14,415 research outputs found
Oral Interview with Eng Peng
No full text26 min.Interview with Eng Peng on his experience coming to America, and how he attained the American Dream of hard work and being a homeowner
Relational power and communication: praxis for educational inclusivity
No full textEducational inclusivity (EI) is used in this chapter to explore inclusive education from the perspective of people living with disability in the Global South. The Kianh Centre in Vietnam is presented as an exemplar of the supportive role that specialist education settings can play for the development of equitable learning and participation. Focussing on the communication impairments of students, EI examines relationships of communication in localized experiences at the Centre, drawing specifically on Foucault’s concept of non-hierarchical power in its facilitation. This approach moves away from universal human rights for a critical southern theory approach. A framework of communication praxis is derived to explore how human and non-human contents, in fields of communication, affect interpersonal communication to effect inclusion. Proposed as such, communication praxis provokes the researcher to explore relationships at the Kianh Centre for EI pathways recognizing the importance of interpersonal communication in education
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
Agent-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
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
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
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
Agent-based Cloud service composition
No full textService composition in multi-Cloud environments
must coordinate self-interested participants, automate
service selection, (re)configure distributed services, and deal
with incomplete information about Cloud providers and
their services. This work proposes an agent-based approach
to compose services in multi-Cloud environments for different
types of Cloud services: one-time virtualized services,
e.g., processing a rendering job, persistent virtualized services,
e.g., infrastructure-as-a-service scenarios, vertical services,
e.g., integrating homogenous services, and horizontal
services, e.g., integrating heterogeneous services. Agents
are endowed with a semi-recursive contract net protocol and
service capability tables (information catalogs about Cloud
participants) to compose services based on consumer requirements.
Empirical results obtained from an agent-based
testbed show that agents in this work can: successfully compose
services to satisfy service requirements, autonomously
select services based on dynamic fees, effectively cope with
constantly changing consumers’ service needs that trigger
updates, and compose services in multiple Clouds even with
incomplete information about Cloud participants
Comparison between a phenomenological approach and a morphoelasticity approach regarding the displacement of extracellular matrix
No full textPlastic (permanent) deformations were earlier, modeled by a phenomenological model in Peng and Vermolen (Biomech Model Mechanobiol 19(6):2525–2551, 2020). In this manusctipt, we consider a more physics-based formulation that is based on morphoelasticity. We firstly introduce the morphoelasticity approach and investigate the impact of various input variables on the output parameters by sensitivity analysis. A comparison of both model formulations shows that both models give similar computational results. Furthermore, we carry out Monte Carlo simulations of the skin contraction model containing the morphoelasticity approach. Most statistical correlations from the two models are similar, however, the impact of the collagen density on the severeness of contraction is larger for the morphoelasticity model than for the phenomenological model.Numerical Analysi
3rd Lee Peng Yee Symposium: Celebrating Mathematics (18 - 19 Nov 2013)
No full textSome participants at the Symposium dinner: Mdm Chua Kwee Gek, Prof. Lee Peng Yee, Mdm. Yeo Shumei, Prof. Berinderjeet Kaur, (back row) A/P Tay Eng Guan and A/P Toh Pee Choon
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