E-mail spam is no more garbage but risk since it recently includes virus attachments and spyware agents which make the recipients' system ruined, therefore, there is an emerging need for spam detection. Many spam detection techniques based on machine learning techniques have been proposed. As the amount of spam has been increased tremendously using bulk mailing tools, spam detection techniques should counteract with it. To cope with this, parameters optimization and feature selection have been used to reduce processing overheads while guaranteeing high detection rates. However, previous approaches have not taken into account feature variable importance and optimal number of features. Moreover, to the best of our knowledge, there is no approach which uses both parameters optimization and feature selection together for spam detection. In this paper, we propose a spam detection model enabling both parameters optimization and optimal feature selection; we optimize two parameters of detection models using Random Forests (RF) so as to maximize the detection rates. We provide the variable importance of each feature so that it is easy to eliminate the irrelevant features. Furthermore, we decide an optimal number of selected features using two methods; (i) only one parameters optimization during overall feature selection and (ii) parameters optimization in every feature elimination phase. Finally, we evaluate our spam detection model with cost-sensitive measures to avoid misclassification of legitimate messages, since the cost of classifying a legitimate message as a spam far outweighs the cost of classifying a spam as a legitimate message. We perform experiments on Spambase dataset and show the feasibility of our approaches.

Recent innovations in additive manufacturing (AM) have proven its efficacy for not only the manufacturing industry but also the healthcare industry. Researchers from Cal Poly, San Luis Obispo, and California State University Long Beach are developing a model that will determine the optimal locations for additive manufacturing hubs that can effectively serve both the manufacturing and healthcare industries. This paper will focus on providing an overview of the healthcare industry's unique needs for an AM hub and summarise the specific inputs for the model. The methods used to gather information include extensive literature research on current practices of AM models in healthcare and an inclusive survey of healthcare practitioners. This includes findings on AM's use for surgical planning and training models, the workflow to generate them, sourcing methods, and the AM techniques and materials used. This paper seeks to utilise the information gathered through literature research and surveys to provide guidance for the initial development of an AM hub location model that locates optimal service locations.

The bulk solvent is a major component of biomacromolecular crystals that contributes significantly to the observed diffraction intensities. Accurate modelling of the bulk solvent has been recognized as important for many crystallographic calculations. Owing to its simplicity and modelling power, the flat (mask-based) bulk-solvent model is used by most modern crystallographic software packages to account for disordered solvent. In this model, the bulk-solvent contribution is defined by a binary mask and a scale (scattering) function. The mask is calculated on a regular grid using the atomic model coordinates and their chemical types. The grid step and two radii, solvent and shrinkage, are the three parameters that govern the mask calculation. They are highly correlated and their choice is a compromise between the computer time needed to calculate the mask and the accuracy of the mask. It is demonstrated here that this choice can be optimized using a unique value of 0.6 Å for the grid step irrespective of the data resolution, and the radii values adjusted correspondingly. The improved values were tested on a large sample of Protein Data Bank entries derived from X-ray diffraction data and are now used in the computational crystallography toolbox (CCTBX) and in Phenix as the default choice.

A symmetry guide for the secondary structural degrees of freedom and related physical properties generated by tilts of BX6 octahedra in perovskites is proposed.

In the family of perovskite materials, the tilts of BX6 octahedra are the most common type of structural distortion. Conventionally, the formation of low-symmetry perovskite phases with tilted octahedra is analyzed by considering only primary order parameters. However, octahedral tilting also gives rise to secondary order parameters which contribute to additional atomic displacements, ordering and lattice distortions. Our study highlights the significant impact of secondary order parameters on the structural formation and emergent physical properties of perovskites. Through group-theoretical and crystallographic analyses, we have identified all secondary order parameters within Glazer-type tilt systems and clarified their physical manifestations. We explore the fundamental symmetry relationships among various structural degrees of freedom in perovskites, including tilt-induced ferroelasticity, correlations between displacements and ordering of atoms occupying different positions, and the potential for rigid unit rotations and unconventional octahedral tilts. Particular emphasis is placed on the emergence of secondary order parameters and their coupling with primary order parameters, as well as their symmetry-based hierarchy, illustrated through a modified Bärnighausen tree. We applied our theoretical insights to elucidate phase transitions in well known perovskites such as CaTiO3 and RMnO3 (where R = La and lanthanide ions), thereby demonstrating the significant influence of secondary order parameters on crystal structure formation. Our results serve as a symmetry-based guide for the design, identification and structural characterization of perovskites with tilted octahedra, and for understanding tilt-induced physical properties.

Alignment of each optical element at a synchrotron beamline takes days, even weeks, for each experiment costing valuable beam time. Evolutionary algorithms (EAs), efficient heuristic search methods based on Darwinian evolution, can be utilized for multi-objective optimization problems in different application areas. In this study, the flux and spot size of a synchrotron beam are optimized for two different experimental setups including optical elements such as lenses and mirrors. Calculations were carried out with the X-ray Tracer beamline simulator using swarm intelligence (SI) algorithms and for comparison the same setups were optimized with EAs. The EAs and SI algorithms used in this study for two different experimental setups are the Genetic Algorithm (GA), Non-dominated Sorting Genetic Algorithm II (NSGA-II), Particle Swarm Optimization (PSO) and Artificial Bee Colony (ABC). While one of the algorithms optimizes the lens position, the other focuses on optimizing the focal distances of Kirkpatrick–Baez mirrors. First, mono-objective evolutionary algorithms were used and the spot size or flux values checked separately. After comparison of mono-objective algorithms, the multi-objective evolutionary algorithm NSGA-II was run for both objectives – minimum spot size and maximum flux. Every algorithm configuration was run several times for Monte Carlo simulations since these processes generate random solutions and the simulator also produces solutions that are stochastic. The results show that the PSO algorithm gives the best values over all setups.

Our study compares short-range order parameters refined from the diffuse scattering in single-crystal X-ray and single-crystal electron diffraction data. Nb0.84CoSb was chosen as a reference material. The correlations between neighbouring vacancies and the displacements of Sb and Co atoms were refined from the diffuse scattering using a Monte Carlo refinement in DISCUS. The difference between the Sb and Co displacements refined from the diffuse scattering and the Sb and Co displacements refined from the Bragg reflections in single-crystal X-ray diffraction data is 0.012 (7) Å for the refinement on diffuse scattering in single-crystal X-ray diffraction data and 0.03 (2) Å for the refinement on the diffuse scattering in single-crystal electron diffraction data. As electron diffraction requires much smaller crystals than X-ray diffraction, this opens up the possibility of refining short-range order parameters in many technologically relevant materials for which no crystals large enough for single-crystal X-ray diffraction are available.

For a power system to operate efficiently and securely, the importance of the correct and coordinated provision and control of reactive power cannot be overemphasised. It is necessary to examine reactive power requirements under both steady-state and dynamic conditions. Although... Read more

The post Parameters of generators, transformers, lines and cables for vars, voltage and loads control appeared first on EEP - Electrical Engineering Portal.

To be honest, transmission and distribution networks are full of problems. But that’s nothing new, and you already knew that. This technical article will shed some light on solving some pretty severe problems in transmission and distribution networks by using... Read more

The post Controlling power system parameters through reactive power (VAr) compensation appeared first on EEP - Electrical Engineering Portal.

Definitions, associated measurement methods and guidance targets of user-centric parameters for call handling in cellular mobile voice service

Signalling procedures of the probes to be used for remote testing of network parameters

Olha Prykhodko and Kostiantyn Ralchenko
Theor. Probability and Math. Statist. 111 (), 123-135.
Abstract, references and article information

Total scattering measurements enable understanding of the structural disorder in crystalline materials by Fourier transformation of the total structure factor, S(Q), where Q is the magnitude of the scattering vector. In this work, the direct calculation of total scattering from a crystalline structural model is proposed. To calculate the total scattering intensity, a suitable Q-broadening function for the diffraction profile is needed because the intensity and the width depend on the optical parameters of the diffraction apparatus, such as the X-ray energy resolution and divergence, and the intrinsic parameters. X-ray total scattering measurements for CeO2 powder were performed at beamline BL04B2 of the SPring-8 synchrotron radiation facility in Japan for comparison with the calculated S(Q) under various optical conditions. The evaluated Q-broadening function was comparable to the full width at half-maximum of the Bragg peaks in the experimental total scattering pattern. The proposed calculation method correctly accounts for parameters with Q dependence such as the atomic form factor and resolution function, enables estimation of the total scattering factor, and facilitates determination of the reduced pair distribution function for both crystalline and amorphous materials.

A calculation procedure for X-ray total scattering and the pair distribution function from a crystalline structural model is presented. It allows one to easily and precisely deal with diffraction-angle-dependent parameters such as the atomic form factor and the resolution of the optics.

In a previous blog post, Notifications from MATLAB, I showed how Amazon's Notification system (AWS SNS) can be used from MATLAB service can be used to easily send information between endpoints in a distributed system, be they applications or people.... read more >>

Lots of users have asked us about more customization and control over the sound of our audio algorithms in the past, so today, we have introduced some advanced algorithm parameters for our singletrack version in a private beta program!

• Leveler Presets are basically complete new leveling algorithms
• Maximum Loudness Range (LRA) Target to control the strength of our Leveler
• Maximum True Peak Level
• Better Hum and Noise Reduction Controls

UPDATE Nov. 2018:
We released a complete rework of the Adaptive Leveler parameters and the description here is not valid anymore!
Please see Auphonic Adaptive Leveler Customization (Beta Update)!

Please join our private beta program and let us know how you use these new features or if you need even more control!

Leveler Presets

Our Adaptive Leveler corrects level differences between speakers, between music and speech and will also apply dynamic range compression to achieve a balanced overall loudness. If you don't know about the Leveler yet, take a look at our Audio Examples.

Leveler presets are basically complete new leveling algorithms, which we have been working on in the past few months:
Our current Leveler tries to normalize all speakers to the same loudness. However, in some cases, you might want more or less loudness differences (dynamic range / loudness range) between the speakers and music segments, or more or less compression, etc.
For these use cases, we have developed additional Leveler Presets and the parameter Maximum Loudness Range.

Preset Medium:

This is our current leveling algorithm as demonstrated in the Audio Examples.

Preset Hard:

The hard preset reacts faster and applies more gain and compression compared to the medium preset. It is built for recordings with extreme loudness differences, for example very quiet questions from the audience in a lecture recording, extremely soft and loud voices within one audio track, etc.

Preset Soft:

This preset reacts slower, applies less gain and compression compared to the medium preset. Use it if you want to keep more loudness differences (dynamic narration), if you want your voices to sound "less compressed/processed", for dynamic music (concert/classical recordings), background music, etc.

Preset Softer:

Like soft, but softer :)

Preset Speech Medium, Music Soft:

Uses the medium preset in speech segments and the soft preset in music segments. It is built for music live recordings or dynamic music mixes, where you want to amplify all speakers but keep the loudness differences within and between music segments.

Preset Medium, No Compressor:

Like the medium preset, but only (mid-term) leveling and no (short-term) compression is applied. This preset is optimal if you just use a Maximum Loudness Range Target and want to avoid any additional compression as much as possible.

Maximum Loudness Range (LRA) Target

The loudness range (LRA) indicates the variation of loudness over the course of a program and is measured in LU (loudness units) - for more details see Loudness Measurement and Normalization or EBU Tech 3342.

The parameter Max Loudness Range controls how much leveling is applied:
volume changes of our Adaptive Leveler will be restricted so that the loudness range of the output file is below the selected value.
High loudness range values will result in very dynamic output files, low loudness range values in compressed output audio. If the LRA value of your input file is already below the maximum loudness range value, no leveling at all will be applied.

It is also important which Leveler Preset you select, for example, if you use the soft(er) preset, it won't be possible to achieve very low loudness range targets.

Also, the Max Loudness Range parameter is not such a precise target value as the Loudness Target. The LRA of your output file might be off a few LU, as it is not reasonable to reach the exact target value.

Use Cases: The Maximum LRA parameter allows you to control the strength of our leveling algorithms, in combination with the parameter Leveler Preset. This might be used for automatic mixdowns with different LRA values for different target platforms (very compressed ones like mobile devices or Alexa, very dynamic ones like home cinema, etc.).

Maximum True Peak Level

This parameter sets the maximum allowed true peak level of the processed output file, which is controlled by the True Peak Limiter after our Global Loudness Normalization algorithms.

If set to Auto (which is the current default), a reasonable value according to the selected loudness target is used: -1dBTP for 23 LUFS (EBU R128) and higher, -2dBTP for -24 LUFS (ATSC A/85) and lower loudness targets.

The maximum true peak level parameter is already available in our desktop program.

Better Hum and Noise Reduction Controls

Hum Base Frequency:

Set the hum base frequency to 50Hz or 60Hz (if you know it), or use Auto to automatically detect the hum base frequency in each speech region.

Hum Reduction Amount:

Maximum hum reduction amount in dB, higher values remove more noise.
In Auto mode, a classifier decides how much hum reduction is necessary in each speech region. Set it to a custom value (> 0), if you prefer more hum reduction or want to bypass our classifier. Use Disable Dehum to disable hum reduction and use our noise reduction algorithms only.

Behavior of noise and hum reduction parameter combinations:

Advanced Parameters Private Beta and Feedback

At the moment the advanced algorithm parameters are for beta users only. This is to allow us to get user feedback, so we can change the parameters to suit user needs.
Please let us know your case studies, if you need any other algorithm parameters or if you have any questions!

Here are some private beta invitation codes:

y6KCBI4yo0 ksIFEsmI1y BDZec2a21V i4XRGLlVm2 0UDxuS0vbu aaBxi35sKN aaiDSZUbmY bu8lPF80Ih eMsSl6Sf8K DaWpsUnyjo
2YM00m8zDW wh7K2pPmSa jCX7mMy2OJ ZGvvhzCpTF HI0lmGhjVO eXqVhN6QLU t4BH0tYcxY LMjQREVuOx emIogTCAth 0OTPNB7Coz
VIFY8STj2f eKzRSWzOyv 40cMMKKCMN oBruOxBkqS YGgPem6Ne7 BaaFG9I1xZ iSC0aNXoLn ZaS4TykKIa l32bTSBbAx xXWraxS40J
zGtwRJeAKy mVsx489P5k 6SZM5HjkxS QmzdFYOIpf 500AHHtEFA 7Kvk6JRU66 z7ATzwado6 4QEtpzeKzC c9qt9Z1YXx pGSrDzbEED
MP3JUTdnlf PDm2MOLJIG 3uDietVFSL 1i7jZX0Y9e zPkSgmAqqP 5OhcmHIZUP E0vNsPxZ4s FzTIyZIG2r 5EywA0M7r5 FMhpcFkVN5
oRLbRGcRmI 2LTh8GlN7h Cjw6Z3cveP fayCewjE55 GbkyX89Lxu 4LpGZGZGgc iQV7CXYwkH pGLyQPgaha e3lhKDRUMs Skrei1tKIa

If you have an invitation code, you can enter it here to activate the advanced audio algorithm parameters:
Auphonic Algorithm Parameters Private Beta Activation

A system (200) and a method (100) of operating a computing device to perform memoization are disclosed. The method includes determining whether a result of a function is stored in a cache and, if so, retrieving the result from the cache and, if not, calculating the result and storing it in the cache. The method (100) includes transforming (104) by the computing device at least one selected from the input parameters and the output parameters of the function, the transforming being based on an analysis of the function and its input arguments to establish whether or not there is a possible relationship reflecting redundancy among the input parameters and output parameters of the function. The transforming may include at least one of: use of symmetry, scaling, linear shift, interchanging of variables, inversion, polynomial and/or trigonometric transformations, spectral or logical transformations, fuzzy transformations, and systematic arrangement of parameters.

The disclosure provides a method for passing a parameter between processors. The method comprises the following steps: in a source program of a slave processor, directly introducing a static configuration parameter to be passed; obtaining a relative address of the static configuration parameter when converting the source program of the slave processor into a target program of the slave processor; and configuring directly, by a master processor, a parameter value of the static configuration parameter in the target program of the slave processor according to the obtained relative address of the static configuration parameter. The disclosure also provides a system for passing a parameter between processors. The system has no need to use external hardware such as a dual-port Random Access Memory (RAM) and a register, thus, the requirement of parameter transmission on the external hardware is reduced, and further the area and static power consumption of a chip are reduced. The disclosure reduces the cycle delay of the slave processor in accessing the dual-port RAM and the register, thereby effectively reducing the dynamic power consumption of the chip, improving the processing capability of the slave processor and enhancing the effective performance of the slave processor.

The present invention is based on the finding that parameters including: a first set of parameters of a representation of a first portion of an original signal and a second set of parameters of a representation of a second portion of the original signal can be efficiently encoded when the parameters are arranged in a first sequence of tuples and a second sequence of tuples. The first sequence of tuples includes tuples of parameters having two parameters from a single portion of the original signal and the second sequence of tuples includes tuples of parameters having one parameter from the first portion and one parameter from the second portion of the original signal. A bit estimator estimates the number of necessary bits to encode the first and the second sequence of tuples. Only the sequence of tuples, which results in the lower number of bits, is encoded.

A method of performance monitoring in a data processing environment is provided. The data processing environment includes multiple systems, each of which has resources. Each resource relates to a resource type, wherein at least one performance parameter is defined for each resource type. The method includes determining a value of the at least one performance parameter for at least one resource, aggregating performance parameter values and related resources of a resource type, creating for at least a part of the resources a next predefined aggregation level which includes all resources relating to the resource type and associating all performance parameter values to this aggregation level, and repeating the creating for at least a part of the resources a next predefined aggregation level until a predefined target aggregation level of the data processing environment has been reached.

A coiling parameterization tool includes a processor and a display for displaying values of lumen volume, packing and coiling parameters for filling a lumen in relation to a desired packing. The processor is configured to detect a change in one of the displayed values and, in response to the change, to automatically evaluate, change and display remaining values displayed on the display.

One or more temporal stimulation parameters of vagus nerve stimulation (VNS) are selected to substantially modulate one or more target physiological functions without substantially modulating one or more non-target physiological functions. In one embodiment, a stimulation duty cycle is selected such that VNS is delivered to the cervical vagus nerve trunk to modulate a cardiovascular function without causing laryngeal muscle contractions.

Methods, systems, and devices are described for communicating physical layer wireless parameters over an application programming interface. A wireless modem of a wireless device may measure at least one physical layer wireless parameter. The wireless modem may report the at least one physical layer wireless parameter to an application running on the wireless device over an application programming interface between the wireless modem and the application. A behavior of the application may be adapted to control wireless communications between the application and a network based on the at least one physical layer wireless parameter reported by the wireless modem. Other aspects, embodiments, and features are also claimed and described.

The present invention proposes a digital system and method of measuring (estimating) non-energy parameters of the signal (phase, frequency and frequency rate) received in additive mixture with Gaussian noise. The first embodiment of the measuring system consists of a PLL system tracking variable signal frequency, a block of NCO full phase computation (OFPC), a block of signal phase primary estimation (SPPE) and a first type adaptive filter filtering the signal from the output of SPPE. The second embodiment of the invention has no block SPPE, and NCO full phase is fed to the input of a second type adaptive filter. The present invention can be used in receivers of various navigation systems, such as GPS, GLONASS and GALILEO, which provide precise measurements of signal phase at different rates of frequency change, as well as systems using digital PLLs for speed measurements.

A technique for emulating virtual port control of airtime fairness for wireless stations using per station Enhanced Distributed Channel Access (EDCA) parameters. Specific parameters are received for each of a plurality of stations connected to the access point. An EDCA field of a beacon that stores a general EDCA parameter is set to an empty state. The beacon is broadcast to a plurality stations on the wireless communication network and within range of an access point. The beacon comprises a BSSID (Basic Service Set Identifier) for use by the plurality of stations to connect with the access point for access to the wireless communication network. The beacon also comprises an empty EDCA field. In response to broadcasting the empty EDCA parameter, receiving a direct inquiry from each of the plurality of stations for the general EDCA parameter. Each of the plurality of stations is responded to with a direct communication of a specific parameter corresponding to each station. A transmission is received from at least one of the stations complying with the specific parameter.

A. V. Ivanov and I. K. Matsak
Theor. Probability and Math. Statist. 99 (2020), 91-99.
Abstract, references and article information

We performed post-hoc analyses on the utility of pre-therapeutic and early interim ⁶⁸Ga-DOTA-Tyr3-octreotide (⁶⁸Ga-DOTATOC) positron emission tomography (PET) tumor uptake and volumetric parameters and a recently proposed biomarker, the inflammation-based index (IBI), for peptide receptor radionuclide therapy (PRRT) in neuroendocrine tumor (NET) patients treated with ⁹⁰Y-DOTATOC in the setting of a prospective phase II trial. Methods: Forty-three NET patients received up to four cycles of 1.85 GBq/m²/cycle ⁹⁰Y-DOTATOC with a maximal kidney biologic effective dose of 37 Gy. All patients underwent a ⁶⁸Ga-DOTATOC PET/computed tomography (CT) at baseline and seven weeks after the first PRRT cycle. ⁶⁸Ga-DOTATOC-avid tumor lesions were semi-automatically delineated using a customized standardized uptake value (SUV) threshold-based approach. PRRT response was assessed on CT using RECIST 1.1. Results: Median progression-free survival (PFS) and overall survival (OS) were 13.9 and 22.3 months, respectively. An SUVmean higher than 13.7 (75th percentile (P75)) was associated with better survival (hazard ratio (HR) 0.45; P = 0.024), whereas a ⁶⁸Ga-DOTATOC-avid tumor volume higher than 578 ml (P75) was associated with worse OS (HR 2.18; P = 0.037). Elevated baseline IBI was associated with worse OS (HR 3.90; P = 0.001). Multivariate analysis corroborated independent associations between OS and SUVmean (P = 0.016) and IBI (P = 0.015). No significant correlations with PFS were found. A composite score based on SUVmean and IBI allowed to further stratify patients in three categories with significantly different survival. On early interim PET, a decrease in SUVmean of more than 17% (P75) was associated with worse survival (HR 2.29; P = 0.024). Conclusion: Normal baseline IBI and high ⁶⁸Ga-DOTATOC tumor uptake predict better outcome in NET patients treated with ⁹⁰Y-DOTATOC. This can be used for treatment personalization. Interim ⁶⁸Ga-DOTATOC PET does not provide information for treatment personalization.

Eve Van Cauter
Mar 1, 1992; 41:368-377
Original Article

Khalid A. Jadoon
Oct 1, 2016; 39:1777-1786
Emerging Technologies and Therapeutics

Xiufang Liu, Dehui Wang.

Source: Brazilian Journal of Probability and Statistics, Volume 33, Number 3, 638--673.

Abstract:
This paper discusses a $p$th-order dependence-driven random coefficient integer-valued autoregressive time series model ($operatorname{DDRCINAR}(p)$). Stationarity and ergodicity properties are proved. Conditional least squares, weighted least squares and maximum quasi-likelihood are used to estimate the model parameters. Asymptotic properties of the estimators are presented. The performances of these estimators are investigated and compared via simulations. In certain regions of the parameter space, simulative analysis shows that maximum quasi-likelihood estimators perform better than the estimators of conditional least squares and weighted least squares in terms of the proportion of within-$Omega$ estimates. At last, the model is applied to two real data sets.

Caio L. N. Azevedo, Dalton F. Andrade

Source: Braz. J. Probab. Stat., Volume 24, Number 3, 415--433.

Abstract:
The nominal response model (NRM) was proposed by Bock [ Psychometrika 37 (1972) 29–51] in order to improve the latent trait (ability) estimation in multiple choice tests with nominal items. When the item parameters are known, expectation a posteriori or maximum a posteriori methods are commonly employed to estimate the latent traits, considering a standard symmetric normal distribution as the latent traits prior density. However, when this item set is presented to a new group of examinees, it is not only necessary to estimate their latent traits but also the population parameters of this group. This article has two main purposes: first, to develop a Monte Carlo Markov Chain algorithm to estimate both latent traits and population parameters concurrently. This algorithm comprises the Metropolis–Hastings within Gibbs sampling algorithm (MHWGS) proposed by Patz and Junker [ Journal of Educational and Behavioral Statistics 24 (1999b) 346–366]. Second, to compare, in the latent trait recovering, the performance of this method with three other methods: maximum likelihood, expectation a posteriori and maximum a posteriori. The comparisons were performed by varying the total number of items (NI), the number of categories and the values of the mean and the variance of the latent trait distribution. The results showed that MHWGS outperforms the other methods concerning the latent traits estimation as well as it recoveries properly the population parameters. Furthermore, we found that NI accounts for the highest percentage of the variability in the accuracy of latent trait estimation.

We study the problem of parameter estimation for a non-ergodic Gaussian Vasicek-type model defined as $dX_t=(mu+ heta X_t)dt+dG_t, tgeq0$ with unknown parameters $ heta>0$ and $muinR$, where $G$ is a Gaussian process. We provide least square-type estimators $widetilde{ heta}_T$ and $widetilde{mu}_T$ respectively for the drift parameters $ heta$ and $mu$ based on continuous-time observations ${X_t, tin[0,T]}$ as $T ightarrowinfty$.

Our aim is to derive some sufficient conditions on the driving Gaussian process $G$ in order to ensure that $widetilde{ heta}_T$ and $widetilde{mu}_T$ are strongly consistent, the limit distribution of $widetilde{ heta}_T$ is a Cauchy-type distribution and $widetilde{mu}_T$ is asymptotically normal. We apply our result to fractional Vasicek, subfractional Vasicek and bifractional Vasicek processes. In addition, this work extends the result of cite{EEO} studied in the case where $mu=0$.

Xi Chen, Jason D. Lee, Xin T. Tong, Yichen Zhang.

Source: The Annals of Statistics, Volume 48, Number 1, 251--273.

Abstract:
The stochastic gradient descent (SGD) algorithm has been widely used in statistical estimation for large-scale data due to its computational and memory efficiency. While most existing works focus on the convergence of the objective function or the error of the obtained solution, we investigate the problem of statistical inference of true model parameters based on SGD when the population loss function is strongly convex and satisfies certain smoothness conditions. Our main contributions are twofold. First, in the fixed dimension setup, we propose two consistent estimators of the asymptotic covariance of the average iterate from SGD: (1) a plug-in estimator, and (2) a batch-means estimator, which is computationally more efficient and only uses the iterates from SGD. Both proposed estimators allow us to construct asymptotically exact confidence intervals and hypothesis tests. Second, for high-dimensional linear regression, using a variant of the SGD algorithm, we construct a debiased estimator of each regression coefficient that is asymptotically normal. This gives a one-pass algorithm for computing both the sparse regression coefficients and confidence intervals, which is computationally attractive and applicable to online data.

  Download PDF When developing games and simulations, you may want your users to be able to influence assets that are active in a physics simulation. In this article, you learn how to develop a Unity...

hi all, 

          what wrong with the error "param_write.log does not exist" when i export parameters in allegro 16.6 pcb board.

          someone can provide suggestions, thanks.

best regards.

Hello Spectre Users, Simulating S-parameters in a time domain (transient, periodic steady state) simulator has been and continues to be a challenge for many analog and RF designers. I'm often asked: What is required in order to achieve accurate...(read more)

Hi All, If you were unable to attend IMS 2017 in June 2017, the IMS MicroApp “7 Habits of Highly Successful S-Parameters” is on our Cadence website. On Cadence Online Support , the in-depth AppNote is here: 20466646 . Best regards, Tawna...(read more)

Large-signal S-parameters (LSSPs) are an extension of small-signal S-parameters and are defined as the ratio of reflected (or transmitted) waves to incident waves. (read more)

BACKGROUND AND PURPOSE:

Detailed insight into the composition of thrombi retrieved from patients with ischemic stroke by mechanical thrombectomy might improve pathophysiologic understanding and therapy. Thus, this study searched for links between histologic thrombus composition and stroke subtypes and mechanical thrombectomy results.

Prof. Jason Pomeroy talks about the rise of the digital economy and its impact on the workplace.

Dalal Street expects ICICI Bank to report healthy earnings in Q4

EMC32-S: Transmission of Disturbance Signal Parameters to dAV Camera Systems

Eashwar Mime Co. presents the opposition between an individual's voice and collective silence using mime - an art form that has almost disappeared since the advent of the spoken word in films, writes Shoma Chatterji.

Equity parameters volatile in early trade, Nifty bank down by 2.7 pc

Equity parameters in green amid volatile trade, Bharti Infratel top gainer