Performing for (and against) the microphone : personal takes : producing a credible vocal

This contribution proposes the effect of the studio practice compiling vocals from many takes on the performance of vocalists.

Detection and prevention of distributed denial of services attacks by collaborative effort of software agents, first prototype implementation

Distributed Denial of Services DDoS, attacks has become one of the biggest threats for resources over Internet. Purpose of these attacks is to make servers deny from providing services to legitimate users. These attacks are also used for occupying media bandwidth. Currently intrusion detection systems can just detect the attacks but cannot prevent / track the location of intruders. Some schemes also prevent the attacks by simply discarding attack packets, which saves victim from attack, but still network bandwidth is wasted. In our opinion, DDoS requires a distributed solution to save wastage of resources. The paper, presents a system that helps us not only in detecting such attacks but also helps in tracing and blocking (to save the bandwidth as well) the multiple intruders using Intelligent Software Agents. The system gives dynamic response and can be integrated with the existing network defense systems without disturbing existing Internet model. We have implemented an agent based networking monitoring system in this regard.

In the Rough : In-Field evaluation of an autonomous vehicle for golf course maintenance

Maintenance is a time consuming and expensive task for any golf course or driving range manager. For a golf course the primary tasks are grass mowing and maintenance (fertilizer and herbicide spreading), while for a driving range mowing, maintenance and ball collection are required. All these tasks require an operator to drive a vehicle along paths which are generally predefined. This paper presents some preliminary in-field tsting results for an automated tractor vehicle performing golf ball collection on an actual driving range, and mowing on difficult unstructured terrain.

Gamma-tocotrienol as an effective agent in targeting prostate cancer stem cell-like population

Emerging evidence supports that prostate cancer originates from a rare sub-population of cells, namely prostate cancer stem cells (CSCs). Conventional therapies for prostate cancer are believed to mainly target the majority of differentiated tumor cells but spare CSCs, which may account for the subsequent disease relapse after treatment. Therefore, successful elimination of CSCs may be an effective strategy to achieve complete remission from this disease. Gamma-tocotrienols (-T3) is one of the vitamin-E constituents which have been shown to have anticancer effects against a wide-range of human cancers. Recently, we have reported that -T3 treatment not only inhibits prostate cancer cell invasion but also sensitizes the cells to docetaxel-induced apoptosis, suggesting that -T3 may be an effective therapeutic agent against advanced stage prostate cancer. Here, we demonstrate for the first time that -T3 can down-regulate the expression of prostate CSC markers (CD133/CD44) in androgen independent (AI) prostate cancer cell lines (PC-3 & DU145), as evident from western blotting analysis. Meanwhile, the spheroid formation ability of the prostate cancer cells was significantly hampered by -T3 treatment. In addition, pre-treatment of PC-3 cells with -T3 was found to suppress tumor initiation ability of the cells. More importantly, while CD133-enriched PC-3 cells were highly resistant to docetaxel treatment, these cells were as sensitive to -T3 treatment as the CD133-depleted population. Our data suggest that -T3 may be an effective agent in targeting prostate CSCs, which may account for its anticancer and chemosensitizing effects reported in previous studies.

Multi-modal object tracking using dynamic performance metrics

Intelligent surveillance systems typically use a single visual spectrum modality for their input. These systems work well in controlled conditions, but often fail when lighting is poor, or environmental effects such as shadows, dust or smoke are present. Thermal spectrum imagery is not as susceptible to environmental effects, however thermal imaging sensors are more sensitive to noise and they are only gray scale, making distinguishing between objects difficult. Several approaches to combining the visual and thermal modalities have been proposed, however they are limited by assuming that both modalities are perfuming equally well. When one modality fails, existing approaches are unable to detect the drop in performance and disregard the under performing modality. In this paper, a novel middle fusion approach for combining visual and thermal spectrum images for object tracking is proposed. Motion and object detection is performed on each modality and the object detection results for each modality are fused base on the current performance of each modality. Modality performance is determined by comparing the number of objects tracked by the system with the number detected by each mode, with a small allowance made for objects entering and exiting the scene. The tracking performance of the proposed fusion scheme is compared with performance of the visual and thermal modes individually, and a baseline middle fusion scheme. Improvement in tracking performance using the proposed fusion approach is demonstrated. The proposed approach is also shown to be able to detect the failure of an individual modality and disregard its results, ensuring performance is not degraded in such situations.

Construction, application and validation of selection evaluation model (SEM) for intelligent HVAC control system

Design teams are confronted with the quandary of choosing apposite building control systems to suit the needs of particular intelligent building projects, due to the availability of innumerable ‘intelligent’ building products and a dearth of inclusive evaluation tools. This paper is organised to develop a model for facilitating the selection evaluation for intelligent HVAC control systems for commercial intelligent buildings. To achieve these objectives, systematic research activities have been conducted to first develop, test and refine the general conceptual model using consecutive surveys; then, to convert the developed conceptual framework into a practical model; and, finally, to evaluate the effectiveness of the model by means of expert validation. The results of the surveys are that ‘total energy use’ is perceived as the top selection criterion, followed by the‘system reliability and stability’, ‘operating and maintenance costs’, and ‘control of indoor humidity and temperature’. This research not only presents a systematic and structured approach to evaluate candidate intelligent HVAC control system against the critical selection criteria (CSC), but it also suggests a benchmark for the selection of one control system candidate against another.

Intelligent negotiation behaviour model for an open railway access market

In an open railway access market, the provisions of railway infrastructures and train services are separated and independent. Negotiations between the track owner and train service providers are thus required for the allocation of the track capacity and the formulation of the services timetables, in which each party, i.e. a stakeholder, exhibits intelligence from the previous negotiation experience to obtain the favourable terms and conditions for the track access. In order to analyse the realistic interacting behaviour among the stakeholders in the open railway access market schedule negotiations, intelligent learning capability should be included in the behaviour modelling. This paper presents a reinforcement learning approach on modelling the intelligent negotiation behaviour. The effectiveness of incorporating learning capability in the stakeholder negotiation behaviour is then demonstrated through simulation.

A prioritised fuzzy constraint satisfaction approach to model agent negotiation for railway scheduling

With the recent regulatory reforms in a number of countries, railways resources are no longer managed by a single party but are distributed among different stakeholders. To facilitate the operation of train services, a train service provider (SP) has to negotiate with the infrastructure provider (IP) for a train schedule and the associated track access charge. This paper models the SP and IP as software agents and the negotiation as a prioritized fuzzy constraint satisfaction (PFCS) problem. Computer simulations have been conducted to demonstrate the effects on the train schedule when the SP has different optimization criteria. The results show that by assigning different priorities on the fuzzy constraints, agents can represent SPs with different operational objectives.

The development of Lactococcus lactis as an antimicrobial agent

Non-pathogenic lactic acid bacteria are economically important Gram-positive bacteria used extensively in the food industry. Due to their “generally regarded as safe” status, certain species from the genera Lactobacillus and Lactococcus are also considered desirable as candidates for the production and secretion of recombinant proteins, particular those with therapeutic applications. The hypothesis examined by this thesis is that Lactococcus lactis can be modified to be an effective antimicrobial agent. Therefore, the aims of this thesis were to investigate the optimisation of the expression, secretion and/or activities of potential heterologous antimicrobial proteins by the model lactic acid bacterium, Lactococcus lactis subsp. cremoris MG1363. L. lactis strains were engineered to express and secrete the recombinant CyuC surface protein from Lactobacillus reuteri BR11, and a fusion protein consisting of CyuC and lysostaphin using the Sep promoter and secretion signal. CyuC has been characterised as a cystine-binding protein, but has also been demonstrated to have fibronectin binding activity. Lysostaphin is a bacteriolytic enzyme with specific activity against the Gram-positive pathogen, Staphylococcus aureus. These modified L. lactis strains were then investigated to see if they had the ability to inhibit the adhesion of S. aureus to host extracellular matrix (ECM) proteins. It was observed that the cell extracts of the L. lactis strain with the vector only (pGhost9:ISS1) was able to inhibit the adhesion of S. aureus to fibronectin, whilst the cell extracts of the L. lactis strain expressing lysostaphin was able to inhibit adhesion to keratin. Finally, this thesis has identified specific lactococcal genes that affect the secretion of lysostaphin through the use of random transposon mutagenesis. Ten mutants with higher lysostaphin activity contained insertions in four different genes encoding: (i) an uncharacterised putative transmembrane protein (llmg_0609), (ii) an enzyme catalysing the first step in peptidoglycan biosynthesis (murA2), (iii) a homolog of the oxidative defence regulator (trmA), and (iv) an uncharacterised putative enzyme involved in ubiquinone biosynthesis (llmg_2148). The higher lysostaphin activity observed in these mutants was found to be due to higher amounts of lysostaphin being secreted. The findings of this thesis contribute to the development of this organism as an antimicrobial agent and also to our understanding of L. lactis genetics.