Synthesis and properties analysis of char-reinforced Al–13.5Si–2.5Mg alloy composites

The re-evaluation of previous and existing methods in materials processing is becoming ever more critical because of processing and starting materials cost factors. A study on the synthesis and properties investigation of hypereutectic Al–13.5Si–2.5Mg alloy reinforced with carbon chars using coconut shell as the organic precursor has been carried out. The low-cost, double compaction solid-state technique was used. Reinforcing the hypereutectic alloy with coconut shell char particles (size:<140 m) at 2 vol % and consolidating by reaction sintering at 600 °C in vacuum for 15 min, followed by near net-shape compaction at 250 MPa, increased the hardness of the alloy 6% while reducing its strength (UTS) by only 3%. The use of palm kernel shell char as the dispersed phase was found to yield identical results. At 2 vol % char, the mechanical properties, sintered density and dimensional changes were optimally found to be suitable for lightweight anti-friction electromechanical applications. Attempts to reinforce the alloy with 2 vol % coconut shell chars activated in CO2 reduced its strength in the range of 19 to 26% at different burn-off percentages. This is attributed to the higher amount of oxide products formed during the activation process. At 600 °C, formation of the brittle Al4C3 phase in the different sintered composites containing activated and unactivated chars was identified by X-ray studies. © 1998 Chapman & Hall     

Electrical properties of ZnSe-CdS alloy films

Thin films of ZnSe _x CdS_1–x (t 0.6 m) over the entire range of x, were deposited on glass substrates at two temperatures, T _s (350 and 470 K) by vacuum evaporation. X-ray diffraction studies showed that all the films were polycrystalline in nature. Films prepared at 470 K were nearly stoichiometric. Grain size increased with substrate temperature, T _s. The electrical conductivity and Hall measurements were carried out by d.c. van der Pauw technique. Hall effect studies/hot probe test showed that all the films were of n-type conductivity. Hall mobility increased with T _s. In addition, mobilities increased with temperature in films of all compositions, indicating the dominance of grain-boundary scattering. Grain-boundary potentials were in range 0.03–0.06 eV.     

Helicobacter pylori does not migrate from the antrum to the corpus in response to omeprazole

BACKGROUND: Omeprazole is known to have an effect on Helicobacter pylori in vivo. One opinion is that H. pylori "migrates" from the antrum to the corpus in response to omeprazole therapy. METHODS: To determine whether H. pylori migrates in response to omeprazole, we assessed the presence of H. pylori in the antrum and corpus in duodenal ulcer patients receiving omeprazole for 4 wk. Culture and histological examination of antral biopsies (Genta stain) were performed before patients received omeprazole, at the end of therapy, and 4-6 wk later. The end points were presence or absence of H. pylori and the number of H. pylori colonies per biopsy. RESULTS: Seventy-two patients had H. pylori in both the antrum and corpus at entry and 4-6 wk after ending therapy. Three general patterns were prevalent at the end of omeprazole therapy: antrum- and corpus-positive (54%), antrum-negative and corpus-positive (24%), both antrum- and corpus-negative (21%), and one patient had antrum-positive with corpus-negative (1%). Evaluation of the number of colonies per biopsy in those who remained H. pylori-positive in both the antrum and corpus throughout showed that the number of H. pylori decreased in both the antrum and corpus during therapy (507 +/- 60 vs. 225 +/- 51, p < 0.01 and 415 +/- 58 vs. 290 +/- 46 0.1) for antrum and corpus, respectively, and tended to return to pre-therapy levels 4-6 wk later. The number of H. pylori in the corpus also decreased in the antrum-negative and corpus-positive group during therapy with omeprazole (433 +/- 87 vs. 185 +/- 61, p < 0.05). In most of the patients studied, the number of H. pylori in the corpus was less posttreatment than it was pretreatment. The decrease in H. pylori load was also reflected in the development of false-negative urea breath tests. CONCLUSIONS: Omeprazole is detrimental to H. pylori in both the antrum and the corpus; migration from the antrum to the corpus in response to omeprazole is a myth.     

Concept-based evidential reasoning for multimodal fusion in human–computer interaction

Considerable research has been done on using information from multiple modalities, like hands, facial gestures or speech, for better interaction between humans and computers, and many promising human–computer interfaces (HCI) have been developed in recent years. However, most of the current HCI systems have a few drawbacks: firstly, they are highly dependent on the performance of individual sensors. S econdly, the information fusion process from these sensors tends to ignore the semantic nature of the modalities, which may reinforce or clarify each other over time. Finally, they are not robust enough at representing the imprecise nature of human gestures, since individual gestures are highly ambiguous in themselves. In this paper, we propose an approach for the semantic fusion of different input modalities, based on transferable belief models. We show that this approach allows for a better representation of the ambiguity involved in recognizing gestures. Ambiguity is resolved by combining the beliefs of the individual sensors on the input information, to form new extended concepts, based on a pre-defined domain specific knowledge base, represented by conceptual graphs. We apply this technique to a multimodal system consisting of a hand gesture recognition sensor and a brain computing interface. It is shown that the technique can successfully combine individual gestures obtained from the two sensors, to form meaningful concepts and resolve ambiguity. The advantage of this approach is that it is robust even if one of the sensors is inefficient or has no input. Another important feature is its scalability, wherein more input modalities, like speech or facial gestures, can be easily integrated into the system at minimal cost, to form a comprehensive HCI interface.     

A new approach for generating efficient sample from market basket data

Classical data mining algorithms require expensive passes over the entire database to generate frequent items and hence to generate association rules. With the increase in the size of database, it is becoming very difficult to handle large amount of data for computation. One of the solutions to this problem is to generate sample from the database that acts as representative of the entire database for finding association rules in such a way that the distance of the sample from the complete database is minimal. Choosing correct sample that could represent data is not an easy task. Many algorithms have been proposed in the past. Some of them are computationally fast while others give better accuracy. In this paper, we present an algorithm for generating a sample from the database that can replace the entire database for generating association rules and is aimed at keeping a balance between accuracy and speed. The algorithm that is proposed takes into account the average number of small, medium and large 1-itemset in the database and average weight of the transactions to define threshold condition for the transactions. Set of transactions that satisfy the threshold condition is chosen as the representative for the entire database. The effectiveness of the proposed algorithm has been tested over several runs of database generated by IBM synthetic data generator. A vivid comparative performance evaluation of the proposed technique with the existing sampling techniques for comparing the accuracy and speed has also been carried out.     

Unsupervised strategies for shilling detection and robust collaborative filtering

Collaborative filtering systems are essentially social systems which base their recommendation on the judgment of a large number of people. However, like other social systems, they are also vulnerable to manipulation by malicious social elements. Lies and Propaganda may be spread by a malicious user who may have an interest in promoting an item, or downplaying the popularity of another one. By doing this systematically, with either multiple identities, or by involving more people, malicious user votes and profiles can be injected into a collaborative recommender system. This can significantly affect the robustness of a system or algorithm, as has been studied in previous work. While current detection algorithms are able to use certain characteristics of shilling profiles to detect them, they suffer from low precision, and require a large amount of training data. In this work, we provide an in-depth analysis of shilling profiles and describe new approaches to detect malicious collaborative filtering profiles. In particular, we exploit the similarity structure in shilling user profiles to separate them from normal user profiles using unsupervised dimensionality reduction. We present two detection algorithms; one based on PCA, while the other uses PLSA. Experimental results show a much improved detection precision over existing methods without the usage of additional training time required for supervised approaches. Finally, we present a novel and highly effective robust collaborative filtering algorithm which uses ideas presented in the detection algorithms using principal component analysis.     

Hybrid signal processing and machine intelligence techniques for detection,quantification and classification of power quality disturbances

This paper presents an advanced signal processing technique known as S-transform (ST) to detect and quantify various power quality (PQ) disturbances. ST is also utilized to extract some useful features of the disturbance signal. The excellent time–frequency resolution characteristic of the ST makes it an attractive candidate for analysis of power system disturbance signals. The number of features required in the proposed approach is less than that of the wavelet transform (WT) for identification of PQ disturbances. The features extracted by using ST are used to train a support vector machine (SVM) classifier for automatic classification of the PQ disturbances. Since the proposed methodology can reduce the features of disturbance signal to a great extent without losing its original property, it efficiently utilizes the memory space and computation time of the processor. Eleven types of PQ disturbances are considered for the classification purpose. The simulation results show that the combination of ST and SVM can effectively detect and classify different PQ disturbances.     

Bidirectional differential on-chip wave-pipelined serial interconnect with surfing

In the literature, surfing technique has been proposed for differential on-chip wave-pipelined serial interconnects with uniform repeaters (UR) and non-uniform repeaters to increase the data transfer rate for unidirectional schemes. In this paper, a novel bidirectional data transfer through the differential wave-pipelined serial interconnects with surfing for UR is proposed. A new circuit called ‘Bidirectional surfing inverter pair’ is proposed for differential wave-pipelined serial interconnects. The method of logical effort is used for the design of surfing circuits. To evaluate the efficiency of these techniques, 40 mm metal 4 interconnects using the proposed surfing techniques are implemented along with transmitter, receiver and delay locked loop in UMC 180 nm technology and their performances are studied through post layout simulations. The proposed bidirectional differential surfing scheme has a maximum data transfer rate of 2 Gb/s and has allowable jitter of 52 ps on both directions through the same interconnects.