Breast cancer diagnosis: a survey of pre-processing, segmentation, feature extraction and classification

Machine learning methods have been an interesting method in the field of medical for many years, and they have achieved successful results in various fields of medical science. This paper examines the effects of using machine learning algorithms in the diagnosis and classification of breast cancer from mammography imaging data. Cancer diagnosis is the identification of images as cancer or non-cancer, and this involves image preprocessing, feature extraction, classification, and performance analysis. This article studied 93 different references mentioned in the previous years in the field of processing and tries to find an effective way to diagnose and classify breast cancer. Based on the results of this research, it can be concluded that most of today’s successful methods focus on the use of deep learning methods. Finding a new method requires an overview of existing methods in the field of deep learning methods in order to make a comparison and case study

An Improved Adaptive Trust-Region Method for Unconstrained Optimization

In this study, we propose a trust-region-based procedure to solve unconstrained optimization problems that take advantage of the nonmonotone technique to introduce an efficient adaptive radius strategy. In our approach, the adaptive technique leads to decreasing the total number of iterations, while utilizing the structure of nonmonotone formula helps us to handle large-scale problems. The new algorithm preserves the global convergence and has quadratic convergence under suitable conditions. Preliminary numerical experiments on standard test problems indicate the efficiency and robustness of the proposed approach for solving unconstrained optimization problems

Investigating the Effect of Curing and Thermal Equilibrium Time on Rutting Potential of Hot Mix Asphalt

Rutting is a common damage of flexible pavements, reducing the service life of asphalt pavement. Due to laboratory limitations, asphalt mixtures are subjected to different curing times (since construction until placement in the test chamber) and thermal equilibrium times (since placement in the test chamber until the beginning of the test) before rutting tests. Neglecting these factors can lead to errors in the laboratory results. Therefore, the present study attempted to investigate the effect of curing times of 1, 2, and 3 days at 25ºC and thermal equilibrium times of 2, 4, and 6 hours on the rutting potential of different hot-mix asphalt (HMA) mixtures. Results of rutting tests showed that the rutting potential of asphalt mixtures decreases by increasing the curing time, while the permanent deformation at the end of loading cycles and rutting potential increase by increasing the thermal equilibrium time. Additionally, the results of statistical analyses revealed that curing time and thermal equilibrium time change the rutting potential of asphalt mixtures

Investigations on Vehicle Interaction with CWR Tracks Considering Some Aspects of Rail Support Modulus

One of the important parameters for controlling the behavior of continuous welded rail (CWR) in railway tracks is rail support modulus. Reviewing the technical literature reveals some elapsed points in this regard such as continuous or discrete supports, V-shaped rail irregularity and geometrical stiffness which can considerably affect on the vehicle-track dynamic interaction. So, the present study was allocated to numerical investigating the effects of aforementioned parameters on the vehicle-track dynamic interaction. In this matter, the finite element model of ballasted railway track in conjunction with multi-body dynamics model of vehicle was developed and they simultaneously solved numerically. This preliminary model was verified through comparison of the results with published works in this area. Consequently the model was promoted considering continuous and discrete support condition, implementing the V-shaped irregularity and geometrical stiffness. In each step, the results of the extended models were completely presented in the form track structure response

A STUDY OF THE PIANO WORKS OF CHU WANGHUA, WITH AN EMPHASIS ON SIX PRELUDES

ABSTRACT From the early twentieth century to the present day, Chinese piano music has begun to enjoy enormous prosperity, integrating a modern and distinctive Chinese style with Western musical language. Chu WangHua is one of the most distinguished Chinese composers and pianists and has had great influence on the recent development of Chinese piano music. During his most turbulent compositional periods, Chu struggled with deep depression and pressure to succeed; however, he persisted in composing, his great passion. In his sixty-year compositional career, Chu produced a large body of repertoire, including piano works, concertos, symphonies, ensemble, string quartets and more; the majority of these are piano works. Six Preludes is one of Chu’s most representative and remarkable works written in the Chinese style. The six pieces in this set, named Bamboo in the Wind, Sound of Valley, On the Banks of the River, Berceuse, Elegie, and Memorial, are based on Chinese traditional folk tunes and instrumental music and incorporate Western musical style, harmonic language, and compositional technique. This study will examine Six Preludes, emphasizing the following musical aspects: traditional Chinese scales and modes, parallel harmony, counterpoint, and formal structure, to explore the distinctions between Chinese and Western styles. Chu WangHua’s unique approach to composition not only enables him to stand out from other Chinese composers, but also promotes Chinese piano music worldwide

Laboratory Investigation on the Effect of Microsilica Additive on the Mechanical Behavior of Deep Soil Mixing Columns in Saline Dry Sand

Since loose and salty subgrades consider as problematic barriers while constructing new transportation infrastructures such as railway tracks and roads are required, the current study aims to find a solution to stabilize these kinds of subgrades using the deep soil mixing (DSM) technique and micro silica additive. In the present study a series of experimental DSM columns were executed in a salty sand-filled chamber utilizing a laboratory scale DSM apparatuses. In the first step, by adding three salt percentages of 5, 10 and 20 into the original sand, four different sandy subgrades with a relative density of 70% were prepared. Considering three percentages of 10, 15 and 20 for micro silica additive, the water-to-cement ratio of 1, salt percentages of 0, 5, 10 and 20 totally 150 sand-cement columns were constructed in the lab environment. In continuation, unconfined compression strength (UCS) and elasticity modulus of all capped DSM columns have been determined and interpreted using scanning electron microscope (SEM) images at three ages of 7,14 and 28 days. The results indicated that increasing the salinity of subgrade soil from 0 to 20% resulted in a falling UCS and Young module by 28 and 21% for 28-days specimens. Furthermore, as a solution, adding micro silica in cement-water grout up to 15% resulted in enhancing mechanical characteristics of the DSM columns. So that adding 15% microsilica caused a 21 and 42% increase in UCS and elasticity modulus of 28-days samples respectively, executed in subgrade with 20% salt

A Low-Complexity Near-Optimal Detector for Multispan Zero-Dispersion Fiber-Optic Channels

We design a novel receiver based on the theoretical finding that the linear phase noise is uncorrelated with the nonlinear phase noise. The implementation of the proposed receiver is straightforward and it performs almost equally to the optimal detector at a much lower complexity

Political Economy of Renewable Energy and Scenarios for Iran in the Energy Transition to 2050 Outlook

In recent years, the share of renewables in the global energy basket has increased significantly. This will have geopolitical consequences, especially for a country like Iran, whose economy is largely dependent on fossil fuel revenues. By examining the transition process of the global and regional economy towards renewable and clean energy, this article tries to outline Iran's position in the energy transition perspective. The main question is: how will Iran position itself in the global energy transition outlook to 2050? Through scenario planning, the authors identified four possible scenarios, including "meeting sustainable development and transition to green gold", "gradual and independent transition to sustainable development and green gold", "development based on black gold" and "development locked with black gold". They cover a wide range of possible futures. By knowing these scenarios and comparing their desirability, policymakers will be able to properly assess the costs and opportunities of the transition to clean energy in different situations.

Diffusion tension imaging is a good tool for assessing patients with dementia and behavioral problems and discriminating them from other dementia patients

Background Dementia is one of the leading public health concerns as the world’s population ages. Although Alzheimer’s disease (AD) is the most common dementia diagnosis among older patients, some patients have additional behavioral symptoms. It is therefore important to provide an exact diagnosis, both to provide the best possible treatment for patients and to facilitate better understanding. Purpose To investigate whether magnetic resonance imaging (MRI) with fractional anisotropy (FA) can accurately find patients with behavioral symptoms within a group of AD patients. Material and Methods Forty-five patients from the geriatric outpatient clinic were recruited consecutively to form a group of patients with AD and behavioral symptoms (AD + BS) and a control group of 50 patients with established AD. All patients had a full assessment for dementia to establish the diagnosis according to ICD-10. MRI included 3D anatomical recordings for morphometric measurements, DTI for fiber tracking, and quantitative assessment of regional white matter integrity. The DTI analyses included computing of the diffusion tensor and its derived FA index. Results We found a significant difference in FA values between the patient groups’ frontal lobes. The FA was greater in the study group in both left (0.39 vs 0.09, p < 0.05) and right (0.40 vs 0.16, p < 0.05) frontal lobes. Conclusion MRI with FA will find damage in frontal tracts and may be used as a diagnostic tool and be considered a robust tool for the recognizing different types of dementia in the future.publishedVersio