Oxidation behavior of single-crystal Al2O3-fiber-reinforced Ni3Al-based composites

A series of single-crystal Al₂O₃-fiber-reinforced Ni3Al-based intermetallic matrix composites were fabricated by pressure casting. The matrices employed were binary Ni₃Al, Ni₃Al-0.5 at. pct Cr, and Ni₃Al-0.34 at. pct Zr. The development of microstructure upon oxidation in air at either 1100 °C or 1200 °C was investigated by optical, scanning, and transmission electron microscopy. In air-oxidized binary Ni₃Al, some of the fibers were fully or partially covered with a layer of oxide. A weak fiber/matrix bond in this system, which led to fiber debonding during composite processing, is believed to be responsible for the ingress of O into the composite and oxidation of the matrix in the debonded regions at the fiber/matrix interface. Addition of Cr to Ni₃Al resulted in an almost threefold increase in fiber/matrix bond strength. No oxidation of the interface was observed. A thick layer of oxide was formed around all the fibers when the composite was thermally cycled prior to isothermal annealing. Addition of Zr to Ni₃Al resulted in the formation of a layer of ZrO₂ on the surface of the fibers during composite processing. The ZrO₂ layer provided a fast path for the diffusion of O, which led to the formation of a rootlike oxide structure around the fibers. The rootlike structure consisted of a network of Al₂O₃-covered ZrO₂.     

The IFR/DFR property of the forward recurrence-time distribution

When a failure or replacement process is modeled as a renewal process, the residual life of the unit in use at a given time is generally referred to as the forward recurrence time (RT). Distributional properties of this random variable are critically important in many applications. This paper investigates the extent to which the failure-rate function monotonicity of a life distribution is inherited by the forward RT distribution at time s of its renewal process. For DFR life distributions, the forward RT distribution is also DFR for every s⩾0. However, the corresponding property does not necessarily hold for IFR life distributions. The forward RT distribution is IFR in the limit as s→0 and as s→∞. For IFR Weibull life distributions, we demonstrate numerically that the forward RT distribution is IFR for small s. As s is increased, it alternates between being IFR and non-IFR in an interesting cyclical pattern, and remains IFR beyond a large enough s     

Prediction of suspended sediment concentration from water quality variables

This study investigates use of water quality (WQ) variables, namely total chromium concentration, total iron concentration, and turbidity for predicting suspended sediment concentration (SSC). For this purpose, the artificial neural networks (ANNs) and regression analysis (RA) models are employed. Seven different RA models are constructed, considering the functional relation between measured WQ variables and SSC. The WQ and SSC data are fortnightly obtained from six monitoring stations, located on the stream Harsit, Eastern Black Sea Basin, Turkey. A total of 132 water samples are collected from April 2009 to February 2010. Model prediction results reveal that ANN is able to predict SSC from WQ data, with mean absolute error (MAE) of 10.30 mg/L and root mean square error (RMSE) of 13.06 mg/L. Among seven RA models, the best one, which has the form including all independent parameters, produces results comparable to those of ANN, with MAE = 14.28 mg/L and RMSE = 15.35 mg/L. The sensitivity analysis results reveal that the most effective parameter on the SSC is total chromium concentration. These results have time- and cost-saving implications.     

Salt and pepper noise filtering with fuzzy-cellular automata

A new image denoising algorithm is proposed to restore digital images corrupted by impulse noise. It is based on two dimensional cellular automata (CA) with the help of fuzzy logic theory. The algorithm describes a local fuzzy transition rule which gives a membership value to the corrupted pixel neighborhood and assigns next state value as a central pixel value. The proposed method removes the noise effectively even at noise level as high as 90%. Extensive simulations show that the proposed algorithm provides better performance than many of the existing filters in terms of noise suppression and detail preservation. Also, qualitative and quantitative measures of the image produce better results on different images compared with the other algorithms.     

A comprehensive study on mid-level representation and ensemble learning for emotional analysis of video material

Multimedia Tools and Applications - In today’s society where audio-visual content such as professionally edited and user-generated videos is ubiquitous, automatic analysis of this content is...     

Multi-domain collaborative exploration mechanisms for query expansion in an agent-based filtering framework

Novice users often do not have enough domain knowledge to create good queries for searching information on-line. To help alleviate the situation, exploration techniques have been used to increase the diversity of the search results so that not only those explicitly asked will be returned, but also those potentially relevant ones will be returned too. Most existing approaches, such as collaborative filtering, do not allow the level of exploration to be controlled. Consequently, the search results can be very different from what is expected. We propose an exploration strategy that performs intelligent query processing by first searching usable old queries, and then utilising them to adapt the current query, with the hope that the adapted query will be more relevant to the user’s areas of interest. We applied the proposed strategy to the implementation of a personal information assistant (PIA) set up for user evaluation for 3 months. The experimental results showed that the proposed exploration method outperformed collaborative filtering, and mutation and crossover methods by around 25% in terms of the elimination of off-topic results.     

Comparison of OR and AI methods in discrete manufacturing using fuzzy logic

Since 1950s the techniques of Operations Research (OR) and Optimization have been utilized to increase the efficiency of the production systems. With the widespread use of computers, it has even become easier to deal with industrial problems. However the complexity of the problems still reveals the difficulty in providing solutions. The use of artificial intelligence (AI) seems to attract the attention of the researcher to overcome to the difficulties. This has already been realized with several successful applications. In this study, the use of AI and OR techniques is compared using fuzzy logic. The progress of manufacturing systems, characteristics of production processes, system managements and system behavior are taken into account. The study is focussed on only discrete manufacturing.     

Closed-loop stimulation of hypoglossal nerve in a dog model of upper airway obstruction

Electrical stimulation of upper airway (UAW) muscles has been under investigation as a treatment method for obstructive sleep apnea (OSA). Particular attention has been given to the electrical activation of the genioglossal muscle, either directly or via the stimulation of the hypoglossal nerve (HG), since the genioglossus is the main tongue protrusor muscle. Regardless of the stimulation site or method, an implantable electrical stimulation device for OSA patients will require a reliable method for detection of obstructive breaths to apply the stimulation when needed. In this paper, we test the hypothesis that the activity of the HG nerve can be used as a feedback signal for closed-loop stimulation of the HG nerve in an animal model of UAW obstruction where a force is applied on the submental region to physically narrow the airways. As an advantage, the method uses a single electrode for both recording and stimulation of the HG nerve. Simple linear filtering techniques were found to be adequate for producing the trigger signal for the electrical stimulation from the HG recordings. Esophageal pressure, which was used to estimate the size of the UAW passage, returned to the preloading values during closed-loop stimulation of the HG nerve. The data demonstrate the feasibility of the closed-loop stimulation of the HG nerve using its activity as the feedback signal.     

FPGA Based Implementation and Comparison of Beamformers for CDMA2000

For the integration of smart antennas into third generation code division multiple access (CDMA) base stations, it still remains as a challenging task to implement smart antenna algorithms on programmable processors. In this paper, we study implementations of some CDMA compatible beamforming algorithms, namely least mean square (LMS), constant modulus (CM), and space code correlator (SCC) algorithms, using Xilinx??s Virtex family FPGAs. This study exhibits feasibility of implementing even simple, practical, and computationally small algorithms based on today??s most powerful FPGA technologies. 16 and 32 bits floating point implementations of the algorithms are investigated using both Virtex II and Virtex IV FPGAs. CDMA2000 reverse link baseband signal format is used in the signal modeling. Randomly changing fading and Direction-of-arrivals (DOAs) of multipaths are considered as a channel condition. The implementation results in terms of beamforming accuracy, FPGA resource utilization, weight vector computation time, and DOA estimation error are presented. Beamformer weight vectors using LMS and CM can be computed within less than 20 ??s on Virtex II FPGA and 10 ??s on Virtex IV FPGA, and using SCC it can be achieved within less than 22 ??s on Virtex IV FPGA. These results show that FPGAs provide approximately 500 times faster speed in implementations than our previous work with DSPs.