Fitting Approach Research Articles

Differentiating Benign and Malignant Breast Lesions in Diffusion Kurtosis MRI: Does the Averaging Procedure Matter?

Diffusion kurtosis imaging (DKI) is used to differentiate between benign and malignant breast lesions. DKI fits are performed either on voxel-by-voxel basis or using volume-averaged signal. Investigate and compare DKI parameters' diagnostic performance using voxel-by-voxel and volume-averaged signal fit approach. Retrospective. A total of 104 patients, aged 24.1-86.4 years. A 3 T Spin-echo planar diffusion-weighted sequence with b-values: 50 s/mm2 , 750 s/mm2 , and 1500 s/mm2 . Dynamic contrast enhanced (DCE) sequence. Lesions were manually segmented by M.P. under supervision of S.O. (2 and 5 years of experience in breast MRI). DKI fits were performed on voxel-by-voxel basis and with volume-averaged signal. Diagnostic performance of DKI parameters (kurtosis corrected diffusion coefficient) and kurtosis was compared between both approaches. Receiver operating characteristics analysis and area under the curve (AUC) values were computed. Wilcoxon rank sum and Students t-test tested DKI parameters for significant (P <0.05) difference between benign and malignant lesions. DeLong test was used to test the DKI parameter performance for significant fit approach dependency. Correlation between parameters of the two approaches was determined by Pearson correlation coefficient. DKI parameters were significantly different between benign and malignant lesions for both fit approaches. Median benign vs. malignant values for voxel-by-voxel and volume-averaged approach were 2.00 vs. 1.28 ( in μm2 /msec), 2.03 vs. 1.26 ( in μm2 /msec), 0.54 vs. 0.90 ( ), 0.55 vs. 0.99 ( ). AUC for voxel-by-voxel and volume-averaged fit were 0.9494 and 0.9508 ( ); 0.9175 and 0.9298 ( ). For both, AUC did not differ significantly (P=0.20). Correlation of values between the two approaches was very high (r=0.99 for and r=0.97 for ). Voxel-by-voxel and volume-averaged signal fit approach are equally well suited for differentiating between benign and malignant breast lesions in DKI. 3 TECHNICAL EFFICACY: Stage 3.

Computational investigation of fitting for calculation of signal dynamics from hyperpolarized xenon-129 Gas MRI

Aim: Computational fitting methods were investigated to determine the most accurate fitting approach for the calculation of dynamic hyperpolarized MRI parameters.&#x0D; Materials and Methods: The signal decay of a time-series Hyperpolarized xenon gas MRI phantom was fitted to Bloch equations using three methods varying the fitting parameters for calculation of flip angle, α, and longitudinal relaxation time, T1. The first fitting method used an initial calculation of α before the fitting process. The second and third techniques used direct fitting of signal decay equations with and without upper-lower boundaries for calculation of α, and T1. Wilcoxon signed-rank test was used to investigate the statistical significance of the calculated parameters.&#x0D; Results: The first approach was the most accurate fitting technique that allowed direct calculation of α=8.65° in agreement to the third approach α=8.73±0.78°, 8.75±0.12°, 8.67±0.05°. Additionally, the standard deviation of the calculated T1 was lower than 1% (T1=103.2±0.04s) which was significantly more accurate than the second method (T1=90±30.2s and 135.7±10.3s) and the third method (T1=101.4±5.1s and 113.5±16.1s).&#x0D; Conclusion: The first technique provides repeatable and reliable calculation of signal decay parameters including α and T1 from the dynamic hyperpolarized gas MR images and more accurate than direct fitting methods.

You can try without visiting: a comprehensive survey on virtually try-on outfits.

Since the last years and until now, technology has made fast progress for many industries, in particularly, garment industry which aims to follow consumer desires and demands. One of these demands is to fit clothes before purchasing them on-line. Therefore, many research works have been focused on how to develop an intelligent apparel industry to ensure the online shopping experience. Image-based virtual try-on is among the most potential approach of virtual fitting that tries on target clothes into customer’s image, therefore, it has received considerable research efforts in the recent years. However, there are several challenges involved in development of virtual try-on that make it difficult to achieve naturally looking virtual outfit such as shape, pose, occlusion, illumination cloth texture, logo and text etc. The aim of this study is to provide a comprehensive and structured overview of extensive research on the advancement of virtual try-on. This review first introduces virtual try-on and its challenges followed by its demand in fashion industry. We summarize state-of-the-art image based virtual try-on for both fashion detection and fashion synthesis as well as their respective advantages, drawbacks, and guidelines for selection of specific try-on model followed by its recent development and successful application. Finally, we conclude the paper with promising directions for future research.

Damage investigations of the rebar under the coupling effect of fatigue and stray electric field induced corrosion

The damage mechanism of RC infrastructures due to the coupling effect of corrosion-fatigue has not yet been fully revealed. This paper devoted to investigating the damage characteristics of rebars under the coupling effect of stray electric field induced corrosion and axial force-controlled fatigue. Firstly, the detail of simulated concrete pore solution species was determined by thermodynamic calculations. Subsequently, the interfacial reaction kinetics was extracted via the electrochemical methods and fitting approaches. Ultimately, we exhibited the damage deformation process and the macro-morphology of fracture surfaces of rebars. In addition, an ia-rmax-Nf projection surface for evaluating the corrosion-fatigue life of rebars was proposed.

Towards single-trial classification of invasively recorded auditory evoked potentials in cochlear implant users

Objective. One promising approach towards further improving cochlear implants (CI) is to use brain signals controlling the device in order to close the auditory loop. Initial electroencephalography (EEG) studies have already shown promising results. However, they are based on noninvasive measurements, whereas implanted electrodes are expected to be more convenient in terms of everyday-life usability. If additional measurement electrodes were implanted during CI surgery, then invasive recordings should be possible. Furthermore, implantation will provide better signal quality, higher robustness to artefacts, and thus enhanced classification accuracy. Approach. In an initial project, three additional epidural electrodes were temporarily implanted during the surgical procedure. After surgery, different auditory evoked potentials (AEPs) were recorded both invasively (epidural) and using surface electrodes, with invasively recorded signals demonstrated as being markedly superior. In this present analysis, cortical evoked response audiometry (CERA) signals recorded in seven patients were used for single-trial classification of sounds with different intensities. For classification purposes, we used shrinkage-regularized linear discriminant analysis (sLDA). Clinical speech perception scores were also investigated. Main results. Analysis of CERA data from different subjects showed single-trial classification accuracies of up to 99.2% for perceived vs. non-perceived sounds. Accuracies of up to 89.1% were achieved in classification of sounds perceived at different intensities. Highest classification accuracies were achieved by means of epidural recordings. Required loudness differences seemed to correspond to speech perception in noise. Significance. The proposed epidural recording approach showed good classification accuracy into sound perceived and not perceived when the best-performing electrodes were selected. Classifying different levels of sound stimulation accurately proved more challenging. At present, the methods explored in this study would not be sufficiently reliable to allow automated closed-loop control of CI parameters. However, our findings are an important initial contribution towards improving applicability of closed auditory loops and for next-generation automatic fitting approaches.

Joint Source-Channel Decoding of Polar Codes for HEVC-Based Video Streaming

Ultra High-Definition (UHD) and Virtual Reality (VR) video streaming over 5G networks are emerging, in which High-Efficiency Video Coding (HEVC) is used as source coding to compress videos more efficiently and polar code is used as channel coding to transmit bitstream reliably over an error-prone channel. In this article, a novel Joint Source-Channel Decoding (JSCD) of polar codes for HEVC-based video streaming is presented to improve the streaming reliability and visual quality. Firstly, a Kernel Density Estimation (KDE) fitting approach is proposed to estimate the positions of error channel decoded bits. Secondly, a modified polar decoder called R-SCFlip is designed to improve the channel decoding accuracy. Finally, to combine the KDE estimator and the R-SCFlip decoder together, the JSCD scheme is implemented in an iterative process. Extensive experimental results reveal that, compared to the conventional methods without JSCD, the error data-frame correction ratios are increased. Averagely, 1.07% and 1.11% Frame Error Ratio (FER) improvements have been achieved for Additive White Gaussian Noise (AWGN) and Rayleigh fading channels, respectively. Meanwhile, the qualities of the recovered videos are significantly improved. For the 2D videos, the average Peak Signal-to-Noise Ratio (PSNR) and Structural SIMilarity (SSIM) gains reach 14% and 34%, respectively. For the 360֯ videos, the average improvements in terms of Weighted-to-Spherically-uniform PSNR (WS-PSNR) and Voronoi-based Video Multimethod Assessment Fusion (VI-VMAF) reach 21% and 7%, respectively.

Internal and external collaboration and supply chain performance: a fit approach

ABSTRACT This study explores the interactional effects and fit of internal and external collaboration on supply chain performance based on the fit theory. Data collected from 205 firms located in China was used to test the hypotheses via partial least squares structural equation modelling, polynomial regression and response surface methodology. The results demonstrate that there is an interactive effect, i.e. fit between internal collaboration and external collaboration on supply chain performance – a phenomenon not previously well understood. The results indicate that not all firms implementing internal collaboration and external collaboration can attain the desired goals. Only when the strength and balance of the two are similar, and at a moderate to upper level, can the supply chain performance be achieved the best; and once a certain threshold value of internal collaboration and external collaboration is achieved, further enhancement in internal and external collaboration will cause the decline of supply chain performance. Our study emphasises the importance of balancing internal constraints and external requirements across the whole supply chain, and provides insights into supply chain collaboration by suggesting that internal collaboration and external collaboration must be fit in the pursuit of supply chain performance.

On the anhysteretic magnetization of soft magnetic materials

Electrical steels are still the materials of choice for large-scale transformers and most electric motors. Yet, they may present a nonhomogeneous magnetic nature which prevents describing accurately their anhysteretic magnetization with the Langevin-Weiss model. Although interpolation and extrapolation methods may be used to model any anhysteretic curve, a simple and physically-based model would be of great value for fundamental and applied research. Inspired in the law of partial volumes for gas mixtures, we proposed a law of partial magnetizations for magnetic mixtures. In a two-component system, the model leads to the double Langevin-Weiss function. We also introduced a graphical method and a fitting approach to analyze and model anhysteretic magnetization curves. A semi-log magnetization derivative plot is central to this end. We validated our strategy through well-motivated examples using published data on soft magnets. The single Langevin-Weiss function provided an accurate description of the magnetization of isotropic and anisotropic magnetically homogeneous materials: a soft ferrite and a nanocrystalline alloy, respectively. For modelling a magnetization transverse to the material’s preferred direction, the key is to allow a negative molecular field constant. The double Langevin-Weiss function was suitable for less homogeneous materials, such as a grain-oriented electrical steel magnetized along the rolling direction and a non-oriented electrical steel. Moreover, a highly-grain-oriented electrical steel magnetized transverse to the rolling direction, which exhibits a constricted hysteresis loop, could be modeled in excellent agreement with data. The key for the latter, has been to allow an antiparallel arrangement of the mean magnetization of both components.

An X-ray photoelectron spectroscopy study of ionic liquids based on a bridged dicationic moiety

A series of imidazolium and pyridinium-based bridged dicationic ionic liquids have been analysed using X-ray photoelectron spectroscopy. The different electronic environments of the dications have been investigated and a robust fitting model for the carbon C1s region has also been developed. The relative positions of different C1s components and N1s of dications have been determined and their complex C1s photoemission spectra produced from both aromatic and aliphatic carbon states giving photoemission peaks in the binding energy range of 289.0–283.9 eV. A contemporary fitting approach has been applied to a different set of environments which allowing comparison of the binding energies of cationic components of imidazolium and pyridinium-based dicationic ionic liquids. The experimental stoichiometry of all the carbons and nitrogens have also been calculated from XP spectra of the dicationic ionic liquids.

Acid–base strength and acido(fluoro)chromism of three push–pull derivatives of 2,6-distyrylpyridine

The acidochromism and acid–base properties of 2,6-distyrylpyridine (2,6-DStP) derivatives bearing on the sides push/pull substituents (namely two dimethylamino, one nitro, and one methoxy and two nitro groups in the case of 2,6-bis[(E)-2-(4-dimetylaminophenyl)ethenyl]pyridine, 2-[(E)-2-(4-nitrophenyl)ethenyl],6-[(E)-2′-(4′-methoxyphenyl)ethenyl]pyridine and 2,6-bis[(E)-2-(4-nitrophenyl)ethenyl]pyridine, respectively) were investigated by stationary and time-resolved spectroscopies. The sensitivity of the absorption and emission spectrum to the medium acidity was found to enhance in the dimethylamino-derivative relative to the unsubstituted 2,6-DStP, also because of the second protonation by the N(CH3)2 group. Spectrophotometric titrations, also processed by a global fitting approach, gave pKa values, for the protonation of the central pyridine, higher in the derivatives with electron-donor unities and lower in compounds bearing electron-acceptor groups. A fluorometric titration was performed in the case of the dimethylamino-derivative thanks to non-negligible emission efficiencies for both neutral and protonated species, unveiling an attractive naked-eye acido(fluoro)chromism from green to yellow upon pyridine protonation, and then to purple with the second protonation involving the lateral N(CH3)2 substituent. Due to the extremely short excited-state lifetimes, as resulted from femtosecond transient absorption experiments, the pKa values for the excited state (pKa*) were estimated through the Förster cycle, revealing that the monoprotonated species of the dimethylamino-derivative would become upon excitation the only stable form in a wide range of pH.Graphical abstract

Correction and Fitting Civil Aviation Flight Data EGT Based on RPM: Polynomial Least Squares Analysis

There are different missing flight data due to various reasons in the process of acquisition and storage, especially in general aviation, which cause inconvenience for flight data analysis. Effectively explaining the relationship between flight data parameters and selecting a simple and effective method for fitting and correcting flight data suitable for engineering applications are the main points of the paper. Herein, a convenient and applicable approach of missing data correction and fitting based on the least squares polynomial method is introduced in this work. Firstly, the polynomial fitting model based on the least squares method is used to establish multi-order polynomial by existing flight data since the order of the least squares polynomial has a direct impact on the fitting effect. The order is too high or too small, over-fitting or deviation will occur, resulting in improper data. Therefore, the optimization and selection of the model order are significant for flight data correction and fitting. Because the flight data of the aircraft engine exhaust gas temperature (EGT) are often lost because of the immature detection technology, a series of the multi-order polynomial are established by the relationship of aircraft engine exhaust gas temperature and Revolutions Per Minute (RPM). Case study results confirm the optimal model order is four for the fitting and correction of aircraft engine exhaust temperature, and the least squares polynomial method is applicable and effective for EGT flight data correction and fitting based on RPM data.

Accurate Matching of Invariant Features Derived from Irregular Curves

High-quality feature matching is a critical prerequisite in a wide range of applications. Most contemporary methods concentrate on detecting keypoints or line features for matching, which have achieved adequate results. However, in some low-texture environments where these features are both lacking, previously used approaches may result in an insufficient number of matches. Besides, in repeated-texture environments, feature matching is also a challenging task. As a matter of fact, there exist numerous irregular curves that can be detected in all kinds of images, including low-texture and repeated-texture scenes, which inspires us to move a step further and dig into the research of curves. In this paper, we propose an accurate method to match invariant features from irregular curves. Our method consists of two stages, the first of which is to match the curves as accurately as possible by an elaborate three-step matching strategy. The second is to extract the matching features with the presented self-adaptive curve fitting approach. Experiments have shown that the matching performances of our features in ordinary scenes are comparable to previous keypoints. Particularly, our features can outperform the keypoints in low-texture and repeated-texture scenes.

A new experimental and theoretical approach for viscosity Iranian heavy crude oils based on tuning friction theory and friction volume theory parameters

In this research work, Friction Theory and Free Volume Theory are applied to live oil characterized based on SARA TEST for viscosity modeling and make a new model in combination with two equation of state (PR and PC-SAFT). Parameters for pseudo-components are obtained by tuning the viscosity at atmospheric pressure and temperatures of 10, 20, and 40 ℃. A new fitting approach is suggested where the number of fitting parameters is 17 and 12 for FT and FVT model, respectively. These parameters are tuned using the Genetic Algorithm and Particle Swarm Optimization and make eight new models. The results show that PC-SAFT provides viscosity predictions for all models with less deviation from experimental viscosity. The FT and FVT models have less error for oils with API > 40 and API < 40, respectively. The PC-SAFT + PSO improves the accuracy in viscosity modeling for both FT and FVT models. PSO can play a significant role even more than PC-SAFT.

Quality of hire: expanding the multi-level fit employee selection using machine learning

PurposeOrganizational psychologists and human resource management (HRM) practitioners often have to select the “right fit” candidate by manually scouting data from various sources including job portals and social media. Given the constant pressure to lower the recruitment costs and the time taken to extend an offer to the right talent, the HR function has to inevitably adopt data analytics and machine learning for employee selection. This paper aims to propose the “Quality of Hire” concept for employee selection using the person-environment (P-E) fit theory and machine learning.Design/methodology/approachThe authors demonstrate the aforementioned concept using a clustering algorithm, namely, partition around mediod (PAM). Based on a curated data set published by the IBM, the authors examine the dimensions of different P-E fits and determine how these dimensions can lead to selection of the “right fit” candidate by evaluating the outcome of PAM.FindingsThe authors propose a multi-level fit model rooted in the P-E theory, which can improve the quality of hire for an organization.Research limitations/implicationsTheoretically, the authors contribute in the domain of quality of hire using a multi-level fit approach based on the P-E theory. Methodologically, the authors contribute in expanding the HR analytics landscape by implementing PAM algorithm in employee selection.Originality/valueThe proposed work is expected to present a useful case on the application of machine learning for practitioners in organizational psychology, HRM and data science.

New Frontiers in Computer-Assisted Career Guidance Systems (CACGS): Implications From Career Construction Theory.

This article addresses the use of computer-assisted career guidance systems (CACGS) in career interventions. Major CACGS developed in the past decades were based on the trait-factor or person-environment fit approaches in their conceptualization and design. The strengths and limitations of these CACGS in addressing the career development needs of individuals are discussed. The Career Construction Theory (CCT) is a promising paradigm to guide the development of new generations of CACGS. The narrative tradition, career adaptability model, and life-design interventions of CCT offer rich conceptual and practical applications that could expand the scope and breadth of career exploration and identity construction through using CACGS. A digital system developed in Hong Kong called Infinity is a case-in-point of a CACGS where users could learn about career planning, engage in self and career construction through using the quantitative and qualitative assessment applications and gamified tools, take career planning actions over time, and communicate with their social supportive systems. Initial findings suggested that users of the system reported lesser decision-making difficulties, higher levels of decision clarity, and better understanding of what is career planning than non-users. Users from high academic achievement schools reported higher levels of career adaptability than their counterparts in schools of similar academic background. Users from low achievement schools reported higher intention to pursue government-supported universities than non-users from schools of similar background. Research and practice implications in schools and organizational settings are discussed.

Quantitative Assessment of Flexibility at the TSO/DSO Interface Subject to the Distribution Grid Limitations

In the last years, renewable energy sources have been changing the power system by making it more challenging to balance the generation and demand at every single point in time. The increasing penetration of distributed generation represents another trend at the distribution level that impacts the exploitation of existing distribution assets. In this context, the flexibility of distributed energy resources connected to the distribution systems may play an important role. The flexibility products are represented by variations in the scheduled/expected active and reactive power setpoints. Recently, regulatory bodies suggested many proposals and undertook actions for enabling new players, such as the distributed energy resources connected to the distribution systems, to provide both system and local services. However, currently, there are still barriers that might limit their effective involvement. Market schemes have been proposed for opening the participation of distributed energy resources in the service markets. This paper proposes an analytical quantification of how much the use of flexibility by the transmission system operator can influence the distribution system operator activities and the expected costs. The final goal is quantifying the flexibility that the transmission system operator can procure from the distribution system without a harmful impact on the distribution network operation. The paper investigates the expected interactions between the use of flexibility for power system balancing and security and the operation of distribution systems. The application of the methodology to a significant Case Study showed that even though the fit and forget approach causes a hypertrophic development of distribution systems to host distributed generation, the transmission system operator cannot obtain the required flexibility services or has to pay extra costs for bottlenecks caused by distribution system operational issues.

The impact of breast support garments on fit, support and posture of larger breasted women

Due to current measurement, sizing and fitting approaches, poor bra fit is prevalent amongst larger breasted women. The impact of improving bra fit hasn't yet been explored. This pre-clinical study aimed to explore immediate and short-term biomechanical responses to changing breast support garment. Asymptomatic participants (n=24) performed a static standing task, drop jumps and seated typing whilst kinematic data from the breasts and spine were recorded. Three breast support conditions were assessed: Usual, professionally fitted bra in the immediate term (PFB), and the same professionally fitted bra after four weeks wear (PFB28). Bra fit assessments were included for both bras. All participants failed the bra fit assessment when wearing the Usual bra and 67% (n=16) failed when wearing the PFB. Less bra fit issues were present in the PFB, resulting in immediate biomechanical changes relating to breast support and spinal posture, yet nothing in the short term (PFB28). This research sets the foundations for future work to investigate whether the implementation of better fitting breast support garments can influence musculoskeletal pain amongst larger breasted women, whilst attributing potential improvement of symptoms, objective measures of breast support and spinal posture.

Technique for measuring the residual strain in strained Si/SiGe MOSFET structures using Raman spectroscopy

Abstract A measurement technique for studying the strain in Si/SiGe layers has been developed based on Raman spectroscopy using a laser microprobe. The Si/SiGe layers were grown by ultra-low pressure chemical vapour deposition in a modified molecular beam epitaxy system. The structures consisted of a strained Si grown on relaxed Si1– x Ge x (x = 0.1, 0.15 . . . 0.35), where the Si channel thickness was varied between 5 and 10 nm. Raman spectroscopy using a 514 nm laser indicated a significant shift in the Si peak from the SiGe layer; the position of this peak is related to the strain in the layer and strongly depends on Ge content, decreasing with increasing Ge in the virtual substrate. However, the strained Si peak shows a considerable overlap with the Si in SiGe peak and is difficult to deconvolute by conventional peak fitting approaches. The residual strain in the thin heterostructure Si/SiGe layers was, therefore, investigated before and after selectively etching the Si. The strain in the channel increased with Ge content in the underlying SiGe as expected, confirming that the high-temperature device processing did not degrade the channel macrostrain.

Revisiting dissociation hypotheses with a structural fit approach: The case of the prepared reflex framework

Attitude and social cognition research often tests dissociations in performance on “explicit” and “implicit” measures using tasks that widely differ from each other. This prevents a clear interpretation of the findings. A structural fit approach, involving tasks that differ only on the factor of theoretical interest, should be preferred. Here, we revisited a dissociation hypothesis using a structural fit approach for the first time. Specifically, Melnikoff, Lambert, and Bargh's (2020) Prepared Reflex framework posits that the establishment and activation of an association between a planned action and its target make the valence of the action unintentionally spread to the target. As a result, the target is evaluated according to the valence of the action. Once the action plan is inactive, however, unintentional measures of attitudes should no longer reflect the valence of the planned action, as the association is not active anymore. In contrast, the valence of the inactive plan should continue to influence intentional measures of attitudes. Melnikoff et al. (2020) found support for this dissociation hypothesis in studies comparing evaluations on self-reports versus an Affect Misattribution Procedure (AMP): Whereas both measures captured the valence of the planned action when the plan was active, only the self-reports captured this valence after the plan was inactive. Here, contrary to the dissociation hypothesis, the plan valence influenced target evaluations on an intentional AMP when the plan was active but not when it was made inactive. These findings highlight the importance of using structurally-fitted tasks in attitude and social cognition research.

Recycling of zinc ions in disc-donut column considering forward mixing mass transfer, and effects of pulsed and non-pulsed condition

The current study focuses on the recovery of zinc ions by solvent extraction in the pulsed contactor. The Zn(II) ions from chloride solution were extracted into the organic phase containing di-(2-ethylhexyl) phosphoric acid (D2EHPA) extractant. The resulting data were characterized for the relative amount of (a) pulsed and no-pulsed condition; and (b) flow rate of both phases. Based on the mass balance equations for the column performance description, numerical computations of mass transfer in a disc-donut column were conducted and validated the experimental data for zinc extraction. Four different models, such as plug flow, backflow, axial dispersion, and forward mixing were evaluated in this study. The results showed that the intensification of the process with the pulsed condition increased and achieved higher mass transfer rates. The forward mixing model findings based on the curve fitting approach validated well with the experimental data. The results showed that an increase in pulsation intensity, as well as the phase flow rates, have a positive impact on the performance of the extractor. In contrast, the enhancement of flow rate led to the reduction of the described model parameters for the adverse phase.