3D haptic needle insertion simulator utilising an agent based spherical voxel model

This paper describes a technique for the real-time modeling of deformable tissue. Specifically geared towards needle insertion simulation, the low computational requirements of the model enable highly accurate haptic feedback to a user without introducing noticeable time delay or buzzing generally associated with haptic surgery simulation. Using a spherical voxel array combined with aspects of computational geometry and agent communication and interaction principals, the model is capable of providing haptic update rates of over 1000Hz with real-time visual feedback. Iterating through over 1000 voxels per millisecond to determine collision and haptic response while making use of Vieta’s Theorem for extraneous force culling.

Modelling financial investment planning from agent perspectives

Multi-agent Systems (MASs) offer strong models for representing complex and dynamic real-world environments. Taking financial investment planning as an example, this paper describes how to model complex systems from agent perspectives. Different agents and their behaviours are identified for financial investment planning. These agents are put together as an agent-based system. The experimental results show that all agents in the system can work cooperatively to provide reasonable investment advice. The system is very flexible and robust. The success of the system indicates that (MASs) can significantly facilitate the modelling of complex systems.

An improved trust model in agent-mediated E-commerce

Trust is a fundamental issue in multiagent systems, especially in agent-mediated e-commence. The trust model plays an important role in determining who and how to interact in open and dynamic environments. To this end, many trust models have been developed. Based on the confidence–reputation model proposed by other researchers, an improved trust model is discussed. The original model was enhanced in two aspects: (1) when evaluating the trustworthiness of target agents, the reliability of the witness itself is taken into account and further aggregated by Dempster-Shafer evidence theory and (2) the ontological property of trust is considered, which implies that trust can be calculated more precisely. A case study is provided to show the effectiveness of the improved model.

Effects of process control agent on the microstructure and mechanical properties of Ti-Sn-Nb alloy prepared by mechanical alloying

In the present study, the influence of process control agent (PCA) on the characteristics of powder and bulk sintered Ti-16Sn-4Nb (wt. %) alloy prepared by mechanical alloying has been investigated. The elemental Ti, Sn and Nb powders were mechanically alloyed in a planetary ball mill for a short period of time using two types of PCA, namely stearic acid (SA) and ethylene bis-stearamide (EBS). The powder morphology, microstructural evolution of the bulk sintered alloy, phase formation and hardness of the alloy have been studied as a function of PCA. Results indicated that the addition of PCA leads to a delay in aIloy formation and introduces contaminations (mainly carbon and oxygen) into the material. The microstructural observation of the bulk alloy revealed a homogeneous distribution of fine Nb-rich colonies (ß-phase) within the a-Ti matrix for small amount of PCA. The hardness values of samples exhibited a significant increase with increasing amount of PCA, reaching a value of ~ 600 BV.

Multi-agent based supply chain management with dynamic reconfiguration capability

Supply chain management (SCM) has received increased attention in a globally challenging environment as companies face the necessity to improve customer service and maximize profit. Therefore, dynamic reconfiguration capability is vital for supply chain management to respond to changing customer requirements and operating environments. On the other hand, for its flexible and autonomous characteristics, multi-agent systems are a viable technology for SCM, and have been widely applied in SCM. To this end, dynamic reconfiguration in agent-based SCM systems is proposed from autonomy oriented computing point of view. The performance of agent-based SCM with dynamic reconfiguration is evaluated under a modified TAC SCM scenario. With a dynamic reconfigurable SCM system, new products and processes can be introduced with considerably less expense and ramp-up time.

The influence of heat on biological activity and concentration of oleocanthal - a natural anti-inflammatory agent

Background – The olive oil phenolic, oleocanthal is a natural non-steroidal anti-inflammatory compound that irritates the oropharynx in a dose-dependent manner. It has been proposed that the biological activity of oleocanthal is partially responsible for the beneficial health effects of the Mediterranean diet. Virgin olive oil containing oleocanthal is often added as an ingredient in a number of cooked dishes and therefore it is of great importance to understand how best to preserve the putative health promoting benefits of this compound, as olive oil phenolics are
subject to heat degradation.

Objective – To investigate if oleocanthal is thermally degraded or its biological activity reduced during cooking.

Design – One extra virgin olive oil containing 54mg/kg oleocanthal was heated at varying temperatures (100°C, 170°C and 240°C) for set time periods (0, 1, 5, 20, 60, 90 min). Oleocanthal concentrations were quantified using HPLC and its biological activity determined with a taste bioassay measuring the intensity of throat irritation.

Outcomes – Results demonstrated that oleocanthal was heat stable compared with other olive oil phenolics, with a maximum loss of 16% as determined by HPLC analysis. In contrast, there was a significant decrease of up to 38% (p<0.05) in the biological activity of oleocanthal as determined by the taste bioassay.

Conclusions – Minimal degradation of oleocanthal concentration was observed upon heating however a significant decrease in the biological activity of this compound was noted with extended heating time. This has important implications for health in that, consumers may be unable to reap all of the putative health benefits associated with oleocanthal when adding virgin olive oil as an ingredient to dishes requiring prolonged heat treatment.

Sensory characterization of the irritant properties of oleocanthal, a natural anti-inflammatory agent in extra virgin olive oils

Oleocanthal is an olive oil phenolic possessing anti-inflammatory activity. Anecdotal evidence suggests that oleocanthal elicits a stinging sensation felt only at the back of the throat (oropharynx). Due to this compound possessing potentially health-benefiting properties, investigation into the sensory aspects of oleocanthal is warranted to aid in future research. The important link between the perceptual aspects of oleocanthal and health benefits is the notion that variation in sensitivity to oleocanthal irritation may relate to potential differences in sensitivity to the pharmacologic action of this compound. The current study assessed the unique irritant attributes of oleocanthal including its location of irritation, temporal profile, and individual differences in the perceived irritation. We show that the irritation elicited by oleocanthal was localized to the oropharynx (P < 0.001) with little or no irritation in the anterior oral cavity. Peak irritation was perceived 15 s postexposure and lasted over 180 s. Oleocanthal irritation was more variable among individuals compared with the irritation elicited by CO₂ and the sweetness of sucrose. There was no correlation between intensity ratings of oleocanthal and CO₂ and oleocanthal and sucrose (r = –0.15, n = 50, P = 0.92 and r = 0.17, n = 84, P = 0.12, respectively), suggesting that independent mechanisms underlie the irritation of CO₂ and oleocanthal. The unusual spatial localization and independence of acid (CO₂) sensations suggest that distinct nociceptors for oleocanthal are located in the oropharyngeal region of the oral cavity.

Observer-based robust finite-time cooperative consensus control for multi-agent networks

This paper studies the finite-time consensus tracking control for multi-agent networks. The time-varying control input and the velocity of the leader is unknown to any follower. Only the position of the leader is known to its neighbors. We first propose a new finite-time multiple-surface sliding mode observer to estimate the leader's velocity. It is seen that the estimation error of the observer can converge to zero in a finite time. Then, we prove that finite-time consensus tracking of multi-agent networks can be achieved on a new terminal sliding mode surface. Simulation results are presented to validate the analysis.

Influence of heat on biological activity and concentration of oleocanthal : a natural anti-inflammatory agent in virgin olive oil

The olive oil phenolic oleocanthal is a natural nonsteroidal anti-inflammatory compound that irritates the oral pharynx in a dose-dependent manner. It has been proposed that the biological activity of oleocanthal is partially responsible for the beneficial health effects of the Mediterranean diet. Virgin
olive oil containing oleocanthal is often added as an ingredient in a number of cooked dishes, and therefore it is of great importance to understand how best to preserve the putative health-promoting benefits of this compound, as olive oil phenolics are subject to degradation upon heating in general. One extra virgin olive oil containing 53.9 mg/kg oleocanthal was heated at various temperatures (100, 170, and 240 °C) for set time periods (0, 1, 5, 20, 60, and 90 min). Oleocanthal concentrations were quantified using HPLC, and its biological activity was determined with a taste bioassay measuring the intensity of throat irritation. Results demonstrated that oleocanthal was heat stable compared with other olive oil phenolics, with a maximum loss of 16% as determined by HPLC analysis. However, there was a significant decrease of up to 31% (p < 0.05) in the biological activity of oleocanthal as determined by the taste bioassay. Although there was minimal degradation of leocanthal concentration, there was a significant decrease in the biological activity of oleocanthal upon extended heating time, indicating a possible loss of the putative health -benefiting properties of oleocanthal. Alternatively, the difference in the concentration and biological activity of oleocanthal after heat treatment could be a result of an oleocanthal antagonist forming, decreasing or masking the biological activity of oleocanthal.

Finite-time consensus algorithm of multi-agent networks

This paper is concerned with leader-follower finite-time consensus control of multi-agent networks with input disturbances. Terminal sliding mode control scheme is used to design the distributed control law. A new terminal sliding mode surface is proposed to guarantee finite-time consensus under fixed topology, with the common assumption that the position and the velocity of the active leader is known to its neighbors only. By using the finite-time Lyapunov stability theorem, it is shown that if the directed graph of the network has a directed spanning tree, then the terminal sliding mode control law can guarantee finite-time consensus even under the assumption that the time-varying control input of the active leader is unknown to any follower.

Effects of leveling agent on the uptake of reactive dyes by untreated and plasma-treated wool

Atmospheric-pressure plasma treatment of wool fabric produced a significantly higher level of adsorbed fiber-reactive dye when applied at 50 °C (pH 3.0–6.0) in the absence of any organic leveling agent. In addition, color yields indicated that dye was more uniformly adsorbed by the plasma-treated fabric compared with the untreated material. When untreated fabric was dyed in the presence of a leveling agent (Albegal B), the extent and levelness of dye sorption were enhanced. These enhancements were, however, relatively small on the plasma-treated wool compared with those on untreated wool. A ‘surface’ mechanism, similar to that proposed when plasma-treated wool is dyed in the absence of leveling agent, can explain the leveling ability of Albegal B under adsorption conditions. Increasing the dyebath temperature to 90 °C resulted in dye penetration of the fibers. Under these conditions, any enhancements of dye uptake produced by the plasma treatment, as well as the use of Albegal B, were relatively small, in contrast to the behavior at 50 °C. Improvements in the uniformity of dye sorption observed at 50 °C were, however, maintained at the higher temperature. It is concluded that the inability of reactive dyes to migrate (and so promote leveling and uniformity) once they have reacted with the fiber, means that differences in the uniformity of dye sorbed at 50 °C are still apparent at equilibrium.

Optimising discrete event simulation models using a reinforcement learning agent

A reinforcement learning agent has been developed to determine optimal operating policies in a multi-part serial line. The agent interacts with a discrete event simulation model of a stochastic production facility. This study identifies issues important to the simulation developer who wishes to optimise a complex simulation or develop a robust operating policy. Critical parameters pertinent to 'tuning' an agent quickly and enabling it to rapidly learn the system were investigated.

Agent-based hybrid framework for decision making on complex problems

Electronic commerce and the Internet have created demand for automated systems that can make complex decisions utilizing information from multiple sources. Because the information is uncertain, dynamic, distributed, and heterogeneous in nature, these systems require a great diversity of intelligent techniques including expert systems, fuzzy logic, neural networks, and genetic algorithms. However, in complex decision making, many different components or sub-tasks are involved, each of which requires different types of processing. Thus multiple such techniques are required resulting in systems called hybrid intelligent systems. That is, hybrid solutions are crucial for complex problem solving and decision making. There is a growing demand for these systems in many areas including financial investment planning, engineering design, medical diagnosis, and cognitive simulation. However, the design and development of these systems is difficult because they have a large number of parts or components that have many interactions. From a multi-agent perspective, agents in multi-agent systems (MAS) are autonomous and can engage in flexible, high-level interactions. MASs are good at complex, dynamic interactions. Thus a multi-agent perspective is suitable for modeling, design, and construction of hybrid intelligent systems. The aim of this thesis is to develop an agent-based framework for constructing hybrid intelligent systems which are mainly used for complex problem solving and decision making. Existing software development techniques (typically, object-oriented) are inadequate for modeling agent-based hybrid intelligent systems. There is a fundamental mismatch between the concepts used by object-oriented developers and the agent-oriented view. Although there are some agent-oriented methodologies such as the Gaia methodology, there is still no specifically tailored methodology available for analyzing and designing agent-based hybrid intelligent systems. To this end, a methodology is proposed, which is specifically tailored to the analysis and design of agent-based hybrid intelligent systems. The methodology consists of six models - role model, interaction model, agent model, skill model, knowledge model, and organizational model. This methodology differs from other agent-oriented methodologies in its skill and knowledge models. As good decisions and problem solutions are mainly based on adequate information, rich knowledge, and appropriate skills to use knowledge and information, these two models are of paramount importance in modeling complex problem solving and decision making. Follow the methodology, an agent-based framework for hybrid intelligent system construction used in complex problem solving and decision making was developed. The framework has several crucial characteristics that differentiate this research from others. Four important issues relating to the framework are also investigated. These cover the building of an ontology for financial investment, matchmaking in middle agents, reasoning in problem solving and decision making, and decision aggregation in MASs. The thesis demonstrates how to build a domain-specific ontology and how to access it in a MAS by building a financial ontology. It is argued that the practical performance of service provider agents has a significant impact on the matchmaking outcomes of middle agents. It is proposed to consider service provider agents' track records in matchmaking. A way to provide initial values for the track records of service provider agents is also suggested. The concept of ‘reasoning with multimedia information’ is introduced, and reasoning with still image information using symbolic projection theory is proposed. How to choose suitable aggregation operations is demonstrated through financial investment application and three approaches are proposed - the stationary agent approach, the token-passing approach, and the mobile agent approach to implementing decision aggregation in MASs. Based on the framework, a prototype was built and applied to financial investment planning. This prototype consists of one serving agent, one interface agent, one decision aggregation agent, one planning agent, four decision making agents, and five service provider agents. Experiments were conducted on the prototype. The experimental results show the framework is flexible, robust, and fully workable. All agents derived from the methodology exhibit their behaviors correctly as specified.