110,716 research outputs found
NC-G-SIM: A Parameterized Generic Simulator for 2D-Mesh, 3D-Mesh
No full textAs chip density keeps doubling during each course of generation, the use of NoC has become an integral part of modern microprocessors and a very prevalent architectural feature of all types of SoCs. To meet the ever expanding communication challenges, diverse and novel NoC solutions are being developed which rely on accurate modeling and simulations to evaluate the impact and analyze their performances. Consequently, this aggravates the need to rely on simulation tools to probe and optimize these NoC architectures. In this work, we present NC-G-SIM (Network on Chip-Generic-SIMulator), a highly flexible, modular, cycle-accurate, configurable simulator for NoCs. To make NC-G-SIM suitable for advanced NoC exploration, it is made highly generic that supports extensive range of cores in any kind of topology whether 2D, 3D or irregular. Simulation results have been evaluated in terms of latencies, throughput and the amount of energy consumed during the simulation period at different levels
Grid Resource Negotiation: Survey and New Directions
No full textSince Grid computing systems involve large-scale resource sharing, resource management is central to their operations. Whereas there are more Grid resource management systems adopting auction, commodity market, and contract-net (tendering) models, this survey supplements and complements existing surveys by reviewing, comparing, and highlighting existing research initiatives on applying bargaining (negotiation) as a mechanism to Grid resource management. The contributions of this paper are: 1) discussing the motivations for considering bargaining models for Grid resource allocation; 2) discussing essential design considerations such as modeling devaluation of Grid resources, considering market dynamics, relaxing bargaining terms, and co-allocation of resources when building Grid negotiation mechanisms; 3) reviewing the strategies and protocols of state-of-the-art Grid negotiation mechanisms; 4) providing detailed comparisons and analyses on how state-of-the-art Grid negotiation mechanisms address the design considerations mentioned in 3); and 5) suggesting possible new directions
Grid Commerce, Market-Driven G-Negotiation, and Grid Resource Management
No full textAlthough the management of resources is essential
for realizing a computational grid, providing an efficient resource
allocation mechanism is a complex undertaking. Since Grid
providers and consumers may be independent bodies, negotiation
among them is necessary. The contribution of this paper
is showing that market-driven agents (MDAs) are appropriate
tools for Grid resource negotiation.MDAs are e-negotiation agents
designed with the flexibility of: 1) making adjustable amounts of
concession taking into account market rivalry, outside options,
and time preferences and 2) relaxing bargaining terms in the
face of intense pressure. A heterogeneous testbed consisting of
several types of e-negotiation agents to simulate a Grid computing
environment was developed. It compares the performance
of MDAs against other e-negotiation agents (e.g., Kasbah) in a
Grid-commerce environment. Empirical results show that MDAs
generally achieve: 1) higher budget efficiencies in many market
situations than other e-negotiation agents in the testbed and
2) higher success rates in acquiring Grid resources under high
Grid loadings
Retention of data in heat-damaged SIM cards and potential recovery methods
No full textExamination of various SIM cards and smart card devices indicates that data may be retained in SIM card memory structures even after heating to temperatures up to 450oC, which the National Institute of Standards and Technology (NIST) has determined to be approximately the maximum average sustained temperature at desk height in a house fire. However, in many cases, and certainly for temperatures greater than 450oC, the SIM card chip has suffered structural or mechanical damage that renders simple probing or rewiring ineffective. Nevertheless, this has not necessarily affected the data, which is stored as charge in floating gates, and alternative methods for directly accessing the stored charge may be applicable
Evolving Fuzzy Rules for Relaxed-Criteria Negotiation
No full textIn the literature on automated negotiation, very few negotiation agents are designed with the flexibility to slightly relax their negotiation criteria to reach a consensus more rapidly and with more certainty. Furthermore, these relaxed-criteria negotiation agents were not equipped with the ability to enhance their performance by learning and evolving their relaxed-criteria negotiation rules. The impetus of this work is designing market-driven negotiation agents (MDAs) that not only have the flexibility of relaxing bargaining criteria using fuzzy rules, but can also evolve their structures by learning new relaxed-criteria fuzzy rules to improve their negotiation outcomes as they participate in negotiations in more e-markets. To this end, an evolutionary algorithm for adapting and evolving relaxed-criteria fuzzy rules was developed. Implementing the idea in a testbed, two kinds of experiments for evaluating and comparing EvEMDAs (MDAs with relaxed-criteria rules that are evolved using the evolutionary algorithm) and EMDAs (MDAs with relaxed-criteria rules that are manually constructed) were carried out through stochastic simulations. Empirical results show that: 1) EvEMDAs generally outperformed EMDAs in different types of e-markets and 2) the negotiation outcomes of EvEMDAs generally improved as they negotiated in more e-markets
Miglioramento della sopravvivenza di lembi cutanei e muscolocutanei ischemici attraverso il trasferimento del gene vegf165 mediante vettori virali adeno-associati (AAV)
No full textAgent-Based Cloud Computing
No full textAgent-based cloud computing is concerned with the design and development of software agents for bolstering cloud service
discovery, service negotiation, and service composition. The significance of this work is introducing an agent-based paradigm for
constructing software tools and testbeds for cloud resource management. The novel contributions of this work include: 1) developing
Cloudle: an agent-based search engine for cloud service discovery, 2) showing that agent-based negotiation mechanisms can be
effectively adopted for bolstering cloud service negotiation and cloud commerce, and 3) showing that agent-based cooperative problemsolving
techniques can be effectively adopted for automating cloud service composition. Cloudle consists of 1) a service discovery agent
that consults a cloud ontology for determining the similarities between providers’ service specifications and consumers’ service
requirements, and 2) multiple cloud crawlers for building its database of services. Cloudle supports three types of reasoning: similarity
reasoning, compatibility reasoning, and numerical reasoning. To support cloud commerce, this work devised a complex cloud
negotiation mechanism that supports parallel negotiation activities in interrelated markets: a cloud service market between consumer
agents and broker agents, and multiple cloud resource markets between broker agents and provider agents. Empirical results show that
using the complex cloud negotiation mechanism, agents achieved high utilities and high success rates in negotiating for cloud resources.
To automate cloud service composition, agents in this work adopt a focused selection contract net protocol (FSCNP) for dynamically
selecting cloud services and use service capability tables (SCTs) to record the list of cloud agents and their services. Empirical results
show that using FSCNP and SCTs, agents can successfully compose cloud services by autonomously selecting services
BLGAN: Bayesian Learning and Genetic Algorithm for Supporting Negotiation With Incomplete Information
No full textAutomated negotiation provides a means for resolving
differences among interacting agents. For negotiation with
complete information, this paper provides mathematical proofs
to show that an agent’s optimal strategy can be computed using
its opponent’s reserve price (RP) and deadline. The impetus of
this work is using the synergy of Bayesian learning (BL) and
genetic algorithm (GA) to determine an agent’s optimal strategy
in negotiation (N) with incomplete information. BLGAN adopts:
1) BL and a deadline-estimation process for estimating an opponent’s
RP and deadline and 2) GA for generating a proposal
at each negotiation round. Learning the RP and deadline of an
opponent enables the GA in BLGAN to reduce the size of its search
space (SP) by adaptively focusing its search on a specific region
in the space of all possible proposals. SP is dynamically defined
as a region around an agent’s proposal P at each negotiation
round. P is generated using the agent’s optimal strategy determined
using its estimations of its opponent’s RP and deadline.
Hence, the GA in BLGAN is more likely to generate proposals
that are closer to the proposal generated by the optimal strategy.
Using GA to search around a proposal generated by its current
strategy, an agent in BLGAN compensates for possible errors in
estimating its opponent’s RP and deadline. Empirical results show
that agents adopting BLGAN reached agreements successfully,
and achieved: 1) higher utilities and better combined negotiation
outcomes (CNOs) than agents that only adopt GA to generate their
proposals, 2) higher utilities than agents that adopt BL to learn
only RP, and 3) higher utilities and better CNOs than agents that
do not learn their opponents’ RPs and deadlines
Sensititre Y05 per l’antimicogramma di lieviti e muffe
No full textIl pannello Sensititre YO5, non ancora disponibile per antimicogrammi di routine, comprende la caspofungina, un’echinocandina con ampio spettro d’azione che inibisce specificamente la ß1-3 D-glucan sintetasi e danneggia direttamente l’impalcatura della parete cellulare.
Il pannello è stato utilizzato per l’antimicogramma di 128 ceppi clinici di funghi di cui 16 Aspergillus spp. e 112 Candida spp. Come ceppi di controllo sono stati utilizzati C. krusei ATCC® 6258, C. parapsilosis ATCC® 22019 e A. flavus ATCC® 204304
Sim, R G, VX60051
No full textThis record was harvested from a previous catalogue system and will be withdrawn in 2025. Information in this record may be superseded or incomplete. Visit this record in UMA's new catalogue at: https://archives.library.unimelb.edu.au/nodes/view/416872Surname: SIM. Given Name(s) or Initials: R G. Military Service Number or Last Known Location: VX60051. Missing, Wounded and Prisoner of War Enquiry Card Index Number: 42327.239276
Item: [2016.0049.49133] "Sim, R G, VX60051
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