Significant improvement of semi-solid microstructure and mechanical properties of A356 alloy by ARB process

Accumulative roll bonding (ARB) process was used in this study as an effective method for manufacturing high-strength, finely-dispersed and highly-uniform A356 alloy. It was found that when the number of ARB cycles was increased, the uniformity of silicon particles in the aluminum matrix improved, the particles became finer and spheroider and therefore, the tensile strength (TS) and ductility of the samples improved. The microstructure of the manufactured A356 alloy after five ARB cycles indicated a totally modified structure such that it's TS and elongation values reached 269 MPa and 5.3% which were 2.6 and 2.5 times greater than those of the as-cast material, respectively. Also, the hardness value increased from 55.4 (for as-cast sample) to 100.2 HV (after the fifth cycle of ARB), and registered 81% increase.     

Transformation characteristics of functionally graded steels produced by electroslag remelting

In this work, functionally graded steel has been produced via diffusion of the alloying elements during electroslag refining. As the alloying element diffuses, it creates alternating regions with different transformation characteristics. Thus, it is possible to obtain steel composites with various combinations of ferrite, bainite, martensite, and austenite phases. By choosing the appropriate thickness of the slices used to set up the consumable electrodes and subsequent heat treatment, different functionally graded phases may be produced. The diffusion coefficients of chromium, nickel, and carbon atoms at temperatures just above the melting point of iron were estimated. Also, the thicknesses of the emerging bainite and martensite phases were determined and are in good agreement with the experimental results.     

An Experimental Investigation on the Copper Recovery from Flotation Tailing Dams by Reflotation

In this study, the possibility of copper recovery from flotation tailing of Mazraeh copper mine was investigated. Magnetic separation method was used for concentration of non-magnetic minerals, especially copper bearing minerals, from iron minerals. As a result, copper grade increased up to 0.18% and its recovery reached 86%. Due to mineral’s oxidized surface, accompanied oxide minerals and large quantities of fine particles (i.e. about 80% and 57% were finer than 37 and 15 μm in the sample, respectively), flotation of copper was very difficult. In this regard, the effects of important factors including solution pH, type and collector dosage, dispersant, impeller speed, type of frother, percent solid and surface sulfurization were studied. It was concluded that copper recovery of 52% and copper grade of 2.7% could be obtained under following conditions: pH: 11, Collector: Z11 with 40 g/t, Impeller speed: 1400 rpm, Frother: A65, percent solid: 10% and surface sulfurization by Na₂S with 1000 g/t. On the other hand, the addition of sodium silicate as a dispersant showed a negative effect on the flotation performance.     

Minimum redundancy maximum relevance (mRMR) based feature selection from endoscopic images for automatic gastrointestinal polyp detection

Multimedia Tools and Applications - In this paper, a computer based system has been proposed as a support to gastrointestinal polyp detection. It can detect and classify gastrointestinal polyps...     

Determining speaker attributes from stress-affected speech in emergency situations with hybrid SVM-DNN architecture

Multimedia Tools and Applications - In the millions of emergency reporting calls made each year, about a quarter are non-emergencies. To avoid responding to such situations, forensic examination of...     

Accurate Classification of EEG Signals Using Neural Networks Trained by Hybrid Population-physic-based Algorithm

Machine Intelligence Research - A brain-computer interface (BCI) system is one of the most effective ways that translates brain signals into output commands. Different imagery activities can be...     

Miniaturization of Monopole Patch Antenna with Extended UWB Spectrum via Novel Hybrid Heuristic Approach

Wireless Personal Communications - Many of the wireless systems employ ultra wide band (UWB) for its efficient data rate and optimal power consumption. However, all the wireless devices need to...     

An efficient computerized decision support system for the analysis and 3D visualization of brain tumor

The quality of health services provided by medical centers varies widely, and there is often a large gap between the optimal standard of services when judged based on the locality of patients (rural or urban environments). This quality gap can have serious health consequences and major implications for patient’s timely and correct treatment. These deficiencies can manifest, for example, as a lack of quality services, misdiagnosis, medication errors, and unavailability of trained professionals. In medical imaging, MRI analysis assists radiologists and surgeons in developing patient treatment plans. Accurate segmentation of anomalous tissues and its correct 3D visualization plays an important role inappropriate treatment. In this context, we aim to develop an intelligent computer-aided diagnostic system focusing on human brain MRI analysis. We present brain tumor detection, segmentation, and its 3D visualization system, providing quality clinical services, regardless of geographical location, and level of expertise of medical specialists. In this research, brain magnetic resonance (MR) images are segmented using a semi-automatic and adaptive threshold selection method. After segmentation, the tumor is classified into malignant and benign based on a bag of words (BoW) driven robust support vector machine (SVM) classification model. The BoW feature extraction method is further amplified via speeded up robust features (SURF) incorporating its procedure of interest point selection. Finally, 3D visualization of the brain and tumor is achieved using volume marching cube algorithm which is used for rendering medical data. The effectiveness of the proposed system is verified over a dataset collected from 30 patients and achieved 99% accuracy. A subjective comparative analysis is also carried out between the proposed method and two state-of-the-art tools ITK-SNAP and 3D-Doctor. Experimental results indicate that the proposed system performed better than existing systems and assists radiologist determining the size, shape, and location of the tumor in the human brain.