Deposition and characterization of alumina films produced by combustion flame pyrolysis

Alumina coatings have been deposited by combustion flame pyrolysis on amorphous silica and stainless steel substrates with the objective to study the effect of solvent composition, Fe³⁺ addition and determine the thermal fatigue lifetime. The effect of solvent composition on crystallinity, transformation temperature and hardness are studied, three different solvent compositions are chosen for preparing the aluminium nitrate solution. Using 100% water, as-deposited films are amorphous and transform to α-alumina only upon annealing, while this equilibrium phase is directly obtained but with a porous microstructure by using 100% methanol. The hardness of the coatings varies with the flammability of the solvents. The effect of Fe³⁺ addition on the crystallization of alumina is studied by combustion pyrolysis of aqueous solutions of Al³⁺ and Fe³⁺ nitrates. Small amount of ferric nitrate reduced the transformation temperature by 100 °C. Thermal cycling of as-deposited amorphous alumina on stainless steel substrate is carried out at different temperatures to determine the thermal fatigue lifetime.     

A Review of Wavelets for Digital Wireless Communication

Wavelets have been favorably applied in almost all aspects of digital wireless communication systems including data compression, source and channel coding, signal denoising, channel modeling and design of transceivers. The main property of wavelets in these applications is in their flexibility and ability to characterize signals accurately. In this paper recent trends and developments in the use of wavelets in wireless communications are reviewed. Major applications of wavelets in wireless channel modeling, interference mitigation, denoising, OFDM modulation, multiple access, Ultra Wideband communications, cognitive radio and wireless networks are surveyed. The confluence of information and communication technologies and the possibility of ubiquitous connectivity have posed a challenge to developing technologies and architectures capable of handling large volumes of data under severe resource constraints such as power and bandwidth. Wavelets are uniquely qualified to address this challenge. The flexibility and adaptation provided by wavelets have made wavelet technology a strong candidate for future wireless communication. Madan Kumar Lakshmanan was born in Chennai, India, in 1979. He received the B.E. (with distinction) in electrical engineering from the University of Madras, Chennai, India, in 2000. He joined the Indian Software firm, Polaris Software Labs Ltd., in 2000 where he wrote software for Telecommunication applications. At Polaris, he was awarded the “On The Spot Of Excellence Award” for his efforts. In 2003, he moved to the Indian Institute of Technology-Madras, to develop and establish a wireless communications network for rural connectivity. In 2004, he was awarded the Royal Dutch/Shell Chevning scholarship to pursue a Master degree in Telecommunications at the Delft University of Technology (TUDelft). At TUDelft he is affiliated to the International Research Center for Telecommunications-Transmission and Radar (IRCTR) where he is undertaking research in the field of wavelets applications in Wireless Communications. Homayoun Nikookar received his Ph.D. in Electrical Engineering from Delft University of Technology (TUDelft), The Netherlands, in 1995. From 1995 to 1998 he was a postdoc researcher at the International Research Center for Telecommunications-Transmission and Radar, TUDelft, where since 1999 he has been an Assistant Professor. Dr. Nikookar has done research on different areas of wireless communications, including wireless channel modeling, UWB, MIMO, multicarrier transmission, Wavelet-based OFDM and CDMA. He is a senior member of the IEEE.     

Fracture characteristics of a burst tested maraging steel rocket motor case

A 0.3 m diameter, 2 m long and 0.0015 m thick, 18 nickel 1800 MNm^–2 grade maraging steel motor case was designed, fabricated and burst tested to gain experience for using the steel as booster case material in satellite launch vehicles. The bursting occurred at 15.2 MPa for which the effective hoop stress worked out to be 1754 MNm^–2 almost equal to the ultimate tensile strength (1764 MNm^–2) of the material in the solution treated and aged condition. The failure analysis revealed that the material failed due to normal tensile overload fracture. The burst test data was used to arrive at fracture mechanics parameters like crack size, gross section area stress and the stress for leak before bursting.     

Biowaste-derived hydroxyapatite reinforced with polyvinyl pyrrolidone/aloevera composite for biomedical applications

The present investigation focuses on the synthesis of crabshell-derived hydroxyapatite (CS-HAP)/ water-soluble synthetic polymer—polyvinylpyrrolidone(PVP)/aloevera(AV)—a natural biopolymer, as a composite for enhanced mechanical, antibacterial and biocompatible properties. The reinforcement of polymer has a significant function in increasing the mechanical property of the composite, whereas the incorporation of AV improves the antibacterial and biocompatibility. Phase composition, morphology, mechanical property, and hydrophilicity of CS-HAP/PVP/AV biocomposite with different concentrations of PVP and AV were examined by Fourier transform infrared spectroscopy (FTIR), X-Ray diffraction (XRD), scanning electron microscopy with energy dispersive X-ray (SEM-EDX), Vickers microhardness tests, contact angle, respectively. Furthermore, the antibacterial efficiency of the composite is assessed using Escherichia coli (E coli) and Staphylococcus aureus (S aureus). The biocompatibility of HOS MG 63 cells on the CS-HAP/PVP/AV composite is evaluated by MTT assay test. The obtained results evidence that the as-synthesized composite have appropriate mechanical, antibacterial and biocompatible properties. Overall, the combination of mechanical property of PVP, antibacterial and biocompatible property of AV in CS-HAP/PVP/AV, makes the composite a potential therapeutic material for various biomedical applications.     

Chloride metallurgy: PGM recovery and titanium dioxide production

This paper examines in detail the thermodynamics and application of chloride metallurgy for the extraction of precious metals, such as gold and silver, and platinum-group metals. The advantages with regard to the solubilities of metal ion species and their reduction potentials in chloride media are discussed with examples. The use of chloride media for the extraction of platinum-group metals from spent autocatalysts and for the production of high-purity pigment-grade TiO₂ and titanium metal from ilmenite feed stocks is discussed in the case studies provided. For more information, contact V.I. Lakshmanan, Process Research Ortech, 2395 Speakman Dr., Mississauga, ON, L5K 1B3 Canada; (905) 822-4941; fax (905) 822-9537.     

Dynamic Matrix Rank with Partial Lookahead

We consider the problem of maintaining information about the rank of a matrix M under changes to its entries. For an n×n matrix M, we show an amortized upper bound of O(n ^ω?1) arithmetic operations per change for this problem, where ω<2.373 is the exponent for matrix multiplication, under the assumption that there is a lookahead of up to Θ(n) locations. That is, we know up to the next Θ(n) locations (i ₁,j ₁),(i ₂,j ₂),…?, whose entries are going to change, in advance; however we do not know the new entries in these locations in advance. We get the new entries in these locations in a dynamic manner. The dynamic matrix rank problem was first studied by Frandsen and Frandsen who showed an upper bound of O(n ^1.575) and a lower bound of Ω(n) for this problem and later Sankowski showed an upper bound of O(n ^1.495) for this problem when allowing randomization and a small probability of error. These algorithms do not assume any lookahead. For the dynamic matrix rank problem with lookahead, Sankowski and Mucha showed a randomized algorithm (with a small probability of error) that is more efficient than these algorithms.     

Intelligent Machine Learning with Metaheuristics Based Sentiment Analysis and Classification

Sentiment Analysis (SA) is one of the subfields in Natural Language Processing (NLP) which focuses on identification and extraction of opinions that exist in the text provided across reviews, social media, blogs, news, and so on. SA has the ability to handle the drastically-increasing unstructured text by transforming them into structured data with the help of NLP and open source tools. The current research work designs a novel Modified Red Deer Algorithm (MRDA) Extreme Learning Machine Sparse Autoencoder (ELMSAE) model for SA and classification. The proposed MRDA-ELMSAE technique initially performs preprocessing to transform the data into a compatible format. Moreover, TF-IDF vectorizer is employed in the extraction of features while ELMSAE model is applied in the classification of sentiments. Furthermore, optimal parameter tuning is done for ELMSAE model using MRDA technique. A wide range of simulation analyses was carried out and results from comparative analysis establish the enhanced efficiency of MRDA-ELMSAE technique against other recent techniques.     

Adaptive Window Based 3-D Feature Selection for Multispectral Image Classification Using Firefly Algorithm

Feature extraction is the most critical step in classification of multispectral image. The classification accuracy is mainly influenced by the feature sets that are selected to classify the image. In the past, handcrafted feature sets are used which are not adaptive for different image domains. To overcome this, an evolutionary learning method is developed to automatically learn the spatial-spectral features for classification. A modified Firefly Algorithm (FA) which achieves maximum classification accuracy with reduced size of feature set is proposed to gain the interest of feature selection for this purpose. For extracting the most efficient features from the data set, we have used 3-D discrete wavelet transform which decompose the multispectral image in all three dimensions. For selecting spatial and spectral features we have studied three different approaches namely overlapping window (OW-3DFS), non-overlapping window (NW-3DFS) adaptive window cube (AW-3DFS) and Pixel based technique. Fivefold Multiclass Support Vector Machine (MSVM) is used for classification purpose. Experiments conducted on Madurai LISS IV multispectral image exploited that the adaptive window approach is used to increase the classification accuracy.     

Blockchain Based Consensus Algorithm and Trustworthy Evaluation of Authenticated Subgraph Queries

Over the past era, subgraph mining from a large collection of graph database is a crucial problem. In addition, scalability is another big problem due to insufficient storage. There are several security challenges associated with subgraph mining in today’s on-demand system. To address this downside, our proposed work introduces a Blockchain-based Consensus algorithm for Authenticated query search in the Large-Scale Dynamic Graphs (BCCA-LSDG). The two-fold process is handled in the proposed BCCA-LSDG: graph indexing and authenticated query search (query processing). A blockchain-based reputation system is meant to maintain the trust blockchain and cloud server of the proposed architecture. To resolve the issues and provide safe big data transmission, the proposed technique also combines blockchain with a consensus algorithm architecture. Security of the big data is ensured by dividing the BC network into distinct networks, each with a restricted number of allowed entities, data kept in the cloud gate server, and data analysis in the blockchain. The consensus algorithm is crucial for maintaining the speed, performance and security of the blockchain. Then Dual Similarity based MapReduce helps in mapping and reducing the relevant subgraphs with the use of optimal feature sets. Finally, the graph index refinement process is undertaken to improve the query results. Concerning query error, fuzzy logic is used to refine the index of the graph dynamically. The proposed technique outperforms advanced methodologies in both blockchain and non-blockchain systems, and the combination of blockchain and subgraph provides a secure communication platform, according to the findings.