活塞综合检测仪的研制

介绍了活塞综合检测仪的功能、组成、检测过程、测量原理与方法和主要技术性能指标。该仪器是国内研制的第一台智能型活塞综合检测仪。实际应用表明,这是一台高精度、高稳定性和高效率的检测仪器。     

Collaborative assignment using belief-desire-intention agent modeling and negotiation with speedup strategies

In this paper, we propose a distributed agent model that applies belief-desire-intention (BDI) reasoning and negotiation for addressing the linear assignment problem (LAP) collaboratively. In resource allocation, LAP is viewed as seeking a concurrent allocation of one different resource for every task to optimize a linear sum objective function. The proposed model provides a basic agent-based foundation needed for efficient resource allocation in a distributed environment. A distributed agent algorithm that has been developed based on the BDI negotiation model is examined both analytically and experimentally. To improve performance in terms of average negotiation speed and solution quality, two initialization heuristics and two different reasoning control strategies are applied, with the latter yielding different variants of the basic algorithm. Extensive simulations suggest that all the heuristic-algorithm combinations can produce a near optimal solution soon enough in some specific sense. The significance and applicability of the research work are also discussed.     

Bilattices and Reasoning in Artificial Intelligence: Concepts and Foundations

The past few decades have seen a resurgence ofreasoning techniques in artificial intelligenceinvolving both classical and non-classical logics. Inhis paper, ``Multi-valued Logics: A Uniform Approach toReasoning in Artificial Intelligence', Ginsberg hasshown that through the use of bilattices,several reasoning techniques can be unified under asingle framework. A bilattice is a structure that canbe viewed as a class of truth values that canaccommodate incomplete and inconsistent informationand in certain cases default information. Inbilattice theory, knowledge is ordered along twodimensions: truth/falsity and certainty/uncertainty. By defining the corresponding bilattices as truthspaces, Ginsberg has shown that the same theoremprover can be used to simulate reasoning in firstorder logic, default logic, prioritized default logicand assumption truth maintenance system. Although thisis a significant contribution, Ginsberg's paper waslengthy and involved. This paper summarizes some ofthe essential concepts and foundations of bilatticetheory. Furthermore, it discusses the connections ofbilattice theory and several other existingmulti-valued logics such as the various three-valuedlogics and Belnap's four-valued logic. It is notedthat the set of four truth values in Belnap's logicform a lattice structure that is isomorphic to thesimplest bilattice. Subsequently, Fitting proposed aconflation operation that can be used to selectsub-sets of truth values from this and otherbilattices. This method of selecting sub-sets oftruth values provides a means for identifyingsub-logic in a bilattice.     

Ant colony optimization for routing and load-balancing: survey and new directions

Although an ant is a simple creature, collectively a colony of ants performs useful tasks such as finding the shortest path to a food source and sharing this information with other ants by depositing pheromone. In the field of ant colony optimization (ACO), models of collective intelligence of ants are transformed into useful optimization techniques that find applications in computer networking. In this survey, the problem-solving paradigm of ACO is explicated and compared to traditional routing algorithms along the issues of routing information, routing overhead and adaptivity. The contributions of this survey include 1) providing a comparison and critique of the state-of-the-art approaches for mitigating stagnation (a major problem in many ACO algorithms), 2) surveying and comparing three major research in applying ACO in routing and load-balancing, and 3) discussing new directions and identifying open problems. The approaches for mitigating stagnation discussed include: evaporation, aging, pheromone smoothing and limiting, privileged pheromone laying and pheromone-heuristic control. The survey on ACO in routing/load-balancing includes comparison and critique of ant-based control and its ramifications, AntNet and its extensions, as well as ASGA and SynthECA. Discussions on new directions include an ongoing work of the authors in applying multiple ant colony optimization in load-balancing.     

Negotiation Agents that Make Prudent Compromises and are Slightly Flexible in Reaching Consensus

The contribution of this work is designing and developing enhanced market-driven agents with the flexibility to (1) respond to changing market conditions, and (2) raise and relax trade aspirations. Previous theoretical analyses have shown that market-driven agents ( MDA s) make prudent compromises by reacting to changing market situations by taking into account factors such as competition, deadlines, and trading options. This work augments the design of an MDA with three fuzzy decision controllers that guide the agent in (i) relaxing trade aspiration in face of intense negotiation pressure, and (ii) raising trade aspiration in extremely favorable markets. Results from extensive simulations conducted using an implemented testbed suggest that when compared to MDA s, agents in this work achieved (1) higher success rates in reaching deals, (2) higher average utilities, and (3) higher expected utility.     

Dietary Trans Fats Enhance Doxorubicin‐Induced Cardiotoxicity in Mice

This study investigated the combined effects of trans fat diet (TFD) and doxorubicin upon cardiac oxidative, inflammatory, and coagulatory stress. TFD increased trans fatty acid deposit in heart (P < 0.05), and decreased protein C and antithrombin‐III activities in circulation (P < 0.05). TFD plus doxorubicin treatment elevated activities of plasminogen activator inhibitor‐1, lactate dehydrogenase, and creatine phosphokinase (P < 0.05). This combination also raised xanthine oxidase activity, and enhanced cardiac levels of reactive oxygen species, interleukin (IL)‐6, IL‐10, tumor necrosis factor‐alpha, and monocyte chemoattractant protein‐1 than TFD or doxorubicin treatment alone (P < 0.05). TFD alone increased cardiac nuclear factor kappa B (NF‐κB) activity (P < 0.05), but failed to affect expression of NF‐κB and mitogen‐activated protein kinase (MAPK) (P > 0.05). Doxorubicin treatment alone augmented cardiac activity, mRNA expression, and protein production of NF‐κB and MAPK (P < 0.05). TFD plus doxorubicin treatment further upregulated cardiac expression of NF‐κB p65, p‐p38, and p‐ERK1/2 (P < 0.05). These findings suggest that TFD exacerbates doxorubicin‐induced cardiotoxicity.     

Continuous-Time Negotiation Mechanism for Software Agents

While there are several existing mechanisms and systems addressing the crucial and difficult issues of automated one-to-many negotiation, this paper develops a flexible one-to-many negotiation mechanism for software agents. Unlike the existing general one-to-many negotiation mechanism, in which an agent should wait until it has received proposals from all its trading partners before generating counterproposals, in the flexible one-to-many negotiation mechanism, an agent can make a proposal in a flexible way during negotiation, i.e., negotiation is conducted in continuous time. To decide when to make a proposal, two strategies based on fixed waiting time and a fixed waiting ratio is proposed. Results from a series of experiments suggest that, guided by the two strategies for deciding when to make a proposal, the flexible negotiation mechanism achieved more favorable trading outcomes as compared with the general one-to-many negotiation mechanism. To determine the amount of concession, negotiation agents are guided by four mathematical functions based on factors such as time, trading partners' strategies, negotiation situations of other threads, and competition. Experimental results show that agents guided by the four functions react to changing market situations by making prudent and appropriate rates of concession and achieve generally favorable negotiation outcomes     

ERL: Logic for entity-relationship databases

We develop a logic for entity-relationship databases, ERL, that is a generalization of database logic. ERL provides advantages to the ER model much as FOL (first-order logic) does to the relational model: a uniform language for expressing database schema, integrity constraints, and database manipulation; clearly defined semantics; the capability to express database transformations; and deductive capabilities. We propose three query languages for ER databases called ERRC, ERSQL, and ERQBE, which are generalizations of the relational calculus, SQL, and QBE, respectively. We use example queries and updates to demonstrate the capabilities of these languages. We apply database transformations to introduce the notion of views and to show that both ERRC and ERSQL are relationally complete.Research sponsored in part by the National Science Foundation under grant IRI-8921951 and by Towson State University.     

Agent-based Cloud service composition

Service 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.