A Comparative Study for 2D and 3D Computer-aided Diagnosis Methods for Solitary Pulmonary Nodules

Many computer-aided diagnosis (CAD) methods, including 2D and 3D approaches, have been proposed for solitary pulmonary nodules (SPNs). However, the detection and diagnosis of SPNs remain challenging in many clinical circumstances. One goal of this work is to investigate the relative diagnostic accuracy of 2D and 3D methods. An additional goal is to develop a two-stage approach that combines the simplicity of 2D and the accuracy of 3D methods. The experimental results show statistically significant differences between the diagnostic accuracy of 2D and 3D methods. The results also show that with a very minor drop in diagnostic performance the two-stage approach can significantly reduce the number of nodules needed to be processed by the 3D method, streamlining the computational demand

Supervised Collective Classification for Crowdsourcing

Crowdsourcing utilizes the wisdom of crowds for collective classification via information (e.g., labels of an item) provided by labelers. Current crowdsourcing algorithms are mainly unsupervised methods that are unaware of the quality of crowdsourced data. In this paper, we propose a supervised collective classification algorithm that aims to identify reliable labelers from the training data (e.g., items with known labels). The reliability (i.e., weighting factor) of each labeler is determined via a saddle point algorithm. The results on several crowdsourced data show that supervised methods can achieve better classification accuracy than unsupervised methods, and our proposed method outperforms other algorithms.Comment: to appear in IEEE Global Communications Conference (GLOBECOM) Workshop on Networking and Collaboration Issues for the Internet of Everythin

Improved Antireflection Properties of an Optical Film Surface with Mixing Conical Subwavelength Structures

Based on finite difference time domain method, an optical film surface with mixing conical subwavelength structures is numerically investigated to improve antireflection property. The mixing conical subwavelength structure is combined with the pure periodic conical subwavelength structures and the added small conical structures in the gap between the pure periodic conical subwavelength structures. The antireflection properties of two types of subwavelength structures with different aspect ratios in spectral range of 400–800 nm are analyzed and compared. It is shown that, for the mixing type, the average reflectance is decreased and the variances of the reflectance are evidently smaller. When the added structure with a better aspect ratio exists, the average reflectance of the surface can be below 0.30%. Obviously, the antireflection properties of the optical film surface with mixing conical subwavelength structures can be improved

Key Users and Box Office Analysis in an Interest Based Virtual Community

In recent years, with the growth of the Internet technology, the users of virtual community not only play the role of the information receiver but also a very important one to provide information. However, there is large amount of information aggregated daily and therefore information overloading has become a very serious problem. Under this situation, how to find information efficiently is also a very important issue. In this paper, we believe users in a virtual community may affect each other, especially those with high influence who have been called as Key Users. Therefore, we observe the biggest virtual community of movies on the Internet which is named IMDb (The Internet Movie Database). An architecture also has been proposed that combines Social Networks Analysis and the features of IMDb to discover those users who have high influence in the virtual community. We collected 17 months (January 2010 to May 2011) from IMDb including 17 366 users and 243 074 reviews. By applying the method we proposed, there are about 22 key users and 111 reviews were discovered. We also use the box office of the movies to justify our results

Particle bonding mechanism in CGDS-a three-dimensional approach

Abstract: Cold gas dynamics spray (CGDS) is a surface coating process using highly accelerated particles to form the surface coating by high speed impact of the particles. In the CGDS process, metal particles of generally 1-50 μm diameter is carried by a gas stream in high pressure (typically 20-30 atm) through a DE Laval type nozzle to achieve supersonic flying so as to impact on the substrate. Typically, the impact velocity ranges between 300 and 1200 m/s in the CGDS process. When the particle gains its critical velocity, the minimum in-flight speed at which it can deposit, adiabatic shear instabilities will occur. Herein, to ascertain the critical velocities of different particle sizes on the bonding efficiency in CGDS process, three-dimensional numerical simulations of single particle deposition process were performed. In the CGDS process, one of the most important parameters which determine the bonding strength with the substrate is particle impact temperature. Bonding will occur when the particle’s impacting velocity surpass the critical velocity, at which the interface can achieve 60 % of melting temperature of particle material (Ref 1). Therefore, critical velocity should be a main parameter on the coating quality. The particle critical velocity is determined not only by its size, but also by its material properties. This study numerically investigate the critical velocity for the particle deposition process in CGDS. In the present numerical analysis, copper (Cu) was chosen as particle material and aluminum (Al) as substrate material for this study. The impacting velocities were selected between 300 m/s and 800 m/s increasing in steps of 100 m/s. The simulation result reveals temporal and spatial interfacial temperature distribution and deformation between particle(s) and substrate. Finally, comparison is carried out between the computed results and experimental data

Effects of Particle Size Fractions on Reducing Heart Rate Variability in Cardiac and Hypertensive Patients

It is still unknown whether the associations between particulate matter (PM) and heart rate variability (HRV) differ by particle sizes with aerodynamic diameters between 0.3 μm and 1.0 μm (PM(0.3–1.0)), between 1.0 μm and 2.5 μm (PM(1.0–2.5)), and between 2.5 μm and 10 μm (PM(2.5–10)). We measured electrocardiographics and PM exposures in 10 patients with coronary heart disease and 16 patients with either prehypertension or hypertension. The outcome variables were standard deviation of all normal-to-normal (NN) intervals (SDNN), the square root of the mean of the sum of the squares of differences between adjacent NN intervals (r-MSSD), low frequency (LF; 0.04–0.15 Hz), high frequency (HF; 0.15–0.40 Hz), and LF:HF ratio for HRV. The pollution variables were mass concentrations of PM(0.3–1.0), PM(1.0–2.5), and PM(2.5–10). We used linear mixed-effects models to examine the association between PM exposures and log(10)-transformed HRV indices, adjusting for key personal and environmental attributes. We found that PM(0.3–1.0) exposures at 1- to 4-hr moving averages were associated with SDNN and r-MSSD in both cardiac and hypertensive patients. For an interquartile increase in PM(0.3–1.0), there were 1.49–4.88% decreases in SDNN and 2.73–8.25% decreases in r-MSSD. PM(0.3–1.0) exposures were also associated with decreases in LF and HF for hypertensive patients at 1- to 3-hr moving averages except for cardiac patients at moving averages of 2 or 3 hr. By contrast, we found that HRV was not associated with either PM(1.0–2.5) or PM(2.5–10). HRV reduction in susceptible population was associated with PM(0.3–1.0) but was not associated with either PM(1.0–2.5) or PM(2.5–10)