Purpose: The research aims to identify the incentives that play an important role in the evolution of e-government in Greece at local scale and its actual development level. It also investigates the factors and the perceived barriers that affect the development of local egovernment in Greek Municipalities, as well as the benefits they derive from it. Design/Methodology/Approach: The research is based on a survey that was conducted through a questionnaire to all 325 Municipalities of the country and includes data from 109 Municipalities that participated in the quantitative approach. Findings: While e-government is spread at a relatively satisfactory level, it appears that only a few Municipalities are performing well. Results highlight also the two main incentives that motivate Municipalities to adopt e-government: The first is the improvement of the efficiency of information exchange with the external environment and the second is managing internal issues-relationships in conjunction with the existence of prominent IT departments. Amongst the main factors that affect e-government adoption by Local authorities, budgetary constraints stand out, while the lack of personnel specialized in Information Technologies is identified as common obstacle. Practical Implications: Findings suggest that an integrated approach to e-government is needed in order to enable organizations to minimize failures and to overcome barriers and counter risks. The capacity to align e-government applications with the increasing and evolving needs and requirements of the citizens is the key to optimizing the benefits of e-Government at local scale.

An aim of this paper is to propose a layered dynamic autwwiociative memory which treats binary patterns as input/output and consists of a (multi-)layered network trained by the backpropagation and a simple feedback from output to input. This simple architecture, auto-encoder type fegdforward nekwork with feedback dynamics, works as an extended version of auto-associative memory, and overcomes poor ability of auto-encoder for recalling a learned pattern. It also solves two critical problems of conventional correlation type associative models: crosstalk noise elimination and multiple-match resolution.In this paper, we show that decision hyperplanes, which are formed in a multilayer feedforward network by means of the backpropagation or LMS ( Least Mean Squared ) learning algorithm, characterize the performance of the proposed model. Abstract: The effects of mapping an ensemble of vectors, using an external coding sequence, upon the retrieval efficiency of such an ensemble in a neural networks model are studied. Computer simulations show an increase in capacity and in the retrieval efficiency by using such a coding. Significant improvements were obtained by using a coded concatenation procedure upon ensembles of highly correlative vectors. Abstract AUTOASSOCIATIVE MEMORY WITH ADJUSTABLE BEHAVIOR Mmfq Rsshid Microelectornic and Computer Tkhnology Corp. Austin, Texar '18759.6509 35M) Weat Balcones Center Dr.N e d networks with high-order interactions only has been shown to be sufficient to provide satisfactory amctivity to the stored patterns and error corrections. Such interactions inmase the storage capacity of the networks and allow to solve a class of problems which were intractable with standad networks. In this paper we analyze the capacity of these higher order networks by the statistical method and show that why the probability of the Abstract We describe an autoassociative high capacity neural network memory architecture based on competitive learning mechanism. This network uses a modified version of ART 1 dynamics and inherits some of its desirable properties. It has a tunable error correction capability and well behaved basins of attraction, which are independent of the size of the network. The dynamic states of neurOnS active and passive can always be chosen with Probability 0.5 each.adjustment of stored vectors according to the idiosyncracies of a particular input environment is another notable feature of this architecture, especially in the absence of a complete knowledge of the nature of the input environment. 11-571

BackgroundValidated, clinically meaningful outcome measures should be used to detect clinically relevant effects of treatments. Since the clinical heterogeneity in mitochondrial disorders is extremely wide, the selection and validation of outcome measures is challenging. Espe-cially for children, whom are developing and growing and even have a larger phenotypic heterogeneity compared to adults, this challenge has so far resulted in a lack of val-idated outcome measures. Gait analysis is an emerging method to quantify subtle changes in walking patterns of adults with neurological disorders and can provide in-sight in the effects of a therapeutic intervention. Based on the results of a validation study in m.3243A>G carriers, we included gait quantification as the primary outcome measure for the adult randomised, placebo-controlled, cross-over, phase 2 trial performed in this population in our centre (the KHENERGY trial). We hypothesise that gait analysis is also a feasible and reliable outcome measure for intervention studies in ambulatory children with mi-tochondrial disease.MethodsThe aim of this study was to select the opti-mal protocol to quantify gait patterns with the Gaitrite in paediatric mitochondrial patients, comparing a normal walking protocol and a post-exercise protocol. Ambula-tory children with a genetically confirmed mitochondrial disease are asked to walk across the Gaitrite three times for each trial and two times for each condition to estimate test-retest variability. First, the normal walking condition is tested. Subsequently, a 3-minte walking test is performed, followed by a post-exercise protocol. After 10 min of rest, a recovery condition is tested. Secondly, the gait patterns of the mitochondrial patients are compared to 5 age-and gender matched healthy controls to gain more insight in which walking parameters were affected by mi-tochondrial disorders.Results and conclusionThe results of this validation study will be presented.

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