Uniform Deviation Research Articles

The conscious experience of color constancy and neural responses to subliminal deviations - A behavioral and EEG/ERP oddball study.

Color constancy, a property of conscious color experience, maintains object color appearance across illuminant changes. We investigated the neural correlates of subliminal vs. conscious stimulus deviations of color constancy manipulations. Behavioral and Oddball EEG/ERP experiments were conducted (n=20). Psychophysical illuminant variation discrimination thresholds were first estimated, to establish individual perceptual awareness ranges, allowing for simulation of natural daylight spectral and spatial variations on colored surfaces, at different ambiguity levels. Behavioral results validated illuminant choice. ERPs showed a significant modulation of posterior P1 component specifically for the subliminal global uniform deviation condition, respecting color constancy. Neural correlates of conscious percepts were identified at posterior N2-P3 latencies, parietal (P3b) and frontal regions. We identified an early subliminal correlate of low-level illuminant change, which reflects automatic unconscious detection of global color constancy deviations. Its suppression under conscious perception is probably due to top-down suppression according to prediction error models.

On the velocity at wind turbine and propeller actuator discs

Abstract. The first version of the actuator disc momentum theory is more than 100 years old. The extension towards very low rotational speeds with high torque for discs with a constant circulation became available only recently. This theory gives the performance data like the power coefficient and average velocity at the disc. Potential flow calculations have added flow properties like the distribution of this velocity. The present paper addresses the comparison of actuator discs representing propellers and wind turbines, with emphasis on the velocity at the disc. At a low rotational speed, propeller discs have an expanding wake while still energy is put into the wake. The high angular momentum of the wake, due to the high torque, creates a pressure deficit which is supplemented by the pressure added by the disc thrust. This results in a positive energy balance while the wake axial velocity has lowered. In the propeller and wind turbine flow regime the velocity at the disc is 0 for a certain minimum but non-zero rotational speed. At the disc, the distribution of the axial velocity component is non-uniform in all actuator disc flows. However, the distribution of the velocity in the plane containing the axis, the meridian plane, is practically uniform (deviation <0.2 %) for wind turbine disc flows with tip speed ratio λ>5, almost uniform (deviation ≈2 %) for wind turbine disc flows with λ=1 and propeller flows with advance ratio J=π, and non-uniform (deviation 5 %) for the propeller disc flow with wake expansion at J=2π. These differences in uniformity are caused by the different strengths of the singularity in the wake boundary vorticity strength at its leading edge.

Diagnosis of Cataract using a Robust Algorithm for Telemedicine Applications

This project proposes and evaluates an algorithm to automatically detect cataract from colored images of adult human subjects. The methods currently available make use of DSLR (Digital Single Lens Reflex) cameras which are very expensive thereby, making the whole process expensive. The main objective of this project is to provide a robust and affordable alternative to the classic treatment method which adopts the above methods. In this project via an algorithm we aim to diagnose the presence of cataract from the true colour images of an eye. The algorithm proposed makes use of OpenCV for cataract screening based on textural features such as uniformity, intensity and standard deviation. These features are first computed and mapped using Data Mining techniques after consultation with an eye expert to define the basic threshold of screening system and later tested on real subjects in an eye clinic. Pre-processing includes conservative smoothing followed by image de-noising. The isotropic Gaussian filter is widely used as a low pass filter for image de-noising.Feature extraction is done after pre-processing to extract all the information for cataract detection from the eye’s pupil region. The extracted parameters were compared with the values obtained from an ophthalmologist to determine the presence of Cataract in the eye of the patient. Finally, a tele-ophthalmology model using our proposed system has been suggested, which confirms the telemedicine application of the proposed system.

Diagnosis of Cataract using a Robust Algorithm for Telemedicine Applications

This project proposes and evaluates an algorithm to automatically detect cataract from colored images of adult human subjects. The methods currently available make use of DSLR (Digital Single Lens Reflex) cameras which are very expensive thereby, making the whole process expensive. The main objective of this project is to provide a robust and affordable alternative to the classic treatment method which adopts the above methods. In this project via an algorithm we aim to diagnose the presence of cataract from the true colour images of an eye. The algorithm proposed makes use of OpenCV for cataract screening based on textural features such as uniformity, intensity and standard deviation. These features are first computed and mapped using Data Mining techniques after consultation with an eye expert to define the basic threshold of screening system and later tested on real subjects in an eye clinic. Pre-processing includes conservative smoothing followed by image de-noising. The isotropic Gaussian filter is widely used as a low pass filter for image de-noising.Feature extraction is done after pre-processing to extract all the information for cataract detection from the eye’s pupil region. The extracted parameters were compared with the values obtained from an ophthalmologist to determine the presence of Cataract in the eye of the patient. Finally, a tele-ophthalmology model using our proposed system has been suggested, which confirms the telemedicine application of the proposed system.

Standardization of process parameters for the production of bulky raw silk using cocoon entanglement method

Production of bulky raw silk is preferred for weaving sarees in Indian context. It was thought to increase the speed of movement of cocoons by incorporating suitable device so that entanglement in filaments will take place resulting in different structure of bulky silk yarn. CSTRI has developed a mechanism to rotate the inner vessel keeping the outer vessel constant; thus, the water would not be spilled during the rotation of the vessel in the reeling process. In order to standardize the process parameters viz., basin (rotation of vessel) speed, reel speed, and the number of cocoons reeled for the production of bulky raw silk by cocoon entanglement using Box and Behnken design of experiment. The studies conducted reveal that the average denier, size uniformity, and size deviation are significantly influenced at 1% level on the above process variables. Further, it was observed that the basin speed and reel speed should be in the ratio of 2:1. The basin speed of 150 rpm with reel speed of 75 rpm and 30 cocoons has imparted required bulkiness in the yarn and having characteristics suitable for production of bulky silk fabric which can be used for exclusive end uses.

Infrared navigation system for light dosimetry during pleural photodynamic therapy

Pleural photodynamic therapy (PDT) is performed intraoperatively for the treatment of microscopic disease in patients with malignant pleural mesothelioma. Accurate delivery of light dose is critical to PDT efficiency. As a standard of care, light fluence is delivered to the prescribed fluence using eight isotropic detectors in pre-determined discrete locations inside the pleural cavity that is filled with a dilute Intralipid solution. An optical infrared (IR) navigation system was used to monitor reflective passive markers on a modified and improved treatment delivery wand to track the position of the light source within the treatment cavity during light delivery. This information was used to calculate the light dose, incorporating a constant scattered light dose and using a dual correction method. Calculation methods were extensively compared for eight detector locations and seven patient case studies. The light fluence uniformity was also quantified by representing the unraveled three-dimensional geometry on a two-dimensional plane. Calculated light fluence at the end of treatment delivery was compared to measured values from isotropic detectors. Using a constant scattered dose for all detector locations along with a dual correction method, the difference between calculated and measured values for each detector was within 15%. Primary light dose alone does not fully account for the light delivered inside the cavity. This is useful in determining the light dose delivered to areas of the pleural cavity between detector locations, and can serve to improve treatment delivery with implementation in real-time in the surgical setting. We concluded that the standard deviation of light fluence uniformity for this method of pleural PDT is 10%.

Development and Application of a New Combination of Models to Improve the Uniformity of Ventilation and Exhaust in a 500 kA Potline

Three numerical models have been developed to investigate the thermal balance in a 500 kA aluminum reduction cell. The hooding efficiency, ventilation uniformity, and exhaust gas flowrate (EGF) uniformity of the cell were studied by using an upper cell thermoflow model and a dual-ductline flow model, and the effects of changing the EGF on the thermal balance were investigated using a slice thermoelectric model. The results of the models were compared with industrial measurements taken under similar conditions, revealing good agreement that demonstrates the validity of the use of numerical models to study the impacts of the EGF on the thermal balance. The cell showed a high hooding efficiency, good ventilation uniformity (deviation range − 4% to 5%), and more uniform thermal field when using the high-performance duct and dual-ductline system. The potline could exhibit good EGF uniformity (deviation range ± 5%) in running cells. Through these advantages, the problems of dust accumulation in the duct and gas leakage at the tapping end (TE) were solved effectively, and the EGF was decreased from 10,607 Nm3/h to 8308 Nm3/h without reducing the cell hooding efficiency. The results were transferred to industrial practice by upgrading the duct system of a 500 kA potline, achieving a total energy saving of 233 kWh/t-Al, of which about 80 kWh came from the gas treatment center and 153 kWh from the reduction cells.

A non-exponential extension of Sanov’s theorem via convex duality

AbstractThis work is devoted to a vast extension of Sanov’s theorem, in Laplace principle form, based on alternatives to the classical convex dual pair of relative entropy and cumulant generating functional. The abstract results give rise to a number of probabilistic limit theorems and asymptotics. For instance, widely applicable non-exponential large deviation upper bounds are derived for empirical distributions and averages of independent and identically distributed samples under minimal integrability assumptions, notably accommodating heavy-tailed distributions. Other interesting manifestations of the abstract results include new results on the rate of convergence of empirical measures in Wasserstein distance, uniform large deviation bounds, and variational problems involving optimal transport costs, as well as an application to error estimates for approximate solutions of stochastic optimization problems. The proofs build on the Dupuis–Ellis weak convergence approach to large deviations as well as the duality theory for convex risk measures.

Third Order Adjoint Sensitivity and Uncertainty Analysis of an OECD/NEA Reactor Physics Benchmark: III. Response Moments

The (180)3 third-order mixed sensitivities of the leakage response of a polyethylene-reflected plutonium (PERP) experimental benchmark with respect to the benchmark’s 180 microscopic total cross sections have been computed in accompanying works [1] [2]. This work quantifies the contributions of these (180)3 third-order mixed sensitivities to the PERP benchmark’s leakage response distribution moments (expected value, variance and skewness) and compares these contributions to those stemming from the corresponding first- and second-order sensitivities of the PERP benchmark’s leakage response with respect to the total cross sections. The numerical results obtained in this work reveal that the importance of the 3rd-order sensitivities can surpass the importance of the 1st- and 2nd-order sensitivities when the parameters’ uncertainties increase. In particular, for a uniform standard deviation of 10% of the microscopic total cross sections, the 3rd-order sensitivities contribute 80% to the response variance, whereas the contribution stemming from the 1st- and 2nd-order sensitivities amount only to 2% and 18%, respectively. Consequently, neglecting the 3rd-order sensitivities could cause a very large non-conservative error by under-reporting the response variance by a factor of 506%. The results obtained in this work also indicate that the effects of the 3rd-order sensitivities are to reduce the response’s skewness in parameter space, rendering the distribution of the leakage response more symmetric about its expected value. The results obtained in this work are the first such results ever published in reactor physics. Since correlations among the group-averaged microscopic total cross sections are not available, only the effects of typical standard deviations for these cross sections could be considered. Due to this lack of correlations among the cross sections, the effects of the mixed 3rd-order sensitivities could not be quantified exactly at this time. These effects could be quantified only when correlations among the group-averaged microscopic total cross sections would be obtained experimentally by the nuclear physics community.

Efficient secure surveillance on smart healthcare IoT system through cosine-transform encryption

The emerging technologies with IoT (Internet of Things) systems are elevated as a prototype and combination of the smart connectivity ecosystem. These ecosystems are appropriately connected in a smart healthcare system which are generating finest monitoring activities among the patients, well-organized diagnosis process, intensive support and care against the traditional healthcare operations. But facilitating these highly technological adaptations, the preserving personal information of the patients are on the risk with data leakage and privacy theft in the current revolution. Concerning secure protection and privacy theft of the patient’s information. We emphasized this paper on secure monitoring with the help of intelligently recorded summary’s keyframe extraction and applied two rounds lightweight cosine-transform encryption. This article includes firstly, a regimented process of keyframe extraction which is employed to retrieve meaningful frames of image through visual sensor with sending alert (quick notice) to authority. Secondly, employed two rounds of lightweight cosine-transform encryption operation of agreed (detected) keyframes to endure security and safety for the further any kinds of attacks from the adversary. The combined methodology corroborates highly usefulness with engendering appropriate results, little execution of encryption time (0.2277-0.2607), information entropy (7.9996), correlation coefficient (0.0010), robustness (NPCR 99.6383, UACI 33.3516), uniform histogram deviation (R 0.0359, G 0.0492, B 0.0582) and other well adopted secure ideology than any other keyframe or image encryption approaches. Furthermore, this incorporating method can effectively reduce vital communication cost, bandwidth issues, storage, data transmission cost and effective timely judicious analysis over the occurred activities and keep protection by using effective encryption methodology to remain attack free from any attacker or adversary, and provide confidentiality about patient’s privacy in the smart healthcare system.

Long-term Inter-protocol kV CBCT image quality assessment for a ring-gantry linac via automated QA approach

We develop a fully automated QA process to compare the image quality of all kV CBCT protocols on a Halcyon linac with ring gantry design, and evaluate image quality stability over a 10-month period. A total of 19 imaging scan and reconstruction protocols were characterized with measurement on a newly released QUART phantom. A set of image analysis algorithms were developed and integrated into an automated analysis suite to derive key image quality metrics, including HU value accuracy on density inserts, HU uniformity using the background plate, high contrast resolution with the modulation transfer function (MTF) from the edge profiles, low contrast resolution using the signal-to-noise ratio (SNR) and contrast-to-noise ratio (CNR), slice thickness with the air gap modules, and geometric accuracy with the diameter of the phantom. Image quality data over 10 months was tracked and analyzed to evaluate the stability of the Halcyon kV imaging system. The HU accuracy over all 19 protocols is within tolerance (±50HU). The maximum uniformity deviation is 12.2 HU. The SNR and CNR, depending on the protocol selected, range from 18.5–911.9 and 1.9–102.8, respectively. A much-improved SNR and CNR were observed for iterative reconstruction (iCBCT) modes and protocols designed for large subjects over low dose and fast scanning modes. The Head and Image Gently protocols have the greatest high contrast resolution with MTF10% over 1 lp/mm and MTF50% over 0.6 lp/mm. The iCBCT mode slightly improved the MTF10% and MTF50% compared to the Feldkamp-Davis-Kress approach. The slice thickness (maximum error of 0.31 mm) and geometry metrics (maximum error of 0.7 mm) are all within tolerance (±0.5 mm for slice thickness and ±1 mm for geometry metrics). The long-term study over 10-month showed no significant drift for all key image quality metrics, which indicated the kV CBCT image quality is stable over time.

Statistical learning based on Markovian data maximal deviation inequalities and learning rates

In statistical learning theory, numerous works established non-asymptotic bounds assessing the generalization capacity of empirical risk minimizers under a large variety of complexity assumptions for the class of decision rules over which optimization is performed, by means of sharp control of uniform deviation of i.i.d. averages from their expectation, while fully ignoring the possible dependence across training data in general. It is the purpose of this paper to show that similar results can be obtained when statistical learning is based on a data sequence drawn from a (Harris positive) Markov chain X, through the running example of estimation of minimum volume sets (MV-sets) related to X’s stationary distribution, an unsupervised statistical learning approach to anomaly/novelty detection. Based on novel maximal deviation inequalities we establish, using the regenerative method, learning rate bounds that depend not only on the complexity of the class of candidate sets but also on the ergodicity rate of the chain X, expressed in terms of tail conditions for the length of the regenerative cycles. In particular, this approach fully tailored to Markovian data permits to interpret the rate bound results obtained in frequentist terms, in contrast to alternative coupling techniques based on mixing conditions: the larger the expected number of cycles over a trajectory of finite length, the more accurate the MV-set estimates. Beyond the theoretical analysis, this phenomenon is supported by illustrative numerical experiments.

Uniform large deviation principles for Banach space valued stochastic evolution equations

We prove a large deviation principle (LDP) for a general class of Banach space valued stochastic differential equations (SDEs) that is uniform with respect to initial conditions in bounded subsets of the Banach space. A key step in the proof is showing that a uniform LDP over compact sets is implied by a uniform over compact sets Laplace principle. Because bounded subsets of infinite-dimensional Banach spaces are in general not relatively compact in the norm topology, we embed the Banach space into its double dual and utilize the weak- ⋆ \star compactness of closed bounded sets in the double dual space. We prove that a modified version of our SDE satisfies a uniform Laplace principle over weak- ⋆ \star compact sets and consequently a uniform over bounded sets LDP. We then transfer this result back to the original equation using a contraction principle. The main motivation for this uniform LDP is to generalize results of Freidlin and Wentzell concerning the behavior of finite-dimensional SDEs. Here we apply the uniform LDP to study the asymptotics of exit times from bounded sets of Banach space valued small noise SDE, including reaction diffusion equations with multiplicative noise and two-dimensional stochastic Navier–Stokes equations with multiplicative noise.

Effect of deposition pressures on uniformity, mechanical and tribological properties of thick DLC coatings inside of a long pipe prepared by PECVD method

Diamond-like carbon (DLC) coatings, as an excellent wear-resistant and low friction material, have been successfully applied as the surface protection and lubrication of various components. Recently, its application in the pipe fittings has gradually attracted the attention of the industry. In this paper, a plasma enhanced chemical vapor deposition (PECVD) technology was used to deposit a thick Si/Si-DLC/DLC multilayer composite coating inside a high aspect ratio pipe. The experimental results showed that the structures and properties of coatings strongly depended on deposition pressures. As the deposition pressure increased, the average thickness of the coating increased from 17 μm (50 mTorr) to 21.2 μm (110 mTorr) and its uniformity deviation continued to decreased until the pressure exceeded 100 mTorr, which reached the minimum value of 35.3%. When the deposition pressure rose, the coating hardness peaked at about 18.11 GPa (70 mTorr), and then it decreased to 14.86 GPa (110 mTorr). The friction coefficient and wear rate of the coating first decreased to 0.12 and 7.37 × 10−9 mm3/Nm (70 mTorr), respectively, and then slightly increased as the deposition pressure increased. In addition, the DLC coating we deposited also achieved a high adhesion strength of about 32 N (70 mTorr). In summary, the coating prepared at 70 mTorr had the best overall performance and was promised to be applied in pipeline protection industry.

Influence of the incorporation of a lead foil to intraoral digital receptors on the image quality and root fracture diagnosis.

To evaluate the quality of images obtained with the addition of a lead foil to intraoral digital receptors. Radiographic images of 34 single-rooted human teeth - 19 with vertical root fracture (VRF) and 15 of the control group - were obtained with and without the addition of a lead foil, using the VistaScan, Express, Digora Optime and Digora Toto systems. Images were evaluated by five observers regarding the diagnosis of VRF, using a 5-point scale. In a second moment, an observer preference analysis related to the presence of the lead foil was performed. Images of an acrylic phantom were also obtained with and without the addition of a lead foil, and the quantities of uniformity, grey value and standard deviation of grey values were obtained. There were no significant differences in the VRF diagnostic values, considering the presence of the lead foil. Regarding the image quality preference, the observers preferred images acquired with the lead foil for all systems tested, but with greater values for Digora Optime (61.33%) and Express (61.33%). The presence of the lead foil did influence the image uniformity in all systems tested ( p < 0.05). Moreover, the lead foil increased the mean of grey values for Digora Optime and Express images ( p < 0.05), however it did not influence the SD in any of the digital systems ( p > 0.05). The addition of a lead foil to intraoral digital receptors produces a positive effect in the image quality objectively detected by means of uniformity and subjective visual preference.

3D printed micro-chemical plant for biodiesel synthesis in millireactors

A micro-chemical plant implies the production increment of a determined product using micro/millireactor disposed in parallel. The flow distributor is responsible for the uniform distribution through these parallel microdevices. A mal-distribution, resulted from inadequate flow distributors designs, decrease the micro-chemical plant performance. Hence, the main goal of this paper was to apply 3D printing in manufacturing micro-chemical plant parts and to obtain data on flow uniformity and reaction yield by experimental tests for the increase of biodiesel production. The methodology consisted of design, printing and assembly of the micro-chemical plant and experimental tests for flow rate and chemical reaction. The nonuniformity flow coefficient (Ф) values were obtained for ethanol, sunflower oil and ethanol-sunflower oil mixture. The conical distributor without obstacle with height of 26 mm (CD26) and the conical distributor with obstacle and height of 52 mm (CDO52) presented excellent performance (Ф < 1%) for ethanol and sunflower oil flow, respectively, being used in the biodiesel synthesis scale-up. In the microplant, the pipes used for oil and ethanol followed length/diameter ratios of 39 and 113, respectively, which offered low pressure drop. The flow uniformity deviation obtained in the microplant was 4.2%, and its global yield was 42%, close to a single millireactor operation (50.4%). Thereby, the biodiesel was produced at 126.4 mL min−1. The developed microplant employed an efficient strategy for biodiesel scale-up. Another advantage of the methodology described here is the sharing possibility of files or objects over the internet. A user anywhere around the world can access the microplant developed here and start producing the desired chemical using a 3D Printer.

On Uniform Large Deviations Principle for Multi-valued SDEs via the Viscosity Solution Approach

This paper deals with the uniform large deviations for multivalued stochastic differential equations (MSDEs for short) by applying a stability result of the viscosity solutions of second order Hamilton-Jacobi-Belleman equations with multivalued operators. Moreover, the large deviation principle is uniform in time and in starting point.

Texture in the monitoring of regorafenib therapy in patients with colorectal liver metastases.

Background The morphological changes seen during treatment with regorafenib represent challenges when evaluating treatment response using RECIST. Computed tomography texture analysis (CTTA) has potential as a non-invasive functional imaging biomarker during treatment with anti-angiogenetic therapies. Purpose To explore changes in three-dimensional tumor CTTA in colorectal liver metastases (CRLM) in a cohort of patients with metastatic colorectal cancer during treatment with regorafenib. Material and Methods Twenty-seven patients with CRLM were treated with regorafenib and evaluated using CTTA. Texture analysis was applied in the standard contrast-enhanced CT performed in the portal-venous phase (PVP-CT) and in two selected scan series derived from a dynamic contrast-enhanced CT (DCE-CT). A total of 269 scan series were analyzed. Results In the unfiltered dataset of the PVP-CT, all texture parameters, except for kurtosis, changed significantly during treatment. In the filtered PVP-CT dataset, the CTTA parameters entropy, uniformity, and standard deviation were markedly associated with overall survival (OS) at spatial scaling factors (SSF) of 1.0– 2.0, but did not change significantly during treatment. Skewness increased significantly during treatment and was evaluated at SSF ≥1.0. In general, the same trends in texture parameter changes were seen when analyzing DCE-CT datasets. However, these changes did not reach the same level of significance. Conclusions In this exploratory study, we demonstrated substantial changes in the texture parameters during treatment with regorafenib, most evident in the unfiltered dataset of the PVP-CT. Some texture parameters showed prognostic association with OS. Texture may potentially help evaluate the treatment response in patients treated with regorafenib.

Equivalences and counterexamples between several definitions of the uniform large deviations principle

This paper explores the equivalences between four definitions of uniform large deviations principles and uniform Laplace principles found in the literature. Counterexamples are presented to illustrate the differences between these definitions and specific conditions are described under which these definitions are equivalent to each other. A fifth definition called the equicontinuous uniform Laplace principle (EULP) is proposed and proven to be equivalent to Freidlin and Wentzell’s definition of a uniform large deviations principle. Sufficient conditions that imply a measurable function of infinite dimensional Wiener process satisfies an EULP using the variational methods of Budhiraja, Dupuis and Maroulas are presented. This theory is applied to prove that a family of Hilbert space valued stochastic equations exposed to multiplicative noise satisfy a uniform large deviations principle that is uniform over all initial conditions in bounded subsets of the Hilbert space, and under stronger assumptions is uniform over initial conditions in unbounded subsets too. This is an improvement over previous weak convergence methods which can only prove uniformity over compact sets.

Opportunities for Process Control and Quality Assurance Using Online NIR Analysis to a Continuous Wet Granulation Tableting Line

This paper investigates the application of online near-infrared measurements as a means to measure blend uniformity in a continuous tableting line. Underlying all the monitoring and control methods is the ability to measure key tablet properties online at a rate suitable for control purposes. The use of NIR to determine any deviations in blend uniformity is demonstrated by interpreting the relevant spectral signature allowing quantitative information to be acquired for process monitoring and quality assurance. In addition to demonstrating the functionality of the NIR probe, the practical issues arising in the application are discussed. The composition of the blend was measured using an NIR probe over a range of concentrations and the results were calculated comparing sub unit dose scale of scrutiny of small populations. This was compared with predicted product quality for whole tablets over the whole production period. This technique has demonstrated how data collected online can be used to successfully predict the quality of the whole production run for the purposes of real-time product quality assurance.