Application of co-operative agents in handling fluctuations in a pull production system

This paper presents the general details of the structure and strategy of a multi-agent system that is being developed to improve the performance of pull (kanban) production control to handle large fluctuations in product demand. Employing a set of generic, heterarchial agents each controlling a single product and co-operating together to ensure that all components, regardless of demand fluctuation, are manufactured on time as per basic kanban principles. Preliminary results indicate that the basic kanban model does not cater for large demand fluctuations and the application of this multi-agent strategy may be beneficial to improving the overall system performance and increase the likelihood that all products will be manufactured on time.

Using autonomous mobile agents for efficient data collection in sensor networks

Sensor networks are emerging as the new frontier in sensing technology, however there are still issues that need to be addressed. Two such issues are data collection and energy conservation. We consider a mobile robot, or a mobile agent, traveling the network collecting information from the sensors themselves before their onboard memory storage buffers are full. A novel algorithm is presented that is an adaptation of a local search algorithm for a special case of the Asymmetric Traveling Salesman Problem with Time-windows (ATSPTW) for solving the dynamic scheduling problem of what nodes are to be visited so that the information collected is not lost. Our algorithms are given and compared to other work.

Using mobile agents to detect node compromise in path-based DoS attacks on wireless sensor networks

Wireless sensor networks represent a new generation of real-time  embedded systems with significantly different communication constraints from the traditional networked systems. With their development, a new attack called a path-based DoS (PDoS) attack has appeared. In a PDoS attack, an adversary, either inside or outside the network, overwhelms sensor nodes by flooding a multi-hop endto- end communication path with either replayed packets or injected spurious packets. In this article, we propose a solution using mobile agents which can detect PDoS attacks easily.

Using mobile agents to detect and recover from node compromise in path-based DoS attacks in wireless sensor networks

Wireless sensor networks represent a new generation of real-time embedded systems with significantly different communication constraints from the traditional networked systems. With their development, a new attack called a path-based DoS (PDoS) attack has appeared. In a PDoS attack, an adversary, either inside or outside the network, overwhelms sensor nodes by flooding a multi-hop end-to end communication path with either replayed packets or injected spurious packets. Detection and recovery from PDoS attacks have not been given much attention in the literature. In this article, we propose a solution using mobile agents which can detect PDoS attacks easily and efficiently and recover the compromised nodes.

Surface modification and bleaching of pigmented wool

We treat naturally pigmented karakul wool with a surface modification system of chlorination and catalytic bleaching, then examine its structure and properties. SEM photos reveal the surface morphology of karakul wool, and the Allworden reaction shows the extent of damage to the epicuticle. The results show that the surface modification removes the bulk of the fiber scales and bleaching increases fiber whiteness. After bleaching, the felting propensity of karakul wool improves slightly and its dye uptake decreases. For modified and bleached karakul wool, the felting propensity decreases, the dyeing rate increases, and equilibrium exhaustion decreases compared with untreated karakul wool.

Environmental factors affecting transcription of the human L1 retrotransposon. I. Steroid hormone-like agents

The L1 retrotransposon has significantly shaped the structure of the human genome. At least 30% of human genome sequence can be attributed to L1 reverse transcriptase activity. There are 105 copies of the human L1 retrotransposon, L1Hs, most of which are defective, although ~8–9x103 are full length. L1Hs elements transpose through an RNA intermediate and transcription is thought to be the rate limiting step in retrotransposition. Because transcription of retrotransposons in a variety of organisms has been shown to respond to environmental stimuli, we investigated the influence of various agents on transcription from two different L1Hs promoters. The activity of the L1Hs promoters was analyzed by transfecting L1Hs-expressing cell lines with plasmids containing the L1Hs promoters fused to the LacZ reporter gene and monitoring expression with a ß-galactosidase assay. Small increases in ß-galactosidase activity were observed with both L1Hs promoters after treatment with serum, testosterone, dihydrotestosterone and organochloride pesticides, indicating that these agents can influence L1Hs transcription.

Marketing research and small travel agents: an exploratory study

The research study reported on in this paper examined the marketing research (MR) orientation of small Australian travel agents. A survey was undertaken involving personal interviews with 91 travel agents in Melbourne, each agency having fewer than 20 employees. Agents were asked about their organisation with regard to MR, which MR activities were undertaken and wich MR techniques were employed. Additional questions gathered data on organisational and individual demographics, and some perceptual and attitudinal data. Although approximately half the respondents had no employee assigned to MR, the majority of agents reported engaging in most of the MR activities nominated, although most agents did not use most of the MR techniques covered in the study. Most general demographics were not related to MR participation, although greater devotion of resources to MR was reflected in more comprehensive usage of MR, and a more positive attitude to the cost-effectiveness of MR in small organisations. The desirability of travel agents considering seriously the role of MR in assisting in clarifying the future options for the sector is noted.

Agents and data mining: mutual enhancement by integration

This paper tells a story of synergism of two cutting edge technologies — agents and data mining. By integrating these two technologies, the power for each of them is enhanced. Integrating agents into data mining systems, or constructing data mining systems from agent perspectives, the flexibility of data mining systems can be greatly improved. New data mining techniques can add to the systems dynamically in the form of agents, while the out-of-date ones can also be deleted from systems at run-time. Equipping agents with data mining capabilities, the agents are much smarter and more adaptable. In this way, the performance of these agent systems can be improved. A new way to integrate these two techniques –ontology-based integration is also discussed. Case studies will be given to demonstrate such mutual enhancement.

Syntheses of Cross-Linking Agents, Molecular Modeling of Oligonucleotides and Polypeptide-Ion Complexes

Each section of this thesis will be subdivided into three parts encompassing all of the research in which I have been involved during the past three years. These will be referred to under the headings "Syntheses:' "Molecular Modeling," and "Cross-linking Efficiencies." Each of these subdivisions may have divisions within them when necessary in order to fully detail the research.

Novel agents that potentially inhibit irinotecan-induced diarrhea

Irinotecan (CPT-11, 7-ethyl-10-[4-(1-piperidino)-1-piperidino] carbonyloxycamptothecin) has exhibited clinical activities against a broad spectrum of carcinomas by inhibiting DNA topoisomerase I (Topo I). However, severe and unpredictable dosing-limiting toxicities (mainly myelosuppression and severe diarrhea) hinder its clinical use. The latter consists of early and late-onset diarrhea, occurring within 24 hr or ≥ 24 hr after CPT-11 administration, respectively. This review highlights novel agents potentially inhibiting CPT-11-induced diarrhea, which are designed and tested under guidance of disposition pathways and potential toxicity mechanisms. Early-onset diarrhea is observed immediately after CPT-11 infusion and probably due to the inhibition of acetylcholinesterase activity, which can be eliminated by administration of atropine. Lateonset diarrhea appears to be associated with intestinal exposure to SN-38 (7-ethyl-10-hydroxycamptothecin), the major active metabolite of CPT-11, which may bind to Topo I and induce apoptosis of intestinal epithelia, leading to the disturbance in the absorptive and secretory functions of mucosa. CPT-11 and SN-38 may also stimulate the production of pro-inflammatory cytokines and prostaglandins (PGs), thus inducing the secretion of Na⁺ and Cl^-. Early treatment of severe late-onset diarrhea with oral high-dose loperamide has decreased patient morbidity. Extensive studies have been conducted to identify other potential agents to ameliorate diarrhea in preclinical and clinical models. These include intestinal alkalizing agents, oral antibiotics, enzyme inducers, P-glycoprotein (PgP) inhibitors, cyclooxygenase-2 (COX-2) inhibitors, tumor necrosis factor-agr (TNF-α) inhibitors, or blockers of biliary excretion of SN-38. Further studies are needed to identify the molecular targets associated with CPT-11 toxicity and safe and effective agents for alleviating CPT-11-induced diarrhea.

Making decisions for intelligent agents in procedure descriptive framework

There are many existing and potential industrial and commercial applications for intelligent agents in the literature. The very challenging issue for these applications is to "do what intelligent agents should do". The BDI (beliefs, desires, intentions) architecture is presented to solve this challenge, and it has attracted much attention. The main difficulty for this architecture is the formalization problem. In this paper, we discuss the "procedure descriptive framework", which is a method for formalizing the BDI architecture. We present decision models for intelligent agents in this framework. This research provides a technique for online agents to form beliefs and make decisions according to the current uncertain environment

Decision model for BDI-based intelligent agents

The very challenging issue for intelligent agents is “do what they should do”. The BDI architecture is presented to solve this challenge. The main difficult for this architecture is the formalizing problem. In this paper, we discuss the procedure descriptive framework, which presents a method for formalizing BDI architecture. We a present decision model for intelligent agents in this procedure descriptive framework. This research shows how an agent to generate beliefs and make decisions by using its current beliefs.