The prospects of non-volatile phase-change RAM

Phase-change read-and-write memory (PRAM) is a promising memory that can solve the problems of conventional memory—scalability, read/write speed, and reliability. We will review the opportunities and technical challenges of PRAM. The most important challenge of PRAM is the reduction of the writing current. Various approaches to reduce the writing current will be reviewed and the prospects of PRAM are discussed.     

Feature-based classifiers for design optimization

We present a design optimization method for systems with high-dimensional parameter spaces using inductive decision trees. The essential idea is to map designs into a relatively low-dimensional feature space, and to derive a classifier to search for high-performing design alternatives within this space. Unlike learning classifier systems that were pioneered by Holland and Goldberg, classifiers defined by inductive decision trees were not originally developed for design optimization. In this paper, we explore modifications to such classifiers to make them more effective in the optimization problem. We expand the notions of feature space, generalize the tree construction heuristic beyond the original information-theoretic definitions, increase the reliance on domain expertise, and facilitate the transfer of design knowledge between related systems. There is a relatively small but rapidly growing body of work in the use of inductive trees for engineering design; the method presented herein is complementary to this research effort.     

Organizational determinants of IT adoption in the pharmaceutical distribution sector

The aim of this paper is to propose new organizational factors that might explain the differences in the extent and the speed of IT adoption. With this in mind, we carried out an analysis of 16 cases in the pharmaceutical distribution sector in Spain. The results indicate that there are certain intangible assets that favour the introduction and development of IT. Among these are a frank and fluid communication between departments and members of the organization, low levels of conflict, the explicit support of top management towards IT adoption and learning and creative skills of IT-staff. In addition to these factors, we found others that we propose as catalysts of IT adoption. Among these we might mention the special relationship between the member-clients and the company in the case of cooperative firms.     

Learning-based dynamic coupling of discrete and continuous trackers

We present a data-driven dynamic coupling between discrete and continuous methods for tracking objects of high dofs, which overcomes the limitations of previous techniques. In our approach, two trackers work in parallel, and the coupling between them is based on the tracking error. We use a model-based continuous method to achieve accurate results and, in cases of failure, we re-initialize the model using our discrete tracker. This method maintains the accuracy of a more tightly coupled system, while increasing its efficiency. At any given frame, our discrete tracker uses the current and several previous frames to search into a database for the best matching solution. For improved robustness, object configuration sequences, rather than single configurations, are stored in the database. We apply our framework to the problem of 3D hand tracking from image sequences and the discrimination between fingerspelling and continuous signs in American Sign Language.     

Two-tier architecture for unconstrained handwritten character recognition

In this paper, we propose an approach that combines the unsupervised and supervised learning techniques for unconstrained handwritten numeral recognition. This approach uses the Kohonen self-organizing neural network for data classification in the first stage and the learning vector quantization (LVQ) model in the second stage to improve classification accuracy. The combined architecture performs better than the Kohonen self-organizing map alone. In the proposed approach, the collection of centroids at different phases of training plays a vital role in the performance of the recognition system. Four experiments have been conducted and experimental results show that the collection of centroids in the middle of the training gives high performance in terms of speed and accuracy. The systems developed also resolve the confusion between handwritten numerals.     

Efficient Management of Persistent Knowledge

Although computer speed has steadily increased and memory is getting cheaper, the need for storage managers to deal efficiently with applications that cannot be held into main memory is vital. Dealing with large quantities of clauses implies the use of persistent knowledge and thus, indexing methods are essential to access efficiently the subset of clauses relevant to answering a query. We introduce PerKMan, a storage manager that uses G-trees, and aims at efficient manipulation of large amounts of persistent knowledge. PerKMan may be connected to Prolog systems that offer an external C language interface. As well as the fact that the storage manager allows different arguments of a predicate to share a common index dimension in a novel manner, it indexes rules and facts in the same manner. PerKMan handles compound terms efficiently and its data structures adapt their shape to large dynamic volumes of clauses, no matter what the distribution. The storage manager achieves fast clause retrieval and reasonable use of disk space.     

Development of nano indium tin oxide (ITO) grains by alkaline hydrolysis of In(III) and Sn(IV) salts

Indium tin oxide (ITO) nano powders of different compositions (In: Sn = 90: 10, 70: 30 and 50: 50) were prepared by heat treatment (300-450°C) of mixed hydroxides of In(III) and Sn(IV). The hydroxides were obtained by the reaction of aq. NH₃ with mixed aq. solutions of In(NO₃)₃ and SnCl₄. FTIR and TG/DTA studies revealed that powders existed as In(OH)₃H₂O—SnO₃H₂H₂O in the solid state and then they transformed to In₂O₃—SnO₂ via some metastable intermediates after 300°C. Cubic phase of In₂O₃ was identified by XRD for the oxides up to 30% of Sn. Particle size measurements of the solid dispersed in acetone and SEM study for microstructure showed that the oxides were in the nano range (55-75 nm) whereas the size range determined from Debye-Scherrer equation were 11–24 nm.