Linear and logarithmic capacities in associative neural networks

A model of associate memory incorporating global linearity and pointwise nonlinearities in a state space of n-dimensional binary vectors is considered. Attention is focused on the ability to store a prescribed set of state vectors as attractors within the model. Within the framework of such associative nets, a specific strategy for information storage that utilizes the spectrum of a linear operator is considered in some detail. Comparisons are made between this spectral strategy and a prior scheme that utilizes the sum of Kronecker outer products of the prescribed set of state vectors, which are to function nominally as memories. The storage capacity of the spectral strategy is linear in n (the dimension of the state space under consideration), whereas an asymptotic result of n/4 log n holds for the storage capacity of the outer product scheme. Computer-simulated results show that the spectral strategy stores information more efficiently. The preprocessing costs incurred in the two algorithms are estimated, and recursive strategies are developed for their computation     

The science of making ERORS: what error tolerance implies forcapacity in neural networks

Discusses the development of formal protocols for handling error tolerance which allow a precise determination of the computational gains that may be expected. The error protocols are illustrated in the framework of a densely interconnected neural network architecture (with associative memory the putative application), and rigorous calculations of capacity ar shown. Explicit capacities are also derived for the case of feedforward neural network configurations     

Assessment of central nervous system involvement in gambiense trypanosomiasis: value of the cerebro-spinal white cell count

OBJECTIVE: To assess, in a clinical setting, the comparative values of conventional criteria used in the diagnosis of central nervous system (CNS) involvement in Trypanosoma brucei gambiense sleeping sickness: white cell count (WCC) in cerebrospinal fluid (CSF) > 5 x 10(6) cells/l; total protein concentration in CSF > 40 mg/100 ml); evidence of trypanosomes in CSF following double centrifugation (DC). METHOD: In vitro culture of CSF was used as the gold standard. RESULTS: The study showed that WCC is, by itself, as sensitive for the diagnosis of the CNS involvement as the usually recommended combination of three conventional criteria. The specificity of WCC is improved while the sensitivity is reduced when the cut-off point is set at a higher value (WCC > 10 X 10(6)/l). CONCLUSION: In poorly equipped laboratories, the diagnosis of CNS involvement in patients with confirmed systemic infection should be based only on the WCC. However, a pilot study is needed to assess the feasibility and reliability of the WCC handled by 'front line' personnel, for different cut-off values.     

Formal Techniques for Analysing Scenarios using Message Sequence Charts

This paper describes light-weight formal techniques based on Message Sequence Charts (MSCs) for capturing and validating early requirements and design. Our focus is on ease of use in specifying, simulating and validating scenarios, and checking their desired properties efficiently. We discuss how the formalism of High Level Message Sequence Charts (HMSCs or MSC'96), can be used to capture scenarios in use cases, thus enabling the use of tools for analysing them. We then present two formal semantics for HMSCs – an intuitive linear time semantics based on runs, and an operational semantics in terms of a labelled transition system. Next we present a way of describing desired properties of use case scenarios using templates, for validating scenarios with respect to informal requirements. The correctness properties of a collection of MSCs can then be established by efficient algorithms for finding paths in a directed graph representing the precedence relation on the events of the MSCs. We have implemented the operational semantics and the verification algorithms in the form of a simulation and verification tool for analysing scenarios.     

Surface treatments for pistons and their effect on engine performance

Surface treatment alters the frictional behaviour of pistons in I.C. engines and can be used to improve engine performance. Surface treatments applied to aluminium alloy pistons of a high speed diesel engine and their effect on the engine performance are described. Certain piston surface treatments improve engine performance and also reduce the run-in period.     

Effectiveness of Bio-Activated Carbon Filtration and Ozonation on Control of Halo Acetic Acids Formation during Chlorination of Ganga River Water at Kanpur,India

ABSTRACT

Chlorinated water from River Ganga is the main source of drinking water in Kanpur, India. But, this water contains a significant amount of disinfection by-products (DBPs) that include haloacetic acids (HAAs) as a major contributor, which pose a carcinogenic risk on long-term ingestion. Therefore, in order to control HAAs formation, different combinations of ozonation and bio-activated carbon filtration (BAC-filtration) were studied. The results elucidate that slight ozonation followed by BAC-filtration proved effective in reducing (75.8%) HAAs formation and meet the USEPA drinking standards. These findings open a path to explore cost-effective treatment techniques in continuous mode for safe drinking water.