-class. As a corollary, we conclude that if the kernel or Kohn-Nirenberg symbol of a pseudodifferential operator lies in a parti...

Journal: :International Association of Geodesy symposia 2023

Abstract The third realization of the International Celestial Reference Frame (ICRF3) was adopted in August 2018 and includes positions extragalactic objects at three frequencies: 8.4 GHz, 24 32 GHz. In this paper, we present celestial reference frames estimated from Very Long Baseline Interferometry measurements K-band (24 GHz) including data until June 2022. set starts May 2002 currently cons...

Journal: :Computer Communications 2006
Dmitri Moltchanov Yevgeni Koucheryavy Jarmo Harju

In this paper we firstly propose simple and computationally efficient wireless channel modeling algorithm that explicitly takes into account firstand second-order statistics of frame error observations. For this purpose we use discrete-time Markov modulated processes with at most single event (error) at any time slot. We then adopt the special solution of the inverse eigenvalue problem initiall...

2011
Saharon Shelah

We deal with beginning stability theory for “reasonable” non-elementary classes without any remnants of compactness like dealing with models above Hanf number or by the class being definable by Lω1,ω. We introduce and investigate good λ-frame, show that they can be found under reasonable assumptions and prove we can advance from λ to λ+ when non-structure fail. That is, assume 2 +n < 2 +n+1 for...

2016
L. Thiele

1. A simple network consisting of two nodes, X and Z is shown in Fig 1. The nodes are separated by a distance of L = 800 m, and each node has a single frame of F = 1500 bits (including all headers and preambles) to send to each other. Both nodes attempt to transmit at time t = 0. In case that a node detects a collision, the node executes the exponential back-off algorithm. In the exponential ba...

2011
Teodor Lucian Grigorie Ruxandra Mihaela Botez

Nomenclature A = n×n matrix with elements depending by) , 1 (2 n i i   variances A 1 = (n-1)×(n-1) matrix with elements depending by) , 1 (2 n i i   variances a = output acceleration (perturbed signal) a c = cross-axis acceleration a i = input acceleration B = n×1 matrix with all elements equal to 1 B 1 = (n-1)×1 matrix with all elements equal to 1 B = bias b i = sensors measurement biases)...

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