Construction of Intelligent Virtual Worlds Using a Grammatical Framework

The potential of integrating multiagent systems and virtual environments has not been exploited to its whole extent. This paper proposes a model based on grammars, called Minerva, to construct complex virtual environments that integrate the features of agents. A virtual world is described as a set of dynamic and static elements. The static part is represented by a sequence of primitives and transformations and the dynamic elements by a series of agents. Agent activation and communication is achieved using events, created by the so-called event generators. The grammar defines a descriptive language with a simple syntax and a semantics, defined by functions. The semantics functions allow the scene to be displayed in a graphics device, and the description of the activities of the agents, including artificial intelligence algorithms and reactions to physical phenomena. To illustrate the use of Minerva, a practical example is presented: a simple robot simulator that considers the basic features of a typical robot. The result is a functional simple simulator. Minerva is a reusable, integral, and generic system, which can be easily scaled, adapted, and improved. The description of the virtual scene is independent from its representation and the elements that it interacts with.

An intelligent approach for deploying applications in WSN's

Wireless sensor networks have been identified as one of the key technologies for the 21st century. They consist of tiny devices with limited processing and power capabilities, called motes that can be deployed in large numbers of useful sensing capabilities. Even though, they are flexible and easy to deploy, there are a number of considerations when it comes to their fault tolerance, conserving energy and re-programmability that need to be addressed before we draw any substantial conclusions about the effectiveness of this technology. In order to overcome their limitations, we propose a middleware solution. The proposed scheme is composed based on two main methods. The first method involves the creation of a flexible communication protocol based on technologies such as Mobile Code/Agents and Linda-like tuple spaces. In this way, every node of the wireless sensor network will produce and process data based on what is the best for it but also for the group that it belongs too. The second method incorporates the above protocol in a middleware that will aim to bridge the gap between the application layer and low level constructs such as the physical layer of the wireless sensor network. A fault tolerant platform for deploying and monitoring applications in real time offers a number of possibilities for the end user giving him in parallel the freedom to experiment with various parameters, in an effort towards the deployed applications running in an energy efficient manner inside the network. The proposed scheme is evaluated through a number of trials aiming to test its merits under real time conditions and to identify its effectiveness against other similar approaches. Finally, parameters which determine the characteristics of the proposed scheme are also examined.

Making motes intelligent:an agent-based approach to wireless sensor networks

In-Motes is a mobile agent middleware that generates an intelligent framework for deploying applications in Wireless Sensor Networks (WSNs). In-Motes is based on the injection of mobile agents into the network that can migrate or clone following specific rules and performing application specific tasks. By doing so, each mote is given a certain degree of perception, cognition and control, forming the basis for its intelligence. Our middleware incorporates technologies such as Linda-like tuplespaces and federated system architecture in order to obtain a high degree of collaboration and coordination for the agent society. A set of behavioral rules inspired by a community of bacterial strains is also generated as the means for robustness of the WSN. In this paper, we present In-Motes and provide a detailed evaluation of its implementation for MICA2 motes.

Knowledge Construction Technology through Hypermedia-Based Intelligent Conversational Channel

There have been multifarious approaches in building expert knowledge in medical or engineering field through expert system, case-based reasoning, model-based reasoning and also a large-scale knowledge-based system. The intriguing factors with these approaches are mainly the choices of reasoning mechanism, ontology, knowledge representation, elicitation and modeling. In our study, we argue that the knowledge construction through hypermedia-based community channel is an effective approach in constructing expert’s knowledge. We define that the knowledge can be represented as in the simplest form such as stories to the most complex ones such as on-the-job type of experiences. The current approaches of encoding experiences require expert’s knowledge to be acquired and represented in rules, cases or causal model. We differentiate the two types of knowledge which are the content knowledge and socially-derivable knowledge. The latter is described as knowledge that is earned through social interaction. Intelligent Conversational Channel is the system that supports the building and sharing on this type of knowledge.

Learning Data-Driven Models of Non-Verbal Behaviors for Building Rapport Using an Intelligent Virtual Agent

There is a growing societal need to address the increasing prevalence of behavioral health issues, such as obesity, alcohol or drug use, and general lack of treatment adherence for a variety of health problems. The statistics, worldwide and in the USA, are daunting. Excessive alcohol use is the third leading preventable cause of death in the United States (with 79,000 deaths annually), and is responsible for a wide range of health and social problems. On the positive side though, these behavioral health issues (and associated possible diseases) can often be prevented with relatively simple lifestyle changes, such as losing weight with a diet and/or physical exercise, or learning how to reduce alcohol consumption. Medicine has therefore started to move toward finding ways of preventively promoting wellness, rather than solely treating already established illness. Evidence-based patient-centered Brief Motivational Interviewing (BMI) interven- tions have been found particularly effective in helping people find intrinsic motivation to change problem behaviors after short counseling sessions, and to maintain healthy lifestyles over the long-term. Lack of locally available personnel well-trained in BMI, however, often limits access to successful interventions for people in need. To fill this accessibility gap, Computer-Based Interventions (CBIs) have started to emerge. Success of the CBIs, however, critically relies on insuring engagement and retention of CBI users so that they remain motivated to use these systems and come back to use them over the long term as necessary. Because of their text-only interfaces, current CBIs can therefore only express limited empathy and rapport, which are the most important factors of health interventions. Fortunately, in the last decade, computer science research has progressed in the design of simulated human characters with anthropomorphic communicative abilities. Virtual characters interact using humans’ innate communication modalities, such as facial expressions, body language, speech, and natural language understanding. By advancing research in Artificial Intelligence (AI), we can improve the ability of artificial agents to help us solve CBI problems. To facilitate successful communication and social interaction between artificial agents and human partners, it is essential that aspects of human social behavior, especially empathy and rapport, be considered when designing human-computer interfaces. Hence, the goal of the present dissertation is to provide a computational model of rapport to enhance an artificial agent’s social behavior, and to provide an experimental tool for the psychological theories shaping the model. Parts of this thesis were already published in [LYL+12, AYL12, AL13, ALYR13, LAYR13, YALR13, ALY14].

Exploiting Learning Technologies for World Wide Web Agents

Postprint

Using SPL to Develop AAL Systems Based on Self-adaptive Agents

Abstract One of the most important challenges of this decade is the Internet of Things (IoT) that pursues the integration of real-world objects in Internet. One of the key areas of the IoT is the Ambient Assisted Living (AAL) systems, which should be able to react to variable and continuous changes while ensuring their acceptance and adoption by users. This means that AAL systems need to work as self-adaptive systems. The autonomy property inherent to software agents, makes them a suitable choice for developing self-adaptive systems. However, agents lack the mechanisms to deal with the variability present in the IoT domain with regard to devices and network technologies. To overcome this limitation we have already proposed a Software Product Line (SPL) process for the development of self-adaptive agents in the IoT. Here we analyze the challenges that poses the development of self-adaptive AAL systems based on agents. To do so, we focus on the domain and application engineering of the self-adaptation concern of our SPL process. In addition, we provide a validation of our development process for AAL systems.

Learning data-driven models of non-verbal behaviors for building rapport using an intelligent virtual agent

There is a growing societal need to address the increasing prevalence of behavioral health issues, such as obesity, alcohol or drug use, and general lack of treatment adherence for a variety of health problems. The statistics, worldwide and in the USA, are daunting. Excessive alcohol use is the third leading preventable cause of death in the United States (with 79,000 deaths annually), and is responsible for a wide range of health and social problems. On the positive side though, these behavioral health issues (and associated possible diseases) can often be prevented with relatively simple lifestyle changes, such as losing weight with a diet and/or physical exercise, or learning how to reduce alcohol consumption. Medicine has therefore started to move toward finding ways of preventively promoting wellness, rather than solely treating already established illness.^ Evidence-based patient-centered Brief Motivational Interviewing (BMI) interventions have been found particularly effective in helping people find intrinsic motivation to change problem behaviors after short counseling sessions, and to maintain healthy lifestyles over the long-term. Lack of locally available personnel well-trained in BMI, however, often limits access to successful interventions for people in need. To fill this accessibility gap, Computer-Based Interventions (CBIs) have started to emerge. Success of the CBIs, however, critically relies on insuring engagement and retention of CBI users so that they remain motivated to use these systems and come back to use them over the long term as necessary.^ Because of their text-only interfaces, current CBIs can therefore only express limited empathy and rapport, which are the most important factors of health interventions. Fortunately, in the last decade, computer science research has progressed in the design of simulated human characters with anthropomorphic communicative abilities. Virtual characters interact using humans’ innate communication modalities, such as facial expressions, body language, speech, and natural language understanding. By advancing research in Artificial Intelligence (AI), we can improve the ability of artificial agents to help us solve CBI problems.^ To facilitate successful communication and social interaction between artificial agents and human partners, it is essential that aspects of human social behavior, especially empathy and rapport, be considered when designing human-computer interfaces. Hence, the goal of the present dissertation is to provide a computational model of rapport to enhance an artificial agent’s social behavior, and to provide an experimental tool for the psychological theories shaping the model. Parts of this thesis were already published in [LYL+12, AYL12, AL13, ALYR13, LAYR13, YALR13, ALY14].^

An investigation of two real time machine learning techniques that could enhance the adaptability of game AI agents

Developers strive to create innovative Artificial Intelligence (AI) behaviour in their games as a key selling point. Machine Learning is an area of AI that looks at how applications and agents can be programmed to learn their own behaviour without the need to manually design and implement each aspect of it. Machine learning methods have been utilised infrequently within games and are usually trained to learn offline before the game is released to the players. In order to investigate new ways AI could be applied innovatively to games it is wise to explore how machine learning methods could be utilised in real-time as the game is played, so as to allow AI agents to learn directly from the player or their environment. Two machine learning methods were implemented into a simple 2D Fighter test game to allow the agents to fully showcase their learned behaviour as the game is played. The methods chosen were: Q-Learning and an NGram based system. It was found that N-Grams and QLearning could significantly benefit game developers as they facilitate fast, realistic learning at run-time.

Revêtement intelligent à base des silices mésoporeuses fonctionnalisées pour le relargage stimulé d’agents antimicrobiens

Les biofilms bactériens sont composés d’organismes unicellulaires vivants au sein d’une matrice protectrice, formée de macromolécules naturelles. Des biofilms non désirés peuvent avoir un certain nombre de conséquences néfastes, par exemple la diminution du transfert de chaleur dans les échangeurs de chaleurs, l’obstruction de membranes poreuses, la contamination des surfaces coques de navires, etc. Par ailleurs, les bactéries pathogènes qui prolifèrent dans un biofilm posent également un danger pour la santé s’ils croissent sur des surfaces médicales synthétiques comme des implants biomédicaux, cathéters ou des lentilles de vue. De plus, la croissance sur le tissu naturel par certaines souches des bactéries peut être fatale, comme Pseudomonas aeruginosa dans les poumons. Cependant, la présence de biofilms reste difficile à traiter, car les bactéries sont protégées par une matrice extracellulaire. Pour tenter de remédier à ces problèmes, nous proposons de développer une surface antisalissure (antifouling) qui libère sur demande des agents antimicrobiens. La proximité et la disposition du système de relargage placé sous le biofilm, assureront une utilisation plus efficace des molécules antimicrobiennes et minimiseront les effets secondaires de ces dernières. Pour ce faire, nous envisageons l’utilisation d’une couche de particules de silice mésoporeuses comme agents de livraison d’agents antimicrobiens. Les nanoparticules de silice mésoporeuses (MSNs) ont démontré un fort potentiel pour la livraison ciblée d’agents thérapeutiques et bioactifs. Leur utilisation en nano médecine découle de leurs propriétés de porosité intéressantes, de la taille et de la forme ajustable de ces particules, de la chimie de leur surface et leur biocompatibilité. Ces propriétés offrent une flexibilité pour diverses applications. De plus, il est possible de les charger avec différentes molécules ou biomolécules (de tailles variées, allant de l’ibuprofène à l’ARN) et d’exercer un contrôle précis des paramètres d’adsorption et des cinétiques de relargage (désorption). Mots Clés : biofilms, nanoparticules de silice mésoporeuses, microfluidique, surface antisalissure.

Comparison Of The Solution Of Histidine-tryptophan-alfacetoglutarate With Histidine-tryptophan-glutamate As Cardioplegic Agents In Isolated Rat Hearts: An Immunohistochemical Study.

Cardiac arrest during heart surgery is a common procedure and allows the surgeon to perform surgical procedures in an environment free of blood and movement. Using a model of isolated rat heart, the authors compare a new cardioplegic solution containing histidine-tryptophan-glutamate (group 2) with the histidine-tryptophan-alphacetoglutarate (group 1) routinely used by some cardiac surgeons. To assess caspase, IL-8 and KI-67 in isolated rat hearts using immunohistochemistry. 20 Wistar male rats were anesthetized and heparinized. The chest was opened, cardioctomy was performed and 40 ml/kg of the appropriate cardioplegic solution was infused. The hearts were kept for 2 hours at 4ºC in the same solution, and thereafter, placed in the Langendorff apparatus for 30 minutes with Ringer-Locke solution. Immunohistochemistry analysis of caspase, IL-8, and KI-67 were performed. The concentration of caspase was lower in group 2 and Ki-67 was higher in group 2, both P<0.05. There was no statistical difference between the values of IL-8 between the groups. Histidine-tryptophan-glutamate solution was better than histidine-tryptophan-alphacetoglutarate solution because it reduced caspase (apoptosis), increased KI-67 (cell proliferation), and showed no difference in IL-8 levels compared to group 1. This suggests that the histidine-tryptophan-glutamate solution was more efficient than the histidine-tryptophan-alphacetoglutarate for the preservation of hearts of rat cardiomyocytes.

Perianal Complete Remission With Combined Therapy (seton Placement And Anti-tnf Agents) In Crohn's Disease: A Brazilian Multicenter Observational Study.

Perianal fistulizing Crohn's disease is one of the most severe phenotypes of inflammatory bowel diseases. Combined therapy with seton placement and anti-TNF therapy is the most common strategy for this condition. The aim of this study was to analyze the rates of complete perianal remission after combined therapy for perianal fistulizing Crohn's disease. This was a retrospective observational study with perianal fistulizing Crohn's disease patients submitted to combined therapy from four inflammatory bowel diseases referral centers. We analyzed patients' demographic characteristics, Montreal classification, concomitant medication, classification of the fistulae, occurrence of perianal complete remission and recurrence after remission. Complete perianal remission was defined as absence of drainage from the fistulae associated with seton removal. A total of 78 patients were included, 44 (55.8%) females with a mean age of 33.8 (±15) years. Most patients were treated with Infliximab, 66.2%, than with Adalimumab, 33.8%. Complex fistulae were found in 52/78 patients (66.7%). After a medium follow-up of 48.2 months, 41/78 patients (52.6%) had complete perianal remission (95% CI: 43.5%-63.6%). Recurrence occurred in four (9.8%) patients (95% CI: 0.7%-18.8%) in an average period of 74.8 months. Combined therapy lead to favorable and durable results in perianal fistulizing Crohn's disease.

Correlation between margin fit and microleakage in complete crowns cemented with three luting agents

Microleakage can be related to margin misfit. Also, traditional microleakage techniques are time-consuming. This study evaluated the existence of correlation between in vitro margin fit and a new microleakage technique for complete crowns cemented with 3 different luting agents. Thirty human premolars were prepared for full-coverage crowns with a convergence angle of 6 degrees, chamfer margin of 1.2 mm circumferentially, and occlusal reduction of 1.5 mm. Ni-Cr cast crowns were cemented with either zinc phosphate (ZP) (S.S. White), resin-modified glass-ionomer (RMGI) (Rely X Luting Cement) or a resin-based luting agent (RC) (Enforce). Margin fit (seating discrepancy and margin gap) was evaluated according to criteria in the literature under microscope with 0.001 mm accuracy. After thermal cycling, crowns were longitudinally sectioned and microleakage scores at tooth-cement interface were obtained and recorded at &times;100 magnification. Margin fit parameters were compared with the one-way ANOVA test and microleakage scores with Kruskal-Wallis and Dunn's tests (alpha=0.05). Correlation between margin fit and microleakage was analyzed with the Spearman's test (alpha=0.05). Seating discrepancy and marginal gap values ranged from 81.82 &micro;m to 137.22 &micro;m (p=0.117), and from 75.42 &micro;m to 78.49 &micro;m (p=0.940), respectively. Marginal microleakage scores were ZP=3.02, RMGI=0.35 and RC=0.12 (p<0.001), with no differences between RMGI and RC scores. The correlation coefficient values ranged from -0.27 to 0.30 (p>0.05). Conclusion: Margin fit parameters and microleakage showed no strong correlations; cast crowns cemented with RMGI and RC had lower microleakage scores than ZP cement.

Comparison among four commonly used demineralizing agents for root conditioning: a scanning electron microscopy

Dental roots that have been exposed to the oral cavity and periodontal pocket environment present superficial changes, which can prevent connective tissue reattachment. Demineralizing agents have been used as an adjunct to the periodontal treatment aiming at restoring the biocompatibility of roots. OBJECTIVE: This study compared four commonly used demineralizing agents for their capacity of removing smear layer and opening dentin tubules. METHODS: Fifty fragments of human dental roots previously exposed to periodontal disease were scaled and randomly divided into the following groups of treatment: 1) CA: demineralization with citric acid for 3 min; 2) TC-HCl: demineralization with tetracycline-HCl for 3 min; 3) EDTA: demineralization with EDTA for 3 min; 4) PA: demineralization with 37% phosphoric acid for 3 min; 5) Control: rubbing of saline solution for 3 min. Scanning electron microscopy was used to check for the presence of residual smear layer and for measuring the number and area of exposed dentin tubules. RESULTS: Smear layer was present in 100% of the specimens from the groups PA and control; in 80% from EDTA group; in 33.3% from TC-HCl group and 0% from CA group. The mean numbers of exposed dentin tubules in a standardized area were: TC-HCl=43.8±25.2; CA=39.3±37; PA=12.1±16.3; EDTA=4.4±7.5 and Control=2.3±5.7. The comparison showed significant differences between the following pairs of groups: TC-HCl and Control; TC-HCl and EDTA; CA and Control; and CA and EDTA. The mean percentages of area occupied by exposed dentin tubules were: CA=0.12±0.17%; TC-HCl=0.08±0.06%; PA=0.03±0.05%; EDTA=0.01±0.01% and Control=0±0%. The CA group differed significantly from the others except for the TC-HCl group. CONCLUSION: There was a decreasing ability for smear layer removal and dentin tubule widening as follows: AC>TC-HCl>PA>EDTA. This information can be of value as an extra parameter for choosing one of them for root conditioning.

Flavoring agents present in a dentifrice can modify volatile sulphur compounds (VSCs) formation in morning bad breath

This study aimed to evaluate the effects of a flavor-containing dentifrice on the formation of volatile sulphur compounds (VSCs) in morning bad breath. A two-step, blinded, crossover, randomized study was carried out in 50 dental students with a healthy periodontium divided into two experimental groups: flavor-containing dentifrice (test) and non-flavor-containing dentifrice (control). The volunteers received the designated dentifrice and a new toothbrush for a 3 X/day brushing regimen for 2 periods of 30 days. A seven-day washout interval was used between the periods. The assessed parameters were: plaque index (PI), gingival index (GI), organoleptic breath scores (ORG), VSC levels (as measured by a portable sulphide monitor) before (H1) and after (H2) cleaning of the tongue, tongue coating (TC) wet weight and BANA test from TC samples. The intra-group analysis showed a decrease in ORG, from 3 to 2, after 30 days for the test group (p < 0.05). The inter-group analysis showed lower values in ORG, H1 and H2 for the test group (p < 0.05). There was no difference between the amount of TC between groups and the presence of flavor also did not interfere in the BANA results between groups (p > 0.05). These findings suggest that a flavor-containing dentifrice seems to prevent VSCs formation in morning bad breath regardless of the amount of TC in periodontally healthy subjects.