Evolution of microstructure and mechanical properties during quenching and tempering of ultrahigh strength 0.3C Si–Mn–Cr–Mo low alloy steel

Effects of quenching and tempering treatments on the development of microstructure and mechanical properties of ultrahigh strength 0.3C Si–Mn–Cr–Mo low alloy steel were investigated. Samples were austenitized at 1123–1323 K for 2400 s and oil quenched (OQ) to produce mixed microstructures. Tempering was carried out at 473–773 K for 2–3 h. Phase transformation temperatures were measured using dilatometer. The microstructures were characterized using optical and scanning electron microscope. SEM–EDS analysis was carried out to determine the type and size of non-metallic inclusions. Volume percent of retained austenite was measured by X-ray diffraction technique. Hardness, tensile properties, and impact energies were also determined for all heat treated conditions. Fractography of impact specimens were done using stereomicroscope and SEM. The results showed that newly developed steel exhibited peak hardness, yield strength, and tensile strength of about 600 HV, 1760 MPa, and 1900 MPa, respectively, when OQ from 1203 K and tempered in between 473 and 573 K, combined with adequate ductility and impact toughness. Decrease in hardness and strength was observed with increasing tempering temperature whereas the impact energy was stable up to 623 K, however, impact energy was found to decrease above 632 K due to temper martensite embrittlement.     

Failure Analysis of WC–2Ni–1Co Rotor Part

This study deals with the analysis of an ink-producing machine rotor part composed of WC–2Ni–1Co which failed in brittle manner during service. The part was made by powder metallurgy techniques and is being used in ink-grinding machines due to its high hardness and wear resistance. Similar parts had worked satisfactorily for many ink compositions, but the part under investigation failed prematurely. Investigation was considered important because the part is expensive, and other identical components frequently failed after a short service life. Moreover, replacement of the part requires complete dismantling of the machine which reduces the production rate. Spectroscopic analysis, density, optical and scanning electron microscopy, SEM–EDS analysis, fractography, X-ray diffraction, and microhardness measurements were carried out on failed parts to find out the root causes of the failure. Results revealed that the part cracked due to combined effects of selective dissolution of metal binder-caused corrosive action of ink solution and hydrogen-induced deterioration of WC and Ni–Co phases. Localized removal of binder phase left the hard WC phase unsupported. Cracks were found initiating from the root of the machined slot which acted as a stress concentration point and resulted in brittle fracture.     

A comparative study of wavelet families for classification of wrist motions

The selection of most suitable mother wavelet function is still an open research problem in various signal and image processing applications. This paper presents a comparative study of different wavelet families (Daubechies, Symlets, Coiflets, and Biorthogonal) for analysis of wrist motions from electromyography (EMG) signals. EMG signals are decomposed into three levels using discrete wavelet packet transform. From the decomposed EMG signals, root mean square (RMS) value, autoregressive (AR) model coefficients (4th order) and waveform length (WL) are extracted. Two data projection methods such as principal component analysis (PCA) and linear disciminant analysis (LDA) are used to reduce the dimensionality of the extracted features. Probabilistic neural network (PNN) and general regression neural network (GRNN) are employed to classify the different types of wrist motions, which gives a promising accuracy of above 99%. From the analysis, we inferred that ‘Biorthogonal’ and ‘Coiflets’ wavelet families are more suitable for accurate classification of EMG signals of different wrist motions.     

Feature Analysis of Unsupervised Learning for Multi-task Classification Using Convolutional Neural Network

This study analyzes the characteristics of unsupervised feature learning using a convolutional neural network (CNN) to investigate its efficiency for multi-task classification and compare it to supervised learning features. We keep the conventional CNN structure and introduce modifications into the convolutional auto-encoder design to accommodate a subsampling layer and make a fair comparison. Moreover, we introduce non-maximum suppression and dropout for a better feature extraction and to impose sparsity constraints. The experimental results indicate the effectiveness of our sparsity constraints. We also analyze the efficiency of unsupervised learning features using the t-SNE and variance ratio. The experimental results show that the feature representation obtained in unsupervised learning is more advantageous for multi-task learning than that obtained in supervised learning.     

Effect of Chain Length on the Micellization,Antibacterial, DPPC Interaction and Antioxidant Activities of l‐3,4‐Dihydroxyphenylalanine (l‐DOPA) Esters

l ‐DOPA (l ‐3,4‐dihydroxyphenylalanine) has been widely used as a drug in the clinical treatment of Parkinson's disease. In this report, the systematic study of the effect of chain length on the critical micelle concentration (CMC), antibacterial and antioxidant activity of esters derived from the aromatic amino acid l ‐3,4‐dihydroxyphenylalanine as surfactants are accounted for the first time. The antibacterial activity displayed a cut‐off effect at C₁₂ with respect to both gram positive and gram negative bacteria (except for Pseudomonas aeruginosa where the cut‐off was displayed at C₁₀). Correlation of the CMC with the minimum inhibitory concentration (MIC) shows that the DOPA esters exist in micellar form at the MIC. An increase in chain length of the DOPA esters induces greater binding with phospholipid vesicles 1,2‐dipalmitoyl‐sn‐glycero‐3‐phosphocholine. The C₁₂ ester possessed highest radical scavenging ability among the esters tested against both 2,2‐diphenyl‐1‐picrylhydrazyl and 2,2′‐azino‐bis(3‐ethylbenzothiazoline‐6‐sulphonic acid) showing that antioxidant activity of the DOPA esters is also affected by chain length. This study showed that DOPA esters are promising candidates as antibacterial agents as well as good antioxidants.     

Remaining idle time aware intelligent channel bonding schemes for cognitive radio sensor networks

Wireless Networks - Channel bonding (CB) is a technique used to provide larger bandwidth to users. It has been applied to various networks such as wireless local area networks, wireless sensor...     

Effect of graphite and Mn3O4 on clay-bonded SiC ceramics for the production of electrically conductive heatable filter

Electrically conductive porous SiC ceramics are attracting substantial attention due to their application in heatable filters, vacuum chuck, and semiconductor processing parts, etc. The main problem is their high processing cost. Ideal candidates from an engineering ceramic perspective will be mechanically durable and have the required electrical properties with sufficiently low fabrication costs. To decrease the sintering temperature, kaolin has been added, but it tended to render the material an insulator. Graphite was used to effectively decrease the electrical resistivity. Additionally, manganese oxide was used to decrease the quantity of kaolin (the component that leads to an insulator material after sintering) and decrease the electrical resistivity while maintaining the mechanical properties. In our study, we found that SiC with 35% kaolin, 20% graphite and 10% manganese oxide can produce samples with 6.5 × 10^?1 Ω cm electrical resistivity and 43.5 MPa flexural strength at a low sintering temperature of 1200 °C.     

Investigation of the physicochemical and biological properties of proline-based surfactants in single and mixed surfactant systems

A series of surfactants derived from l-Proline, the free amine esters, the ester hydrochlorides and the quaternary ammonium compounds with varying chain lengths (C₈–C₁₄) were synthesised. The physicochemical and biological properties were determined in both single and sodium dodecyl sulphate (SDS) mixed systems with a view of enhancing the properties of the individual surfactants as potential ingredients in detergent formulations. The mode of action of the proline surfactants were investigated by their ability to form mixed micelles with the phospholipid 1,2-dimyristoyl-sn-glycero-3-phosphatidylcholine (DMPC). The presence of a quaternary ammonium moiety and an increase in alkyl chain length were found to enhance the antibacterial activity of the proline QUAT derivatives. The SDS-C₁₄ QUAT mixed system displayed good antibacterial activity with optimum activity at mole fractions α_QUAT: 0.4 and 0.6. The antibacterial activity of the mixed system was found to be governed by the monomers rather than the micelles. The SDS-C₁₄ QUAT mixed system also showed moderate irritancy which makes them potential candidates as detergents.     

Automatic Radial Distortion Estimation from a Single Image

Many computer vision algorithms rely on the assumptions of the pinhole camera model, but lens distortion with off-the-shelf cameras is usually significant enough to violate this assumption. Many methods for radial distortion estimation have been proposed, but they all have limitations. Robust automatic radial distortion estimation from a single natural image would be extremely useful for many applications, particularly those in human-made environments containing abundant lines. For example, it could be used in place of an extensive calibration procedure to get a mobile robot or quadrotor experiment up and running quickly in an indoor environment. We propose a new method for automatic radial distortion estimation based on the plumb-line approach. The method works from a single image and does not require a special calibration pattern. It is based on Fitzgibbon’s division model, robust estimation of circular arcs, and robust estimation of distortion parameters. We perform an extensive empirical study of the method on synthetic images. We include a comparative statistical analysis of how different circle fitting methods contribute to accurate distortion parameter estimation. We finally provide qualitative results on a wide variety of challenging real images. The experiments demonstrate the method’s ability to accurately identify distortion parameters and remove distortion from images.     

Failure Analysis of Cast Lead–Antimony Battery Grids

This paper presents the failure investigation of lead-acid battery grids received from a local battery manufacturer. Distortion, cracking, and brittleness were observed in as-cast grids. These battery grids were gravity cast by re-melting of locally made Pb–Sb ingots. However, similar distortion and brittleness were not observed in grids of similar design cast by re-melting of imported Pb–Sb ingots. Spectroscopy, optical and scanning electron microscopy, SEM–EDS analysis, and microhardness measurements were carried out on both types of grids to find out the root cause of failure. It was concluded that the distortion and cracking were mainly caused because of coarse dendritic microstructure with interdendritic and intercellular segregation produced by either high pouring temperature or low cooling rates employed during casting. This conclusion suggests that the casting parameters may have differed for the two types of ingots used. However, another contributing factor was thermal stresses induced during solidification and the brittleness of the locally produced ingots which contained a high arsenic content.