980 resultados para ecliptic curve based chameleon hashing


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This paper describes a Multi-agent Scheduling System that assumes the existence of several Machines Agents (which are decision-making entities) distributed inside the Manufacturing System that interact and cooperate with other agents in order to obtain optimal or near-optimal global performances. Agents have to manage their internal behaviors and their relationships with other agents via cooperative negotiation in accordance with business policies defined by the user manager. Some Multi Agent Systems (MAS) organizational aspects are considered. An original Cooperation Mechanism for a Team-work based Architecture is proposed to address dynamic scheduling using Meta-Heuristics.

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As the time goes on, it is a question of common sense to involve in the process of decision making people scattered around the globe. Groups are created in a formal or informal way, exchange ideas or engage in a process of argumentation and counterargumentation, negotiate, cooperate, collaborate or even discuss techniques and/or methodologies for problem solving. In this work it is proposed an agent-based architecture to support a ubiquitous group decision support system, i.e. based on the concept of agent, which is able to exhibit intelligent, and emotional-aware behaviour, and support argumentation, through interaction with individual persons or groups. It is enforced the paradigm of Mixed Initiative Systems, so the initiative is to be pushed by human users and/or intelligent agents.

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Group decision making plays an important role in organizations, especially in the present-day economy that demands high-quality, yet quick decisions. Group decision-support systems (GDSSs) are interactive computer-based environments that support concerted, coordinated team efforts toward the completion of joint tasks. The need for collaborative work in organizations has led to the development of a set of general collaborative computer-supported technologies and specific GDSSs that support distributed groups (in time and space) in various domains. However, each person is unique and has different reactions to various arguments. Many times a disagreement arises because of the way we began arguing, not because of the content itself. Nevertheless, emotion, mood, and personality factors have not yet been addressed in GDSSs, despite how strongly they influence results. Our group’s previous work considered the roles that emotion and mood play in decision making. In this article, we reformulate these factors and include personality as well. Thus, this work incorporates personality, emotion, and mood in the negotiation process of an argumentbased group decision-making process. Our main goal in this work is to improve the negotiation process through argumentation using the affective characteristics of the involved participants. Each participant agent represents a group decision member. This representation lets us simulate people with different personalities. The discussion process between group members (agents) is made through the exchange of persuasive arguments. Although our multiagent architecture model4 includes two types of agents—the facilitator and the participant— this article focuses on the emotional, personality, and argumentation components of the participant agent.

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Involving groups in important management processes such as decision making has several advantages. By discussing and combining ideas, counter ideas, critical opinions, identified constraints, and alternatives, a group of individuals can test potentially better solutions, sometimes in the form of new products, services, and plans. In the past few decades, operations research, AI, and computer science have had tremendous success creating software systems that can achieve optimal solutions, even for complex problems. The only drawback is that people don’t always agree with these solutions. Sometimes this dissatisfaction is due to an incorrect parameterization of the problem. Nevertheless, the reasons people don’t like a solution might not be quantifiable, because those reasons are often based on aspects such as emotion, mood, and personality. At the same time, monolithic individual decisionsupport systems centered on optimizing solutions are being replaced by collaborative systems and group decision-support systems (GDSSs) that focus more on establishing connections between people in organizations. These systems follow a kind of social paradigm. Combining both optimization- and socialcentered approaches is a topic of current research. However, even if such a hybrid approach can be developed, it will still miss an essential point: the emotional nature of group participants in decision-making tasks. We’ve developed a context-aware emotion based model to design intelligent agents for group decision-making processes. To evaluate this model, we’ve incorporated it in an agent-based simulator called ABS4GD (Agent-Based Simulation for Group Decision), which we developed. This multiagent simulator considers emotion- and argument based factors while supporting group decision-making processes. Experiments show that agents endowed with emotional awareness achieve agreements more quickly than those without such awareness. Hence, participant agents that integrate emotional factors in their judgments can be more successful because, in exchanging arguments with other agents, they consider the emotional nature of group decision making.

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This paper aims to present a multi-agent model for a simulation, whose goal is to help one specific participant of multi-criteria group decision making process.This model has five main intervenient types: the human participant, who is using the simulation and argumentation support system; the participant agents, one associated to the human participant and the others simulating the others human members of the decision meeting group; the directory agent; the proposal agents, representing the different alternatives for a decision (the alternatives are evaluated based on criteria); and the voting agent responsiblefor all voting machanisms.At this stage it is proposed a two phse algorithm. In the first phase each participantagent makes his own evaluation of the proposals under discussion, and the voting agent proposes a simulation of a voting process.In the second phase, after the dissemination of the voting results,each one ofthe partcipan agents will argue to convince the others to choose one of the possible alternatives. The arguments used to convince a specific participant are dependent on agent knowledge about that participant. This two-phase algorithm is applied iteratively.

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OBJECTIVE: To identify potential prognostic factors for neonatal mortality among newborns referred to intensive care units. METHODS: A live-birth cohort study was carried out in Goiânia, Central Brazil, from November 1999 to October 2000. Linked birth and infant death certificates were used to ascertain the cohort of live born infants. An additional active surveillance system of neonatal-based mortality was implemented. Exposure variables were collected from birth and death certificates. The outcome was survivors (n=713) and deaths (n=162) in all intensive care units in the study period. Cox's proportional hazards model was applied and a Receiver Operating Characteristic curve was used to compare the performance of statistically significant variables in the multivariable model. Adjusted mortality rates by birth weight and 5-min Apgar score were calculated for each intensive care unit. RESULTS: Low birth weight and 5-min Apgar score remained independently associated to death. Birth weight equal to 2,500g had 0.71 accuracy (95% CI: 0.65-0.77) for predicting neonatal death (sensitivity =72.2%). A wide variation in the mortality rates was found among intensive care units (9.5-48.1%) and two of them remained with significant high mortality rates even after adjusting for birth weight and 5-min Apgar score. CONCLUSIONS: This study corroborates birth weight as a sensitive screening variable in surveillance programs for neonatal death and also to target intensive care units with high mortality rates for implementing preventive actions and interventions during the delivery period.

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Background: A common task in analyzing microarray data is to determine which genes are differentially expressed across two (or more) kind of tissue samples or samples submitted under experimental conditions. Several statistical methods have been proposed to accomplish this goal, generally based on measures of distance between classes. It is well known that biological samples are heterogeneous because of factors such as molecular subtypes or genetic background that are often unknown to the experimenter. For instance, in experiments which involve molecular classification of tumors it is important to identify significant subtypes of cancer. Bimodal or multimodal distributions often reflect the presence of subsamples mixtures. Consequently, there can be genes differentially expressed on sample subgroups which are missed if usual statistical approaches are used. In this paper we propose a new graphical tool which not only identifies genes with up and down regulations, but also genes with differential expression in different subclasses, that are usually missed if current statistical methods are used. This tool is based on two measures of distance between samples, namely the overlapping coefficient (OVL) between two densities and the area under the receiver operating characteristic (ROC) curve. The methodology proposed here was implemented in the open-source R software. Results: This method was applied to a publicly available dataset, as well as to a simulated dataset. We compared our results with the ones obtained using some of the standard methods for detecting differentially expressed genes, namely Welch t-statistic, fold change (FC), rank products (RP), average difference (AD), weighted average difference (WAD), moderated t-statistic (modT), intensity-based moderated t-statistic (ibmT), significance analysis of microarrays (samT) and area under the ROC curve (AUC). On both datasets all differentially expressed genes with bimodal or multimodal distributions were not selected by all standard selection procedures. We also compared our results with (i) area between ROC curve and rising area (ABCR) and (ii) the test for not proper ROC curves (TNRC). We found our methodology more comprehensive, because it detects both bimodal and multimodal distributions and different variances can be considered on both samples. Another advantage of our method is that we can analyze graphically the behavior of different kinds of differentially expressed genes. Conclusion: Our results indicate that the arrow plot represents a new flexible and useful tool for the analysis of gene expression profiles from microarrays.

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Group decision making plays an important role in today’s organisations. The impact of decision making is so high and complex, that rarely the decision making process is made just by one individual. The simulation of group decision making through a Multi-Agent System is a very interesting research topic. The purpose of this paper it to specify the actors involved in the simulation of a group decision, to present a model to the process of group formation and to describe the approach made to implement that model. In the group formation model it is considered the existence of incomplete and negative information, which was identified as crucial to make the simulation closer to the reality.

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Valproic acid (2-propyl pentanoic acid) is a pharmaceutical drug used for treatment of epileptic seizures absence, tonic-clonic (grand mal), complex partial seizures, and mania in bipolar disorder [1]. Valproic acid is a slightly soluble in water and therefore as active pharmaceutical ingredient it is most commonly applied in form of sodium or magnesium valproate salt [1].However the list of adverse effects of these compounds is large and includes among others: tiredness, tremor, sedation and gastrointestinal disturbances [2]. Ionic liquids (ILs) are promising compounds as Active Pharmaceutical Ingredients (APIs)[3]. In this context, the combinations of the valproate anion with appropriate cation when ILs and salts are formed can significantly alter valproate physical, chemical and thermal properties.[4] This methodology can be used for drug modification (alteration of drug solubility in water, lipids, bioavailability, etc)[2] and therefore can eliminate some adverse effect of the drugs related to drug toxicity due for example to its solubility in water and lipids (interaction with intestines). Herein, we will discuss the development of ILs based on valproate anion (Figure 1) prepared according a recent optimized and sustainable acid-base neutralization method [4]. The organic cations such as cetylpyridinium, choline and imidazolium structures were selected based on their biocompatibility and recent applications in pharmacy [3]. All novel API-ILs based on valproate have been studied in terms of their physical, chemical (viscosity, density, solubility) and thermal (calorimetric studies) properties as well as their biological activity.

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In recent years Ionic Liquids (ILs) are being applied in life sciences. ILs are being produce with active pharmaceutical drugs (API) as they can reduce polymorphism and drug solubility problems [1] Also ILs are being applied as a drug delivery device in innovative therapies What is appealing in ILs is the ILs building up platform, the counter-ion can be carefully chosen in order to avoid undesirable side effects or to give innovative therapies in which two active ions are paired. This work shows ILs based on ampicillin (an anti-bacterial agent) and ILs based on Amphotericin B. Also we show studies that indicate that ILs based on Ampicillin could reverse resistance in some bacteria. The ILs produced in this work were synthetized by the neutralization method described in Ferraz et. al. [2] Ampicillin anion was combined with the following organic cations 1-ethyl-3-methylimidazolium, [EMIM]; 1-hydroxy-ethyl-3-methylimidazolium, [C2OHMIM]; choline, [cholin]; tetraethylammonium, [TEA]; cetylpyridinium, [C16pyr] and trihexyltetradecylphosphonium, [P6,6,6,14]. Amphotericin B was combined with [C16pyr], [cholin] and 1-metohyethyl-3-methylimidazolium, [C3OMIM]. The ILs-APIs based on ampicillin[2] were tested against sensitive Gram-negative bacteria Escherichia coli ATCC 25922 and Klebsiella pneumonia (clinical isolated), as well as on Gram positive Staphylococcus Aureus ATCC 25923, Staphylococcus epidermidis and Enterococcus faecalis. The arising resistance developed by bacteria to antibiotics is a serious public health threat and needs new and urgent measures. We study the bacterial activity of these compounds against a panel of resistant bacteria (clinical isolated strains): E. coli CTX M9, E. coli TEM CTX M9, E. coli TEM1, E. coli CTX M2, E. coli AmpC Mox2. In this work we demonstrate that is possible to produce ILs from anti-bacterial and anti-fungal compounds. We show here that the new ILs can reverse the bacteria resistance. With the careful choice of the organic cation, it is possible to create important biological and physic-chemical properties. This work also shows that the ion-pair is fundamental in ampicillin mechanism of action.

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Model updating methods often neglect that in fact all physical structures are damped. Such simplification relies on the structural modelling approach, although it compromises the accuracy of the predictions of the structural dynamic behaviour. In the present work, the authors address the problem of finite element (FE) model updating based on measured frequency response functions (FRFs), considering damping. The proposed procedure is based upon the complex experimental data, which contains information related to the damped FE model parameters and presents the advantage of requiring no prior knowledge about the damping matrix structure or its content, only demanding the definition of the damping type. Numerical simulations are performed in order to establish the applicability of the proposed damped FE model updating technique and its results are discussed in terms of the correlation between the simulated experimental complex FRFs and the ones obtained from the updated FE model.

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The present paper results of an ongoing research project were it is expected to develop an information system to monitoring a cultural-touristic route. The route to monitor is the Romanesque Route of Tâmega. This Route is composed of 58 monuments located in the region of Tâmega in the North of Portugal. Due to the particular location of this region, that is between coastal zone, but not yet in the inland, it has a weak political influence, and it is reflected in the low levels of development at several levels, observed. The Romanesque Route was implemented in a part of this region in 1998, and enlarged to the all-region in 2010. In order to evaluate the socio-ecomonic impact of this route in the region a research project is being developed. The main goal of this paper is to open a discussion on the elements that must be taken into consideration to evaluate the economic and social impact of a touristic cultural route within a region and this one in particular.

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Glucose sensing is an issue with great interest in medical and biological applications. One possible approach to glucose detection takes advantage of measuring changes in fluorescence resonance energy transfer (FRET) between a fluorescent donor and an acceptor within a protein which undergoes glucose-induced changes in conformation. This demands the detection of fluorescent signals in the visible spectrum. In this paper we analyzed the emission spectrum obtained from fluorescent labels attached to a protein which changes its conformation in the presence of glucose using a commercial spectrofluorometer. Different glucose nanosensors were used to measure the output spectra with fluorescent signals located at the cyan and yellow bands of the spectrum. A new device is presented based on multilayered a-SiC:H heterostructures to detect identical transient visible signals. The transducer consists of a p-i'(a-SiC:H)-n/p-i(a-Si:H)-n heterostructure optimized for the detection of the fluorescence resonance energy transfer between fluorophores with excitation in the violet (400 nm) and emissions in the cyan (470 nm) and yellow (588 nm) range of the spectrum. Results show that the device photocurrent signal measured under reverse bias and using appropriate steady state optical bias, allows the separate detection of the cyan and yellow fluorescence signals presented.

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Combined tunable WDM converters based on SiC multilayer photonic active filters are analyzed. The operation combines the properties of active long-pass and short-pass wavelength filter sections into a capacitive active band-pass filter. The sensor element is a multilayered heterostructure produced by PE-CVD. The configuration includes two stacked SiC p-i-n structures sandwiched between two transparent contacts. Transfer function characteristics are studied both theoretically and experimentally. Results show that optical bias activated photonic device combines the demultiplexing operation with the simultaneous photodetection and self amplification of an optical signal acting the device as an integrated photonic filter in the visible range. Depending on the wavelength of the external background and irradiation side, the device acts either as a short- or a long-pass band filter or as a band-stop filter. The output waveform presents a nonlinear amplitude-dependent response to the wavelengths of the input channels. A numerical simulation and two building-blocks active circuit is presented and gives insight into the physics of the device.

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Mestrado em Engenharia Química