Itemset trees for targeted association querying

Association mining techniques search for groups of frequently co-occurring items in a market-basket type of data and turn these groups into business-oriented rules. Previous research has focused predominantly on how to obtain exhaustive lists of such associations. However, users often prefer a quick response to targeted queries. For instance, they may want to learn about the buying habits of customers that frequently purchase cereals and fruits. To expedite the processing of such queries, we propose an approach that converts the market-basket database into an itemset tree. Experiments indicate that the targeted queries are answered in a time that is roughly linear in the number of market baskets, N. Also, the construction of the itemset tree has O(N) space and time requirements. Some useful theoretical properties are proven.     

Finite element analyses of repaired articular surfaces.

The response to a compressive load of a repaired cartilage surface, consisting of full-thickness repair tissue adjacent to normal cartilage, was predicted by the u-p finite element method and compared to that of a normal cartilage surface under the same loading conditions. By individually varying the aggregate modulus, permeability and Poisson's ratio for the repair tissue, analyses were performed to assess the contributions of each to the changes in mechanical behaviour. In comparing the repaired to normal surfaces, the presence of a softer repair tissue resulted in increased axial and decreased radial deformations at any given time point, while a repaired surface with an increased permeability compressed more easily due to the increased fluid flow and caused equilibrium to occur sooner. For smaller Poisson's ratio, the axial deformation was not different from normal if the aggregate modulus was the same as normal; however, the radial expansion was reduced as the repair tissue experienced a larger volume change. These results indicate that the presence of repair tissue in a joint surface can have a strong influence on the mechanical behaviour of the surface.     

An adaptive analog continuous-time CMOS biquadratic filter

An adaptive analog continuous-time biquadratic filter is realized in a 2-μm digital CMOS process for operation at 300 kHz. The biquad implements the notch, bandpass and low-pass transfer functions. The only parameter adapted is the resonant frequency of the biquad, which is identical to the notch frequency and the bandpass center frequency. The update method is based on a least-means-square algorithm which adapts the notch frequency to minimize the power at the notch filter output. The actual update is modified to reduce the circuit complexity to one biquad and one correlator. When the filter is tracking a sinusoid, this update generates a ripple-free gradient that decreases tracking error. Applications include phase-frequency detectors, FM demodulators (linear and frequency shift keying), clock extractors, and frequency acquisition aids for phase-locked loops and Costas loops. Measured results from experimental prototypes are presented. Nonidealities of an all-analog implementation are discussed, along with suggestions to improve performance     

Can Robots Manifest Personality?: An Empirical Test of Personality Recognition,Social Responses,and Social Presence in Human–Robot Interaction

Personality is an essential feature for creating socially interactive robots. Studies on this dimension will facilitate enhanced human–robot interaction (HRI). Using AIBO, a social robotic pet developed by Sony, we examined the issue of personality in HRI. In this gender-balanced 2 (AIBO personality: introvert vs. extrovert) by 2 (participant personality: introvert vs. extrovert) between-subject experiment (N = 48), we found that participants could accurately recognize a robot's personality based on its verbal and nonverbal behaviors. In addition, various complementarity attraction effects were found in HRI. Participants enjoyed interacting with a robot more when the robot's personality was complementary to their own personalities than when the robot's personality was similar to their own personalities. The same complementarity attraction effect was found in participants' evaluation of the robot's intelligence and social attraction. Participants' feelings of social presence during the interaction were a significant mediator for the complementarity attraction effects observed. Practical and theoretical implications of the current study for the design of social robots and the study of HRI were discussed.     

Zeolite Formation in Class F Fly Ash Blended Cement Pastes

Zeolite formation in Class F fly ash blended cement pastes is under investigation. A Na–P type zeolite and Zeolite Y were synthesized from Class F fly ash and NaOH solution after 2 days of aging at room temperature and 6 days of curing at 80°C. However, no zeolites formed when KOH was used. In additional experiments, a Na–P type zeolite, Zeolite Y, and chabazite developed in cement pastes blended with Class F fly ash and NaOH solution which had been aged 2 days at room temperature and then cured 6 days at temperatures ranging from room temperature to 90°C. Seeding the pastes with natural zeolites was also investigated.     

High catalytic activity of PdOx/MnO2 for CO oxidation and importance of oxidation state of Mn

PdO_x/MnO₂ has been examined as a catalyst for CO oxidation using a conventional flow reactor at reaction temperatures between 50 and 150°C. In the reaction conditions of GHSV (gashourlyspacevelocity) of 1.22 × 10⁵/h and CO concentration of 2000 ppm, PdO_x/MnO₂ showed higher catalytic activity compared with PdO_x/Mn₂O₃, which had been previously reported as an effective catalyst due to the cooperative action of Pd and Mn₂O₃ for this reaction. The reason for higher activity of PdO_x/MnO₂ than PdO_x/Mn₂O₃ has been investigated using TPR (temperatureprogrammed reduction) and XPS studies. TPR showed that PdO_x/MnO₂ could be reduced by CO at much lower temperature than PdO_x/Mn₂O₃. During the experiment of reduction and oxidation, XPS showed that the valence of Mn in the PdO_x/MnO₂ was between 4+ and 3+, which is higher than that of Mn in the PdO_x/Mn₂O₃ catalyst of which the valence has been reported to be between 3+ and 2+. It is known that in this catalyst system the support supplies oxygen onto Pd, where the oxidation occurs with adsorbed CO, and the ability of the support to provide oxygen improves the performance of the catalyst. Therefore, it was concluded that the readiness of MnO₂ to be reduced with maintaining a higher oxidation state showed higher CO oxidation activity than Mn₂O₃ as support for PdO_x.     

Absorption of NO x in packed column (I)

A mathematical model for an absorption of nitrogen oxides into water in packed column was developed based on the mass-transfer coefficient in packed column and the chemical reaction accompanying NO _x absorption produces HNO₃ and HNO₂ in the liquid phase. The subsequent dissociation of HNO₂ in the liquid-phase results in the formation of HNO₃ and NO gas, and then this NO gas follows to be oxidized by O₂ in air. The important factors influenced on the absorption of NO _x are the oxidation state of NO gas and the partial pressure of nitrogen oxides in the gas. The efficiency of NO _x absorption increases with the increase of the partial pressure of NO _x . The most critical value for using the model is the constant of .The selection of 11×10⁻⁴kg·mol/atm·m²·sec for resonable for this model.     

Room-Temperature-Processable Highly Reliable Resistive Switching Memory with Reconfigurability for Neuromorphic Computing and Ultrasonic Tissue Classification

Reversible metal-filamentary mechanism has been widely investigated to design an analog resistive switching memory (RSM) for neuromorphic hardware-implementation. However, uncontrollable filament-formation, inducing its reliability issues, has been a fundamental challenge. Here, an analog RSM with 3D ion transport channels that can provide unprecedentedly high reliability and robustness is demonstrated. This architecture is realized by a laser-assisted photo-thermochemical process, compatible with the back-end-of-line process and even applicable to a flexible format. These superior characteristics also lead to the proposal of a practical adaptive learning rule for hardware neural networks that can significantly simplify the voltage pulse application methodology even with high computing accuracy. A neural network, which can perform the biological tissue classification task using the ultrasound signals, is designed, and the simulation results confirm that this practical adaptive learning rule is efficient enough to classify these weak and complicated signals with high accuracy (97%). Furthermore, the proposed RSM can work as a diffusive-memristor at the opposite voltage polarity, exhibiting extremely stable threshold switching characteristics. In this mode, several crucial operations in biological nervous systems, such as Ca²⁺ dynamics and nonlinear integrate-and-fire functions of neurons, are successfully emulated. This reconfigurability is also exceedingly beneficial for decreasing the complexity of systems—requiring both drift- and diffusive-memristors.