19 resultados para IS location

em Aston University Research Archive


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This paper develops and applies an integrated multiple criteria decision making approach to optimize the facility location-allocation problem in the contemporary customer-driven supply chain. Unlike the traditional optimization techniques, the proposed approach, combining the analytic hierarchy process (AHP) and the goal programming (GP) model, considers both quantitative and qualitative factors, and also aims at maximizing the benefits of deliverer and customers. In the integrated approach, the AHP is used first to determine the relative importance weightings or priorities of alternative locations with respect to both deliverer oriented and customer oriented criteria. Then, the GP model, incorporating the constraints of system, resource, and AHP priority is formulated to select the best locations for setting up the warehouses without exceeding the limited available resources. In this paper, a real case study is used to demonstrate how the integrated approach can be applied to deal with the facility location-allocation problem, and it is proved that the integrated approach outperforms the traditional costbased approach.

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Recent years have seen advances in neuroimaging to such an extent that neuroscientists are able to directly study the frequency, location, and timing of neuronal activity to an unprecedented degree. However, marketing science has remained largely unaware of such advances and their huge potential. In fact, the application of neuroimaging to market research - what has come to be called 'neuromarketing' - has caused considerable controversy within neuroscience circles in recent times. This paper is an attempt to widen the scope of neuromarketing beyond commercial brand and consumer behaviour applications, to include a wider conceptualisation of marketing science. Drawing from general neuroscience and neuroeconomics, neuromarketing as a field of study is defined, and some future research directions are suggested. © 2006 Elsevier B.V. All rights reserved.

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The density of the diffuse, primitive and classic beta-amyloid (Abeta) deposits and the incidence of large and small diameter blood vessels was studied in the upper laminae of the frontal cortex of 10 patients with sporadic Alzheimer’s disease (AD). The data were analysed using the partial correlation coefficient to determine whether variations in the density of Abeta deposit subtypes along the cortex were related to blood vessels. Significant correlations between the density of the diffuse or primitive Abeta deposits and blood vessels were found in only a small number of patients. However, the classic Abeta deposits were positively correlated with the large blood vessels in all 10 patients, the correlations remaining when the effects of gyral location and mutual correlations between Abeta deposits were removed. These results suggest that the larger blood vessels are involved specifically in the formation of the classic Abeta deposits and are less important in the formation of the diffuse and primitive deposits.

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The aim of this work was to investigate the feasibility of detecting and locating damage in large frame structures where visual inspection would be difficult or impossible. This method is based on a vibration technique for non-destructively assessing the integrity of structures by using measurements of changes in the natural frequencies. Such measurements can be made at a single point in the structure. The method requires that initially a comprehensive theoretical vibration analysis of the structure is undertaken and from it predictions are made of changes in dynamic characteristics that will occur if each member of the structure is damaged in turn. The natural frequencies of the undamaged structure are measured, and then routinely remeasured at intervals . If a change in the natural frequencies is detected a statistical method. is used to make the best match between the measured changes in frequency and the family of theoretical predictions. This predicts the most likely damage site. The theoretical analysis was based on the finite element method. Many structures were extensively studied and a computer model was used to simulate the effect of the extent and location of the damage on natural frequencies. Only one such analysis is required for each structure to be investigated. The experimental study was conducted on small structures In the laboratory. Frequency changes were found from inertance measurements on various plane and space frames. The computational requirements of the location analysis are small and a desk-top micro computer was used. Results of this work showed that the method was successful in detecting and locating damage in the test structures.

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The topographical distribution of the pattern reversal Visual Evoked Response (VER) was recorded from a localised montage of 20 electrodes over the visual cortex. The response was recorded after stimulation with a black and white checkerboard stimulus. The effect of field location on the major components was investigated in 11 subjects (age range (23-55). The major components of the half field response were; a negative around 75ms (N75) followed by a positivity around 80ms (P80), then a positivity around 100ms (P100) followed by another positivity at around 120ms (P120) and a negativity at approximately 145ms (N145). No effect of field size could be demonstrated on either the amplitude or latency of the late negativity, N145. No significant effect of field size or location was shown on the latency of the P100 response. A delay previously shown in the upper half field response was therefore not substantiated. In contrast the amplitude of the major positivity, P100 was significantly affected by the field size and location. The amplitude of both P100 and N145 were significantly reduced following upper field stimulation when compared with the lower field response. No significant amplitude difference between the upper and lower field responses was demonstrated using electroretinography, the amplitude may therefore be reduced as a result of the ventral position of the upper field representation on the visual cortex. The lateral half field VEP was compared with the distribution of the visual evoked magnetic response (VEMR). The distribution of the VEMR supported the proposal that the paradoxical lateralisation of the VEP half field response is the result of the source being directed ipsilaterally. The morphology of the VEP following octant and double octant stimulation suggests that the response is generated in the striate cortex, with a reversal in response distribution following stimulation of the upper vertical and horizontal meridia.

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The economic effects of road building (beyond those accounted for in cost-benefit analysis) are not well understood. This thesis examines the issues surrounding those effects and attempts to clarify the relationship between road building and industrial location and to identify the effect on employment of that location. The literature reviewed leads to some doubt as to the efficacy of roads as an economic tool. A scries of interviews with representatives of business and property professionals in three areas adjacent to motorways is carried out. These covered the firms' location or relocation decisions, their production costs, transport needs and employment. The conclusions drawn echo the above statements based on reviewed literature: 1. There was a general lack of knowledge of transport within a firm despite subjects' very good understanding of the rest of the firms' operations. 2. The importance of major roads to the business location decision and its perceived importance to the operations of the firms was low. Property professionals sec roads as an effective marketing tool. 3. Firms have a tendency to shed labour upon relocation although this does not necessarily constitute a net loss of employment but a redistribution. Recommendations are made for further research.

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The application of high-power voltage-source converters (VSCs) to multiterminal dc networks is attracting research interest. The development of VSC-based dc networks is constrained by the lack of operational experience, the immaturity of appropriate protective devices, and the lack of appropriate fault analysis techniques. VSCs are vulnerable to dc-cable short-circuit and ground faults due to the high discharge current from the dc-link capacitance. However, faults occurring along the interconnecting dc cables are most likely to threaten system operation. In this paper, cable faults in VSC-based dc networks are analyzed in detail with the identification and definition of the most serious stages of the fault that need to be avoided. A fault location method is proposed because this is a prerequisite for an effective design of a fault protection scheme. It is demonstrated that it is relatively easy to evaluate the distance to a short-circuit fault using voltage reference comparison. For the more difficult challenge of locating ground faults, a method of estimating both the ground resistance and the distance to the fault is proposed by analyzing the initial stage of the fault transient. Analysis of the proposed method is provided and is based on simulation results, with a range of fault resistances, distances, and operational conditions considered.

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Based on Bayesian Networks, methods were created that address protein sequence-based bacterial subcellular location prediction. Distinct predictive algorithms for the eight bacterial subcellular locations were created. Several variant methods were explored. These variations included differences in the number of residues considered within the query sequence - which ranged from the N-terminal 10 residues to the whole sequence - and residue representation - which took the form of amino acid composition, percentage amino acid composition, or normalised amino acid composition. The accuracies of the best performing networks were then compared to PSORTB. All individual location methods outperform PSORTB except for the Gram+ cytoplasmic protein predictor, for which accuracies were essentially equal, and for outer membrane protein prediction, where PSORTB outperforms the binary predictor. The method described here is an important new approach to method development for subcellular location prediction. It is also a new, potentially valuable tool for candidate subunit vaccine selection.

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We describe a novel and potentially important tool for candidate subunit vaccine selection through in silico reverse-vaccinology. A set of Bayesian networks able to make individual predictions for specific subcellular locations is implemented in three pipelines with different architectures: a parallel implementation with a confidence level-based decision engine and two serial implementations with a hierarchical decision structure, one initially rooted by prediction between membrane types and another rooted by soluble versus membrane prediction. The parallel pipeline outperformed the serial pipeline, but took twice as long to execute. The soluble-rooted serial pipeline outperformed the membrane-rooted predictor. Assessment using genomic test sets was more equivocal, as many more predictions are made by the parallel pipeline, yet the serial pipeline identifies 22 more of the 74 proteins of known location.

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Two algorithms, based onBayesian Networks (BNs), for bacterial subcellular location prediction, are explored in this paper: one predicts all locations for Gram+ bacteria and the other all locations for Gram- bacteria. Methods were evaluated using different numbers of residues (from the N-terminal 10 residues to the whole sequence) and residue representation (amino acid-composition, percentage amino acid-composition or normalised amino acid-composition). The accuracy of the best resulting BN was compared to PSORTB. The accuracy of this multi-location BN was roughly comparable to PSORTB; the difference in predictions is low, often less than 2%. The BN method thus represents both an important new avenue of methodological development for subcellular location prediction and a potentially value new tool of true utilitarian value for candidate subunit vaccine selection.

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A comprehensive coverage is crucial for communication, supply, and transportation networks, yet it is limited by the requirement of extensive infrastructure and heavy energy consumption. Here, we draw an analogy between spins in antiferromagnet and outlets in supply networks, and apply techniques from the studies of disordered systems to elucidate the effects of balancing the coverage and supply costs on the network behavior. A readily applicable, coverage optimization algorithm is derived. Simulation results show that magnetized and antiferromagnetic domains emerge and coexist to balance the need for coverage and energy saving. The scaling of parameters with system size agrees with the continuum approximation in two dimensions and the tree approximation in random graphs. Due to frustration caused by the competition between coverage and supply cost, a transition between easy and hard computation regimes is observed. We further suggest a local expansion approach to greatly simplify the message updates which shed light on simplifications in other problems. © 2014 American Physical Society.

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Location estimation is important for wireless sensor network (WSN) applications. In this paper we propose a Cramer-Rao Bound (CRB) based analytical approach for two centralized multi-hop localization algorithms to get insights into the error performance and its sensitivity to the distance measurement error, anchor node density and placement. The location estimation performance is compared with four distributed multi-hop localization algorithms by simulation to evaluate the efficiency of the proposed analytical approach. The numerical results demonstrate the complex tradeoff between the centralized and distributed localization algorithms on accuracy, complexity and communication overhead. Based on this analysis, an efficient and scalable performance evaluation tool can be designed for localization algorithms in large scale WSNs, where simulation-based evaluation approaches are impractical. © 2013 IEEE.

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The global plant location decision is important since it involves the allocation of significant resources and may influence the long term competitiveness of firms. The decision is also complex, taking into account a wide range of factors. The decision should involve the consideration of both international business issues as well as manufacturing strategy. Firms may be seeking access to markets, to low cost labour, or new skills and competencies. In the past there has been some emphasis on firms offshoring production to lower cost regions. Case studies from the authors’ experience of advising clients in this decision show that for ‘luxury’ products, firms have chosen to invest further capacity in home country engineering and manufacturing to maintain quality and brand integrity, despite the fact that these locations are higher cost. On the other hand, for ‘standard’ products, firms have located additional capacity closer to target markets to access lower costs.

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With the advent of GPS enabled smartphones, an increasing number of users is actively sharing their location through a variety of applications and services. Along with the continuing growth of Location-Based Social Networks (LBSNs), security experts have increasingly warned the public of the dangers of exposing sensitive information such as personal location data. Most importantly, in addition to the geographical coordinates of the user’s location, LBSNs allow easy access to an additional set of characteristics of that location, such as the venue type or popularity. In this paper, we investigate the role of location semantics in the identification of LBSN users. We simulate a scenario in which the attacker’s goal is to reveal the identity of a set of LBSN users by observing their check-in activity. We then propose to answer the following question: what are the types of venues that a malicious user has to monitor to maximize the probability of success? Conversely, when should a user decide whether to make his/her check-in to a location public or not? We perform our study on more than 1 million check-ins distributed over 17 urban regions of the United States. Our analysis shows that different types of venues display different discriminative power in terms of user identity, with most of the venues in the “Residence” category providing the highest re-identification success across the urban regions. Interestingly, we also find that users with a high entropy of their check-ins distribution are not necessarily the hardest to identify, suggesting that it is the collective behaviour of the users’ population that determines the complexity of the identification task, rather than the individual behaviour.

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In recent years, the rapid spread of smartphones has led to the increasing popularity of Location-Based Social Networks (LBSNs). Although a number of research studies and articles in the press have shown the dangers of exposing personal location data, the inherent nature of LBSNs encourages users to publish information about their current location (i.e., their check-ins). The same is true for the majority of the most popular social networking websites, which offer the possibility of associating the current location of users to their posts and photos. Moreover, some LBSNs, such as Foursquare, let users tag their friends in their check-ins, thus potentially releasing location information of individuals that have no control over the published data. This raises additional privacy concerns for the management of location information in LBSNs. In this paper we propose and evaluate a series of techniques for the identification of users from their check-in data. More specifically, we first present two strategies according to which users are characterized by the spatio-temporal trajectory emerging from their check-ins over time and the frequency of visit to specific locations, respectively. In addition to these approaches, we also propose a hybrid strategy that is able to exploit both types of information. It is worth noting that these techniques can be applied to a more general class of problems where locations and social links of individuals are available in a given dataset. We evaluate our techniques by means of three real-world LBSNs datasets, demonstrating that a very limited amount of data points is sufficient to identify a user with a high degree of accuracy. For instance, we show that in some datasets we are able to classify more than 80% of the users correctly.