Ambient intelligence in emotion based ubiquitous decision making

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.

Personality, emotion and mood simulation in decision making

In this paper is proposed the integration of personality, emotion and mood aspects for a group of participants in a decision-making negotiation process. The aim is to simulate the participant behavior in that scenario. The personality is modeled through the OCEAN five-factor model of personality (Openness, Conscientiousness, Extraversion, Agreeableness and Negative emotionality). The emotion model applied to the participants is the OCC (Ortony, Clore and Collins) that defines several criteria representing the human emotional structure. In order to integrate personality and emotion is used the pleasure-arousal-dominance (PAD) model of mood.

Personality, emotion, and mood in agent-based group decision making

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.

Context-aware emotion-based model for group decision making

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.

Processing XML with Java – a performance benchmark

Over time, XML markup language has acquired a considerable importance in applications development, standards definition and in the representation of large volumes of data, such as databases. Today, processing XML documents in a short period of time is a critical activity in a large range of applications, which imposes choosing the most appropriate mechanism to parse XML documents quickly and efficiently. When using a programming language for XML processing, such as Java, it becomes necessary to use effective mechanisms, e.g. APIs, which allow reading and processing of large documents in appropriated manners. This paper presents a performance study of the main existing Java APIs that deal with XML documents, in order to identify the most suitable one for processing large XML files

Performance analysis of Java APIS for XML processing

Over time, XML markup language has acquired a considerable importance in applications development, standards definition and in the representation of large volumes of data, such as databases. Today, processing XML documents in a short period of time is a critical activity in a large range of applications, which imposes choosing the most appropriate mechanism to parse XML documents quickly and efficiently. When using a programming language for XML processing, such as Java, it becomes necessary to use effective mechanisms, e.g. APIs, which allow reading and processing of large documents in appropriated manners. This paper presents a performance study of the main existing Java APIs that deal with XML documents, in order to identify the most suitable one for processing large XML files.

ECG denoising based on adaptive signal processing technique

An Electrocardiogram (ECG) monitoring system deals with several challenges related with noise sources. The main goal of this text was the study of Adaptive Signal Processing Algorithms for ECG noise reduction when applied to real signals. This document presents an adaptive ltering technique based on Least Mean Square (LMS) algorithm to remove the artefacts caused by electromyography (EMG) and power line noise into ECG signal. For this experiments it was used real noise signals, mainly to observe the di erence between real noise and simulated noise sources. It was obtained very good results due to the ability of noise removing that can be reached with this technique. A recolha de sinais electrocardiogr a cos (ECG) sofre de diversos problemas relacionados com ru dos. O objectivo deste trabalho foi o estudo de algoritmos adaptativos para processamento digital de sinal, para redu c~ao de ru do em sinais ECG reais. Este texto apresenta uma t ecnica de redu c~ao de ru do baseada no algoritmo Least Mean Square (LMS) para remo c~ao de ru dos causados quer pela actividade muscular (EMG) quer por ru dos causados pela rede de energia el ectrica. Para as experiencias foram utilizados ru dos reais, principalmente para aferir a diferen ca de performance do algoritmo entre os sinais reais e os simulados. Foram conseguidos bons resultados, essencialmente devido as excelentes caracter sticas que esta t ecnica tem para remover ru dos.

Mismatch negativity in childhood temporal lobe epilepsy: a proposed paradigm for testing central auditory processing

Background: Temporal lobe epilepsy (TLE) is a neurological disorder that directly affects cortical areas responsible for auditory processing. The resulting abnormalities can be assessed using event-related potentials (ERP), which have high temporal resolution. However, little is known about TLE in terms of dysfunction of early sensory memory encoding or possible correlations between EEGs, linguistic deficits, and seizures. Mismatch negativity (MMN) is an ERP component – elicited by introducing a deviant stimulus while the subject is attending to a repetitive behavioural task – which reflects pre-attentive sensory memory function and reflects neuronal auditory discrimination and perceptional accuracy. Hypothesis: We propose an MMN protocol for future clinical application and research based on the hypothesis that children with TLE may have abnormal MMN for speech and non-speech stimuli. The MMN can be elicited with a passive auditory oddball paradigm, and the abnormalities might be associated with the location and frequency of epileptic seizures. Significance: The suggested protocol might contribute to a better understanding of the neuropsychophysiological basis of MMN. We suggest that in TLE central sound representation may be decreased for speech and non-speech stimuli. Discussion: MMN arises from a difference to speech and non-speech stimuli across electrode sites. TLE in childhood might be a good model for studying topographic and functional auditory processing and its neurodevelopment, pointing to MMN as a possible clinical tool for prognosis, evaluation, follow-up, and rehabilitation for TLE.

Temporal lobe epilepsy in childhood – a study model of auditory processing

TLE in infancy has been the subject of varied research. Topographical and structural evidence is coincident with the neuronal systems responsible for auditory processing of the highest specialization and complexity. Recent studies have been showing the need of a hemispheric asymmetry for an optimization in central auditory processing (CAP) and acquisition and learning of a language system. A new functional research paradigm is required to study mental processes that require methods of cognitive-sensory information analysis processed in very short periods of time (msec), such as the ERPs. Thus, in this article, we hypothesize that the TLE in infancy could be a good model for topographic and functional study of CAP and its development process, contributing to a better understanding of the learning difficulties that children with this neurological disorder have.

Nutritional value and influence of the thermal processing on a traditional Portuguese fermented sausage (alheira)

Alheiras are a traditional, smoked, fermented meat sausage, produced in Portugal, with an undeniable cultural and gastronomic legacy. In this study, we assessed the nutritional value of this product, as well as the influence of different types of thermal processing. Alheiras from Mirandela were submitted to six different procedures: microwave, skillet, oven, charcoal grill, electric fryer and electric grill. Protein, fat, carbohydrate, minerals, NaCl, and cholesterol contents, as well as fatty acid profile were evaluated. The results show that alheiras are not hypercaloric but an unbalanced foodstuff (high levels of proteins and lipids) and the type of processing has a major impact on their nutritional value. Charcoal grill is the healthiest option: less fat (12.5 g/100 g) and cholesterol (29.3 mg/100 g), corresponding to a lower caloric intake (231.8 kcal, less 13% than the raw ones). Inversely, fried alheiras presented the worst nutritional profile, with the highest levels of fat (18.1 g/100 g) and cholesterol (76.0 g/100 g).

Effects of emotional valence and three-dimensionality of visual stimuli on brain activation: an fMRI study

BACKGROUND: Examining changes in brain activation linked with emotion-inducing stimuli is essential to the study of emotions. Due to the ecological potential of techniques such as virtual reality (VR), inspection of whether brain activation in response to emotional stimuli can be modulated by the three-dimensional (3D) properties of the images is important. OBJECTIVE: The current study sought to test whether the activation of brain areas involved in the emotional processing of scenarios of different valences can be modulated by 3D. Therefore, the focus was made on the interaction effect between emotion-inducing stimuli of different emotional valences (pleasant, unpleasant and neutral valences) and visualization types (2D, 3D). However, main effects were also analyzed.METHODS: The effect of emotional valence and visualization types and their interaction were analyzed through a 3x2 repeated measures ANOVA. Post-hoc t-tests were performed under a ROI-analysis approach. RESULTS: The results show increased brain activation for the 3D affective-inducing stimuli in comparison with the same stimuli in 2D scenarios, mostly in cortical and subcortical regions that are related to emotional processing, in addition to visual processing regions. CONCLUSIONS: This study has the potential of clarify brain mechanisms involved in the processing of emotional stimuli (scenarios’ valence) and their interaction with three-dimensionality.

Properties of tantalum oxynitride thin films produced by magnetron sputtering: the influence of processing parameters

The main purpose of this work is to present and to interpret the change of structure and physical properties of tantalum oxynitride (TaNxOy) thin films, produced by dc reactive magnetron sputtering, by varying the processing parameters. A set of TaNxOy films was prepared by varying the reactive gases flow rate, using a N2/O2 gas mixture with a concentration ratio of 17:3. The different films, obtained by this process, exhibited significant differences. The obtained composition and the interpretation of X-ray diffraction results, shows that, depending on the partial pressure of the reactive gases, the films are: essentially dark grey metallic, when the atomic ratio (N + O)/Ta < 0.1, evidencing a tetragonal β-Ta structure; grey-brownish, when 0.1 < (N + O)/Ta < 1, exhibiting a face-centred cubic (fcc) TaN-like structure; and transparent oxide-type, when (N + O)/Ta > 1, evidencing the existence of Ta2O5, but with an amorphous structure. These transparent films exhibit refractive indexes, in the visible region, always higher than 2.0. The wear resistance of the films is relatively good. The best behaviour was obtained for the films with (N + O)/Ta ≈ 0.5 and (N + O)/Ta ≈ 1.3.

Enoxacin inhibits growth of prostate cancer cells and effectively restores microRNA processing

Prostate cancer (PCa) is one of the most incident malignancies worldwide. Although efficient therapy is available for early-stage PCa, treatment of advanced disease is mainly ineffective and remains a clinical challenge. microRNA (miRNA) dysregulation is associated with PCa development and progression. In fact, several studies have reported a widespread downregulation of miRNAs in PCa, which highlights the importance of studying compounds capable of restoring the global miRNA expression. The main aim of this study was to define the usefulness of enoxacin as an anti-tumoral agent in PCa, due to its ability to induce miRNA biogenesis in a TRBP-mediated manner. Using a panel of five PCa cell lines, we observed that all of them were wild type for the TARBP2 gene and expressed TRBP protein. Furthermore, primary prostate carcinomas displayed normal levels of TRBP protein. Remarkably, enoxacin was able to decrease cell viability, induce apoptosis, cause cell cycle arrest, and inhibit the invasiveness of cell lines. Enoxacin was also effective in restoring the global expression of miRNAs. This study is the first to show that PCa cells are highly responsive to the anti-tumoral effects of enoxacin. Therefore, enoxacin constitutes a promising therapeutic agent for PCa.

Scalable and efficient data processing in networked control systems

Network control systems (NCSs) are spatially distributed systems in which the communication between sensors, actuators and controllers occurs through a shared band-limited digital communication network. However, the use of a shared communication network, in contrast to using several dedicated independent connections, introduces new challenges which are even more acute in large scale and dense networked control systems. In this paper we investigate a recently introduced technique of gathering information from a dense sensor network to be used in networked control applications. Obtaining efficiently an approximate interpolation of the sensed data is exploited as offering a good tradeoff between accuracy in the measurement of the input signals and the delay to the actuation. These are important aspects to take into account for the quality of control. We introduce a variation to the state-of-the-art algorithms which we prove to perform relatively better because it takes into account the changes over time of the input signal within the process of obtaining an approximate interpolation.

Elements of scalable data processing

Cooperating objects (COs) is a recently coined term used to signify the convergence of classical embedded computer systems, wireless sensor networks and robotics and control. We present essential elements of a reference architecture for scalable data processing for the CO paradigm.