Cognitive style factors affecting database query performance

As end-user computing becomes more pervasive, an organization's success increasingly depends on the ability of end-users, usually in managerial positions, to extract appropriate data from both internal and external sources. Many of these data sources include or are derived from the organization's accounting information systems. Managerial end-users with different personal characteristics and approaches are likely to compose queries of differing levels of accuracy when searching the data contained within these accounting information systems. This research investigates how cognitive style elements of personality influence managerial end-user performance in database querying tasks. A laboratory experiment was conducted in which participants generated queries to retrieve information from an accounting information system to satisfy typical information requirements. The experiment investigated the influence of personality on the accuracy of queries of varying degrees of complexity. Relying on the Myers–Briggs personality instrument, results show that perceiving individuals (as opposed to judging individuals) who rely on intuition (as opposed to sensing) composed queries more accurately. As expected, query complexity and academic performance also explain the success of data extraction tasks.

Effects of Age-Related Cognitive Deficits on EEG Phase Coherence

Body and brain undergo several changes with aging. One of these changes is the loss of neuroplasticity, which leads to the decrease of cognitive abilities. Hence the necessity of stopping or reversing these changes is of utmost importance to contemporary society. In the present work, electroencephalogram (EEG) markers of cognitive decline are sought whilst the subjects perform the Wisconsin Card Sorting Test (WCST). Considering the expected age-related cognitive deficits, WCST was applied to young and elder participants. The results suggest that coherence on theta and alpha EEG rhythms decrease with aging and increase with performance. Additionally, theta phase coherence seems more sensitive to performance, while alpha synchronization appears as a potential ageing marker.

Cognitive intervention protocol for age-related memory impairments

With the number of elderly people increasing tremendously worldwide, comes the need for effective methods to maintain or improve older adults' cognitive performance. Using continuous neurofeedback, through the use of EEG techniques, people can learn how to train and alter their brain electrical activity. A software platform that puts together the proposed rehabilitation methodology has been developed: a digital game protocol that supports neurofeedback training of alpha and theta rhythms, by reading the EEG activity and presenting it back to the subject, interleaved with neurocognitive tasks such as n-Back and Corsi Block-Tapping. This tool will be used as a potential rehabilitative platform for age-related memory impairments.

COGNITIVE LEGITIMACY, RESOURCE ACCESS, AND ORGANIZATIONAL OUTCOMES

Previous research has demonstrated the importance of developing legitimacy initiatives in order to create new business opportunities, satisfy shareholders, and obtain access to resources. Within this framework, cognitive legitimacy plays a key role. Through a case study of six Spanish public universities, the authors measure the relationship between cognitive legitimacy, access to resources, and organizational results. The results support the assertion that organizations with more cognitive legitimacy have greater access to resources and improved their results. This study contributes with muchneeded empirical research on cognitive legitimacy and demonstrates its usefulness as an explanative factor of organizational success.

Agent Inferencing Meets the Semantic Web

We provide all agent; the capability to infer the relations (assertions) entailed by the rules that, describe the formal semantics of art RDFS knowledge-base. The proposed inferencing process formulates each semantic restriction as a rule implemented within a, SPARQL query statement. The process expands the original RDF graph into a fuller graph that. explicitly captures the rule's described semantics. The approach is currently being explored in order to support descriptions that follow the generic Semantic Web Rule Language. An experiment, using the Fire-Brigade domain, a small-scale knowledge-base, is adopted to illustrate the agent modeling method and the inferencing process.

Cognitive deficit and depressive symptoms in a community group of elderly people: a preliminary study

Since the number and proportion of old people increases worldwide, health professionals and systems should be made aware and prepared to deal with their problems. Cognitive deficit and symptoms of depression are commom among the elderly, and may occur in relation to various risk factors such as health conditions and psychosocial variables. In order to study cognitive deficit and the presence of signs and symptoms of depression, 62 elderly community subjects enrolled at a Community Health Unit in Porto Alegre, southern Brazil, were interviewed. They were evaluated by means of the Mini Mental State Exam, the Montgomery-Asberg Depression rating scale, and a questionnaire on health conditions, living arrangements and social variables. Higher levels of symptoms of depression were observed among subjects exposed to major risk factors for cerebrovascular diseases (diabetes and coronary disease), while impaired cognitive performance was seen among individuals who could not count on the presence of a confidant (social network variable). The results suggest that the early identification of major risk groups among old people can help to prevent institutionalization and keep individuals in the community.

A hybrid approach to multi-agent decision-making

In the aftermath of a large-scale disaster, agents' decisions derive from self-interested (e.g. survival), common-good (e.g. victims' rescue) and teamwork (e.g. fire extinction) motivations. However, current decision-theoretic models are either purely individual or purely collective and find it difficult to deal with motivational attitudes; on the other hand, mental-state based models find it difficult to deal with uncertainty. We propose a hybrid, CvI-JI, approach that combines: i) collective 'versus' individual (CvI) decisions, founded on the Markov decision process (MDP) quantitative evaluation of joint-actions, and ii)joint-intentions (JI) formulation of teamwork, founded on the belief-desire-intention (BDI) architecture of general mental-state based reasoning. The CvI-JI evaluation explores the performance's improvement

RFID together with multi-agent systems to control global value chains

Nowadays, the cooperative intelligent transport systems are part of a largest system. Transportations are modal operations integrated in logistics and, logistics is the main process of the supply chain management. The supply chain strategic management as a simultaneous local and global value chain is a collaborative/cooperative organization of stakeholders, many times in co-opetition, to perform a service to the customers respecting the time, place, price and quality levels. The transportation, like other logistics operations must add value, which is achieved in this case through compression lead times and order fulfillments. The complex supplier's network and the distribution channels must be efficient and the integral visibility (monitoring and tracing) of supply chain is a significant source of competitive advantage. Nowadays, the competition is not discussed between companies but among supply chains. This paper aims to evidence the current and emerging manufacturing and logistics system challenges as a new field of opportunities for the automation and control systems research community. Furthermore, the paper forecasts the use of radio frequency identification (RFID) technologies integrated into an information and communication technologies (ICT) framework based on distributed artificial intelligence (DAI) supported by a multi-agent system (MAS), as the most value advantage of supply chain management (SCM) in a cooperative intelligent logistics systems. Logistical platforms (production or distribution) as nodes of added value of supplying and distribution networks are proposed as critical points of the visibility of the inventory, where these technological needs are more evident.

Schizophrenia in males of cognitive performance: discriminative and diagnostic values

OBJECTIVE: To evaluate the discriminative and diagnostic values of neuropsychological tests for identifying schizophrenia patients. METHODS: A cross-sectional study with 36 male schizophrenia outpatients and 72 healthy matched volunteers was carried out. Participants underwent the following neuropsychological tests: Wisconsin Card Sorting test, Verbal Fluency, Stroop test, Mini Mental State Examination, and Spatial Recognition Span. Sensitivity and specificity estimated the diagnostic value of tests with cutoffs obtained using Receiver Operating Characteristic curves. The latent class model (diagnosis of schizophrenia) was used as gold standard. RESULTS: Although patients presented lower scores in most tests, the highest canonical function for the discriminant analysis was 0.57 (Verbal Fluency M). The best sensitivity and specificity were obtained in the Verbal Fluency M test (75 and 65, respectively). CONCLUSIONS: The neuropsychological tests showed moderate diagnostic value for the identification of schizophrenia patients. These findings suggested that the cognitive impairment measured by these tests might not be homogeneous among schizophrenia patients.

DITRANS - a multi-agent system for integrated diagnosis of power transformers

This paper describes the development and the implementation of a multi-agent system for integrated diagnosis of power transformers. The system is divided in layers which contain a number of agents performing different functions. The social ability and cooperation between the agents lead to the final diagnosis and to other relevant conclusions through integrating various monitoring technologies, diagnostic methods and data sources, such as the dissolved gas analysis.

MASCEM improvement for agent based coalitions

This paper presents MASCEM - Multi-Agent Simulator for Electricity Markets improvement towards an enlarged model for Seller Agents coalitions. The simulator has been improved, both regarding its user interface and internal structure. The OOA, used as development platform, version was updated and the multi-agent model was adjusted for implementing and testing several negotiations regarding Seller agents’ coalitions. Seller coalitions are a very important subject regarding the increased relevance of Distributed Generation under liberalised electricity markets.

MASGriP – a Multi-Agent Smart Grid Simulation Platform

The increasing number of players that operate in power systems leads to a more complex management. In this paper a new multi-agent platform is proposed, which simulates the real operation of power system players. MASGriP – A Multi-Agent Smart Grid Simulation Platform is presented. Several consumer and producer agents are implemented and simulated, considering real characteristics and different goals and actuation strategies. Aggregator entities, such as Virtual Power Players and Curtailment Service Providers are also included. The integration of MASGriP agents in MASCEM (Multi-Agent System for Competitive Electricity Markets) simulator allows the simulation of technical and economical activities of several players. An energy resources management architecture used in microgrids is also explained.

A multi-agent based approach for intelligent smart grid management

The spread and globalization of distributed generation (DG) in recent years has should highly influence the changes that occur in Electricity Markets (EMs). DG has brought a large number of new players to take action in the EMs, therefore increasing the complexity of these markets. Simulation based on multi-agent systems appears as a good way of analyzing players’ behavior and interactions, especially in a coalition perspective, and the effects these players have on the markets. MASCEM – Multi-Agent System for Competitive Electricity Markets was created to permit the study of the market operation with several different players and market mechanisms. MASGriP – Multi-Agent Smart Grid Platform is being developed to facilitate the simulation of micro grid (MG) and smart grid (SG) concepts with multiple different scenarios. This paper presents an intelligent management method for MG and SG. The simulation of different methods of control provides an advantage in comparing different possible approaches to respond to market events. Players utilize electric vehicles’ batteries and participate in Demand Response (DR) contracts, taking advantage on the best opportunities brought by the use of all resources, to improve their actions in response to MG and/or SG requests.

Multi-agent simulation of continental, regional, and micro electricity markets

Renewable based power generation has significantly increased over the last years. However, this process has evolved separately from electricity markets, leading to an inadequacy of the present market models to cope with huge quantities of renewable energy resources, and to take full advantage of the presently existing and the increasing envisaged renewable based and distributed energy resources. This paper proposes the modelling of electricity markets at several levels (continental, regional and micro), taking into account the specific characteristics of the players and resources involved in each level and ensuring that the proposed models accommodate adequate business models able to support the contribution of all the resources in the system, from the largest to the smaller ones. The proposed market models are integrated in MASCEM (Multi- Agent Simulator of Competitive Electricity Markets), using the multi agent approach advantages for overcoming the current inadequacy and significant limitations of the presently existing electricity market simulators to deal with the complex electricity market models that must be adopted.