TasteMiner: Mining partial tastes for neighbor-based collaborative filtering

Neighbor-based collaborative filtering is one of the most practical recommendation approaches that is renowned because of its simplicity and explanation. However, the big limitation is its high computational complexity. It is demonstrated that clustering-based algorithms, that restrict the neighborhood space, speed up the recommendation process at the price of lower accuracy. We propose a new algorithm, called TasteMiner that efficiently learns partial users taste to restrict the neighborhood space. We frame TasteMiner as a method for neighborhood collaborative filtering, and show its effectiveness compared to previous algorithms     

Modeling and comparing CMOS implementations of the C-element

Various applications have demonstrated that asynchronous circuits have great potential for energy-efficient and high-performance design. One of the primitives used in asynchronous control circuits is the C-element. Analytical delay and energy models are presented and applied to the most popular complementary metal-oxide-semiconductor (CMOS) implementations of the C-element. Optimization of these implementations are discussed. The implementations are also compared using simulations. The simulation results are in good agreement with the analytical predictions     

A thermometric study of the dissolution of some CuZn alloys in acid solutions

The dissolution of Cu and Zn, and of three CuZn alloys in solutions of different concentrations of HNO₃ was studied by the thermometric technique. The variation of ΔT (i.e. T_m ? T_i) and the reaction number (R.N.) with the concentration of the attacking acid followed the relations:

$\Delta T=A_1(C?C_{\mathit{0}})$

and

$R.N.=A_2{\mathit{C}}_n,$

successively. Based on the values of the constants A₁, C_o, A₂ and n, the rate of dissolution of the different materials was found to increase in the order: Cu < Alloy I (70.5%Cu) < Alloy III (58.00%Cu) < Alloy II (62.00%Cu) < Zn.A break was noted in the thermometric curves of Alloy I. This was due to the primary attack on the Zn-component of the alloy, and was confirmed by studying the effect of the initial temperature, T_i, and the area/volume ratio on the shape of the curves, as well as by chemically analysing the corroding solution for both Cu²⁺ and Zn²⁺.The effect of the concentration of HCl, H₂SO₄, H₃PO₄ and of their salts on the reaction number of the alloys in 4N HNO₃ was examined in detail. The adsorption of the foreign acid anion on the metal surface retarded dissolution. Inhibition increased in the succession: Cl^? < HSO₄^? < H₃PO₄^?.The alloys were not affected by cold 4N HCl, H₂SO₄ or H₃PO₄. Attack could be initiated in the case of the first two acids through the addition of KNO₃. The thermometric curves were characterized by long incubation periods, by sharp temperature maxima and by the rapid decrease of temperature thereafter. This supported the conclusion that attack was of the pitting rather than of the general type. Because of stronger anion adsorption, attack in 4N H₂SO₄ was much lower than in 4N HCl. No attack was recorded in 4N H₃PO₄.Parallelism between corrosion assessment by the thermometric technique and by the weight loss method was established.     

Parametric testing statistical hypotheses for fuzzy random variables

In this paper, a method is proposed for testing statistical hypotheses about the fuzzy parameter of the underlying parametric population. In this approach, using definition of fuzzy random variables, the concept of the power of test and p value is extended to the fuzzy power and fuzzy p value. To do this, the concepts of fuzzy p value have been defined using the \(\alpha \)-optimistic values of the fuzzy observations and fuzzy parameters. This paper also develop the concepts of fuzzy type-I, fuzzy type-II errors and fuzzy power for the proposed hypothesis tests. To make decision as a fuzzy test, a well-known index is employed to compare the observed fuzzy p value and a given significance value. The result provides a fuzzy test function which leads to some degrees to accept or to reject the null hypothesis. As an application of the proposed method, we focus on the normal fuzzy random variable to investigate hypotheses about the related fuzzy parameters. An applied example is provided throughout the paper clarifying the discussions made in this paper.     

Efficient Numerical Scheme for Solving Large System of Nonlinear Equations

A fifth-order family of an iterative method for solving systems of nonlinear equations and highly nonlinear boundary value problems has been developed in this paper. Convergence analysis demonstrates that the local order of convergence of the numerical method is five. The computer algebra system CAS-Maple, Mathematica, or MATLAB was the primary tool for dealing with difficult problems since it allows for the handling and manipulation of complex mathematical equations and other mathematical objects. Several numerical examples are provided to demonstrate the properties of the proposed rapidly convergent algorithms. A dynamic evaluation of the presented methods is also presented utilizing basins of attraction to analyze their convergence behavior. Aside from visualizing iterative processes, this methodology provides useful information on iterations, such as the number of diverging-converging points and the average number of iterations as a function of initial points. Solving numerous highly nonlinear boundary value problems and large nonlinear systems of equations of higher dimensions demonstrate the performance, efficiency, precision, and applicability of a newly presented technique.     

Simple fabrication of an uncooled Al/SiO2 microcantilever IR detector based on bulk micromachining

A simple microfabrication process to make an uncooled aluminum/silicon dioxide bi-material microcantilever infrared (IR) detector using silicon bulk micromachining technology is presented in this work. This detector is based on high banding of the microcantilever due to the large dissimilar in thermal expansion coefficients between the two materials. It consists of a 1 μm SiO₂ layer deposited by 200 nm thin Al layer. Since no sacrificial layer is used in this process, complexity related to releasing sacrificial layer is avoided. Moreover Al is protected in Si etchant using dual-doped tetramethyl ammonium hydroxide. The other advantage of this process is that only three masks are used with four photolithography process. Thermal and thermal mechanical behaviors of this structure are obtained using finite element analysis, and the maximum temperature and displacement at the end of cantilever at 100 pW/μm² absorbed IR power density on top surface are 7.82°K and 1.924 μm, respectively.     

Nanoscale Optoregulation of Neural Stem Cell Differentiation by Intracellular Alteration of Redox Balance

Regulation of stem cell (SC) fate, a decision between self‐renewal and differentiation, is of immense importance in regenerative medicine and has been proven to be a powerful stimulus regulating many cell functions influencing the SC fate. This study uses triphenylphosphonium‐functionalized gold nanoparticles (TPP‐AuNPs) to explore the interplay of intracellular electromagnetic (EM) exposure and the SC fate. Localized EM waves are generated inside neural stem cells (NSCs) to stimulate TPP‐AuNPs (AuNPs), targeting the mitochondria through inducing reactive oxygen species and differentiating these cells into neurons. Following laser irradiation of TPP‐AuNPs‐transfected NSCs, their differentiation to neurons is monitored by tracing the relevant markers both at the genetic and protein levels. The electrophysiology technique is further used to examine the functionality of neurons. The results confirm that TPP‐AuNPs subjected to electromotive forces have the potential to regulate cellular fate, although further investigations are still required to shed light on the mechanisms underlying the interaction of EM‐stimulated TPP‐AuNPs on cellular fate to design highly adjustable cell differentiation and reprogramming methods.     

Efficient desulfurization of fuel with functionalized mesoporous carbon CMK-3-O and comparison its performance with mesoporous carbon CMK-3

In this work, a functionalized mesoporous carbon (CMK-3-O) was synthesized after oxidation with nitric acid and was used to adsorb dibenzothiophene (DBT) from model oil for the first time. Then, its performance was compared with that of CMK-3. The functionalized mesoporous carbon, CMK-3-O, showed better a capacitance performance for DBT adsorption than that of CMK-3. The maximum adsorption capacity was obtained for functionalized mesoporous carbon at optimum conditions with 6 M HNO₃ aqueous solution and 30 min contact time. The physical and structural properties of CMK-3-O and CMK-3 were investigated with X-ray diffraction method (XRD), N₂ adsorption–desorption isotherm, FT-IR, and elemental analysis (CHNO). Results of the elemental analysis showed that the oxygen and nitrogen content has increased and the carbon content has decreased through oxidation treatment. The effects of various factors on the adsorption process (such as temperature, amount of adsorbent, contact time, and concentration) of DBT were studied. CMK-3-O showed a maximum adsorption capacity of 86.96 mg DBT g^?1 of CMK-3-O at optimized conditions (temperature, 25°C; adsorbent dosage, 20 g L^?1; contact time, 60 min), which was a higher adsorption capacity of that observed for CMK-3 (57.47 mg DBT g^?1 of CMK-3). Kinetic studies have revealed that the adsorption of DBT can be described by a pseudo-second-order rate equation. Equilibrium data showed that adsorption process was best represented by the Langmuir model. The results also illustrated the fact that the regenerated adsorbent afforded 64.3% of the initial adsorption capacity after the two regeneration cycles.     

Supervised classification of spam emails with natural language stylometry

Email spam is one of the biggest threats to today’s Internet. To deal with this threat, there are long-established measures like supervised anti-spam filters. In this paper, we report the development and evaluation of sentinel—an anti-spam filter based on natural language and stylometry attributes. The performance of the filter is evaluated not only on non-personalized emails (i.e., emails collected randomly) but also on personalized emails (i.e., emails collected from particular individuals). Among the non-personalized datasets are CSDMC2010, SpamAssassin, and LingSpam, while the Enron-Spam collection comprises personalized emails. The proposed filter extracts natural language attributes from email text that are closely related to writer stylometry and generate classifiers using multiple learning algorithms. Experimental outcomes show that classifiers generated by meta-learning algorithms such as adaboostm1 and bagging are the best, performing equally well and surpassing the performance of a number of filters proposed in previous studies, while a random forest generated classifier is a close second. On the other hand, the performance of classifiers using support vector machine and Naïve Bayes is not satisfactory. In addition, we find much improved results on personalized emails and mixed results on non-personalized emails.