Hydrothermal synthesis and indication of room temperature ferromagnetism in CeO2 nanowires

Bundle of CeO₂ nanowires have been successfully synthesized by a simple hydrothermal process using Ce(NO₃)₃·6H₂O as cerium source and NaH₂PO₄·2H₂O as mineralizer, into which no surfactant or template was introduced. The synthesized nanowires were characterized using X-ray diffraction (XRD), field emission scanning electron microscopy (FE-SEM), energy dispersive X-ray spectroscopy (EDS), Raman spectroscopy and magnetization measurements. The XRD results indicated that CeO₂ nanowires have fluorite structure. Magnetization measurements indicate that CeO₂ nanowires exhibit room temperature ferromagnetism with remanent magnetization (M_r) and coercivity (H_C) of about 7.44 × 10^? 4 (emu/g) and 27.19 Oe, respectively, which may results due to the presence of defects in the CeO₂ nanowires.     

Aspect Level Songs Rating Based Upon Reviews in English

With the advancements in internet facilities, people are more inclined towards the use of online services. The service providers shelve their items for e-users. These users post their feedbacks, reviews, ratings, etc. after the use of the item. The enormous increase in these reviews has raised the need for an automated system to analyze these reviews to rate these items. Sentiment Analysis (SA) is a technique that performs such decision analysis. This research targets the ranking and rating through sentiment analysis of these reviews, on different aspects. As a case study, Songs are opted to design and test the decision model. Different aspects of songs namely music, lyrics, song, voice and video are picked. For the reason, reviews of 20 songs are scraped from YouTube, pre-processed and formed a dataset. Different machine learning algorithms—Naïve Bayes (NB), Gradient Boost Tree, Logistic Regression LR, K-Nearest Neighbors (KNN) and Artificial Neural Network (ANN) are applied. ANN performed the best with 74.99% accuracy. Results are validated using K-Fold.     

Context Based Adoption of Ranking and Indexing Measures for Cricket Team Ranks

There is an international cricket governing body that ranks the expertise of all the cricket playing nations, known as the International Cricket Council (ICC). The ranking system followed by the ICC relies on the winnings and defeats of the teams. The model used by the ICC to implement rankings is deficient in certain key respects. It ignores key factors like winning margin and strength of the opposition. Various measures of the ranking concept are presented in this research. The proposed methods adopt the concepts of h-Index and PageRank for presenting more comprehensive ranking metrics. The proposed approaches not only rank the teams on their losing/winning stats but also take into consideration the margin of winning and the quality of the opposition. Three cricket team ranking techniques are presented i.e., (1) Cricket Team-Index (ct-index), (2) Cricket Team Rank (CTR) and (3) Weighted Cricket Team Rank (WCTR). The proposed metrics are validated through the collection of cricket dataset, extracted from Cricinfo, having instances for all the three formats of the game i.e., T20 International (T20i), One Day International (ODI) and Test matches. The comparative analysis between the proposed and existing techniques, for all the three formats, is presented as well.     

EDM of Ti-6Al-4V: Electrode and polarity selection for minimum tool wear rate and overcut

Titanium and its alloys especially Ti-6Al-4V are being widely used numerous application areas. In addition to have iconic properties, Ti-6Al-4V is considered as challenging material in machining perspective that is why it has captured global research focus. In this research, electric discharge machining of Ti-6Al-4V has been carried out by employing four different types of electrode materials (graphite, aluminum, copper, and brass) assigned with two alternate polarities (positive and negative). Selection of the most appropriate tool material and electrode polarity is the important aspect needed to be explored for this alloy. In addition to polarity, discharge current, and pulse time ratio have been considered as process variables owing to have their direct influence in electric discharge machining. Taguchi L9 array has been employed for each of the four electrodes with positive polarity and similarly L9 with negative polarity. Thus, a total number of 72 experiments have been conducted. Tool wear rate and overcut (OC) around the machined surfaces are the response characteristics to be investigated in order to achieve minimum amounts of both of these two responses. Selection of the most suitable tool with common tool polarity has been carried out meeting the decision criteria of minimum tool wear and minimum OC.     

One step synthesis of rutile TiO2 nanoparticles at low temperature

Sphere-like rutile TiO2 nanocrystals have been synthesized by sol-gel method followed by hydrolysis of titanium tetrachloride in deionized water in the presence of ammonium hydroxide as hydrolysis catalyst. The as-prepared TiO2 nanoparticles have single rutile phase with average diameter approximately 26.4 nm. The results show that the temperature has a great influence on the particle size distribution and also crystalline phase (rutile) of TiO2 nanoparticles is consistent with the temperature. Characterization of the as-prepared nanocrystalline powder was carried out by different techniques such as powder X-ray diffraction (XRD), field emission transmission electron microscopy (FE-TEM) and Raman spectroscopy.     

Calculation of the performance measurements for elastic optical OFDM networks

We present an approximate analytical method to evaluate the performance measurements in optical orthogonal frequency-division multiplexing networks. Our approach divides the network into layers, and the equivalent path technique is used to model each path as an equivalent single-link system. The analysis of the performance measurements for an equivalent single-link system is based on a superposition concept using the Kaufman/Delbrouck recursion model. We assume static routing with a first-fit spectrum allocation. The simulation results indicating the accuracy of our method are presented.     

Resource Allocation for OFDMA Based Cognitive Radio Networks with Arbitrarily Distributed Finite Power Inputs

The existing works on resource allocation for OFDMA based cognitive radio networks are based on the assumption of Gaussian inputs whereas in practical systems the inputs are taken from a set of finite symbol alphabets. This paper considers a system with arbitrarily distributed finite power inputs and solve the resource allocation problem by employing the relationship between mutual information and minimum mean-square error. To protect the primary users’ links, constraint on interference power of the secondary users (SUs) is imposed. In OFDMA based CR networks, a tone can be assigned to one SU at most (exclusivity constraint), due to which the resource allocation problem becomes combinatorial and its solution becomes prohibitively difficult.In this paper, first, the exclusivity constraint on tones allocation is relaxed, the problem is convexified and an optimal solution is derived that provides an upper bound on the system performance. Then, an integer tone allocation and optimal power allocation (ITA–OPA) algorithm is developed that guarantees the assignment of each tone to a single SU with close-to-optimal performance. Finally, keeping in view the complexity of the optimal solution and ITA–OPA algorithm, a low-complexity suboptimal algorithm is devised that accounts for exclusive tone assignment. Simulation results show that the suboptimal algorithm also achieves near-optimal performance. The proposed algorithms outperforms the algorithms that assume Gaussian inputs.     

Business undergraduates’ perceived use outcomes of Moodle in a blended learning environment: The roles of usability factors and external support

This study was designed to explore the effects or roles of usability factors (i.e., perceived ease of use, perceived usefulness, and satisfaction) and external support (i.e., teacher and peer support) on undergraduates’ use outcomes of Moodle in a blended learning environment. The research hypotheses derived from relevant constructs taken from the technology acceptance model, information systems continuance model, and the theory of reasoned action. The study’s dependent variable is use outcomes, which was conceptualized with factors such as academic performance, perceived learning assistance, and perceived impacts on learning. We conducted a cross-sectional survey and collected data from 126 undergraduate students attending a university in the Maritime region of Canada. The partial least squares technique was used to test the hypothesized relationships in the proposed research model. We found that usability factors have positive effects on students’ use outcomes; contrarily to predictions teacher and peer support did not. The findings of the study offer useful insights that can help HE administrators gain an understanding of antecedent factors likely to enhance students’ use outcomes of Moodle.     

Capacity maximizing in massive MIMO with linear precoding for SSF and LSF channel with perfect CSI

The capacity of a massive MIMO cellular network depends on user and antenna selection algorithms, and also on the acquisition of perfect Channel State Information (CSI). Low computational cost algorithms for user and antenna selection significantly may enhance the system capacity, as it would consume a smaller bandwidth out of the total bandwidth for downlink transmission. The objective of this paper is to maximize the system sum-rate capacity with efficient user and antenna selection algorithms and linear precoding. We consider in this paper, a slowly fading Rayleigh channel with perfect acquisition of CSI to explore the system sum-rate capacity of a massive MIMO network. For user selection, we apply three algorithms, namely Semi-orthogonal user selection (SUS), Descending Order of SNR-based User Scheduling (DOSUS), and Random User Selection (RUS) algorithm. In all the user selection algorithms, the selection of Base Station (BS) antenna is based on the maximum Signal-to-Noise Ratio (SNR) to the selected users. Hence users are characterized by having both Small Scale Fading (SSF) due to slowly fading Rayleigh channel and Large-Scale Fading (LSF) due to distances from the base station. Further, we use linear precoding techniques, such as Zero Forcing (ZF), Minimum Mean Square Error (MMSE), and Maximum Ratio Transmission (MRT) to reduce interferences, thereby improving average system sum-rate capacity. Results using SUS, DOSUS, and RUS user selection algorithms with ZF, MMSE, and MRT precoding techniques are compared. We also analyzed and compared the computational complexity of all the three user selection algorithms. The computational complexities of the three algorithms that we achieved in this paper are O(1) for RUS and DOSUS, and O(M²N) for SUS which are less than the other conventional user selection methods.