Intelligent Architecture Research Articles

Intelligence distribution for data processing in smart grids: A semantic approach

The smart grid vision demands both syntactic interoperability in order to physically be able to interchange data and semantic interoperability to properly understand and interpret its meaning. The IEC and the EPRI have backed to this end the harmonization of two widely used industrial standards, the CIM and the IEC 61850, as the global unified ontology in the smart grid scenario. Still, persisting such a huge general ontology in each and every one of the members of a distributed system is neither practical nor feasible.Moreover, the smart grid will be a heterogeneous conglomerate of legacy and upcoming architectures that will require first the possibility of representing all the existing assets in the power network as well as new unknown ones, and second, the collaboration of different entities of the system in order to deploy complex activities. Finally, the smart grid presents diverse time span requirements, such as real-time, and all of them must be addressed efficiently but use resources sparingly.Against this background, we put forward an architecture of intelligent nodes spread all over the smart grid structure. Each intelligent node only has a profile of the global ontology. Moreover, adding reasoning abilities, we achieve simultaneously the required intelligence distribution and local decision making. Furthermore, we address the aforementioned real-time and quasi-real-time requirements by integrating stream data processing tools within the intelligent node. Combined with the knowledge base profile and the reasoning capability, our intelligent architecture supports semantic stream reasoning. We have illustrated the feasibility of this approach with a prototype composed of three substations and the description of several complex activities involving a number of different entities of the smart grid. Moreover, we have also addressed the potential extension of the unified ontology.

Architecture of fluid intelligence and working memory revealed by lesion mapping

Although cognitive neuroscience has made valuable progress in understanding the role of the prefrontal cortex in human intelligence, the functional networks that support adaptive behavior and novel problem solving remain to be well characterized. Here, we studied 158 human brain lesion patients to investigate the cognitive and neural foundations of key competencies for fluid intelligence and working memory. We administered a battery of neuropsychological tests, including the Wechsler Adult Intelligence Scale (WAIS) and the N-Back task. Latent variable modeling was applied to obtain error-free scores of fluid intelligence and working memory, followed by voxel-based lesion-symptom mapping to elucidate their neural substrates. The observed latent variable modeling and lesion results support an integrative framework for understanding the architecture of fluid intelligence and working memory and make specific recommendations for the interpretation and application of the WAIS and N-Back task to the study of fluid intelligence in health and disease.

Childhood intelligence is heritable, highly polygenic and associated with FNBP1L.

Intelligence in childhood, as measured by psychometric cognitive tests, is a strong predictor of many important life outcomes, including educational attainment, income, health and lifespan. Results from twin, family and adoption studies are consistent with general intelligence being highly heritable and genetically stable throughout the life course. No robustly associated genetic loci or variants for childhood intelligence have been reported. Here, we report the first genome-wide association study (GWAS) on childhood intelligence (age range 6-18 years) from 17,989 individuals in six discovery and three replication samples. Although no individual single-nucleotide polymorphisms (SNPs) were detected with genome-wide significance, we show that the aggregate effects of common SNPs explain 22-46% of phenotypic variation in childhood intelligence in the three largest cohorts (P=3.9 × 10(-15), 0.014 and 0.028). FNBP1L, previously reported to be the most significantly associated gene for adult intelligence, was also significantly associated with childhood intelligence (P=0.003). Polygenic prediction analyses resulted in a significant correlation between predictor and outcome in all replication cohorts. The proportion of childhood intelligence explained by the predictor reached 1.2% (P=6 × 10(-5)), 3.5% (P=10(-3)) and 0.5% (P=6 × 10(-5)) in three independent validation cohorts. Given the sample sizes, these genetic prediction results are consistent with expectations if the genetic architecture of childhood intelligence is like that of body mass index or height. Our study provides molecular support for the heritability and polygenic nature of childhood intelligence. Larger sample sizes will be required to detect individual variants with genome-wide significance.

Predefined Three Tier Business Intelligence Architecture in Healthcare Enterprise

Business Intelligence (BI) has caused extensive concerns and widespread use in gathering, processing and analyzing data and providing enterprise users the methodology to make decisions. Different from traditional BI architecture, this paper proposes a new BI architecture, Top-Down Scalable BI architecture with defining mechanism for enterprise decision making solutions and aims at establishing a rapid, consistent, and scalable multiple applications on multiple platforms of BI mechanism. The two opposite information flows in our BI architecture offer the merits of having the high level of organizational prospects and making full use of the existing resources. We also introduced the avg-bed-waiting-time factor to evaluate hospital care capacity.

Towards a constructivist methodology: learning constructions by integrating in situ representations and productivity

Abstract The ability to learn constructions may be important for the development of a self-organizing architecture for artificial general intelligence. Constructions are structural relations between more specific or more abstract conceptual representations. They can be derived from the processes of alignment, collocations and distributed equivalences. An architecture that integrates in situ grounded representations with cognitive productivity is ideally suited to learn constructions. This paper described such an architecture, based on neuronal assembly structures and neuronal ’blackboards’ for grounded compositional representations. The paper outlines how constructions could be learned in such an architecture and how the architecture could eventually develop into an autonomous self-organizing architecture for artificial general intelligence.

Business Intelligence as a Competitive Advantage on a Brazilian Chemical Industry in the Global Crisis of 2008, 2009 and 2010

From 2008´s to 2010’s a serious financial crisis forced many sectors to drastically review their production and sales plans. Sectors like the chemical industry were reorganized to deal with the challenging scenario found. The presence of Business Intelligence architecture does not mean that the organization really enjoys the best that this architecture brings. The push of Business Intelligence architecture usage was very important during this critical crisis moment to help on process standardization, data quality improvement and process automation. This article's objective is to demonstrate how the world crisis of 2008, 2009 and 2010 was a great opportunity to improve the usage of business intelligence architecture bringing benefits for a Brazilian chemistry industry.

Distributed neural system for emotional intelligence revealed by lesion mapping

Cognitive neuroscience has made considerable progress in understanding the neural architecture of human intelligence, identifying a broadly distributed network of frontal and parietal regions that support goal-directed, intelligent behavior. However, the contributions of this network to social and emotional aspects of intellectual function remain to be well characterized. Here we investigated the neural basis of emotional intelligence in 152 patients with focal brain injuries using voxel-based lesion-symptom mapping. Latent variable modeling was applied to obtain measures of emotional intelligence, general intelligence and personality from the Mayer, Salovey, Caruso Emotional Intelligence Test (MSCEIT), the Wechsler Adult Intelligence Scale and the Neuroticism-Extroversion-Openness Inventory, respectively. Regression analyses revealed that latent scores for measures of general intelligence and personality reliably predicted latent scores for emotional intelligence. Lesion mapping results further indicated that these convergent processes depend on a shared network of frontal, temporal and parietal brain regions. The results support an integrative framework for understanding the architecture of executive, social and emotional processes and make specific recommendations for the interpretation and application of the MSCEIT to the study of emotional intelligence in health and disease.

NET-COMPUTER: Internet Computer Architecture and its Application in E-Commerce

Research in Intelligent Agents has yielded interesting results, some of which have been translated into commer­cial ventures. Intelligent Agents are executable software components that represent the user, perform tasks on behalf of the user and when the task terminates, the Agents send the result to the user. Intelligent Agents are best suited for the Internet: a collection of computers connected together in a world-wide computer network. Swarm and HYDRA computer architectures for Agents’ execution were developed at the University of Surrey, UK in the 90s. The objective of the research was to develop a software-based computer architecture on which Agents execution could be explored. The combination of Intelligent Agents and HYDRA computer architecture gave rise to a new computer concept: the NET-Computer in which the comput­ing resources reside on the Internet. The Internet computers form the hardware and software resources, and the user is provided with a simple interface to access the Internet and run user tasks. The Agents autonomously roam the Internet (NET-Computer) executing the tasks. A growing segment of the Internet is E-Commerce for online shopping for products and services. The Internet computing resources provide a marketplace for product suppliers and consumers alike. Consumers are looking for suppliers selling products and services, while suppliers are looking for buyers. Searching the vast amount of information available on the Internet causes a great deal of problems for both consumers and suppliers. Intelligent Agents executing on the NET-Computer can surf through the Internet and select specific information of interest to the user. The simulation results show that Intelligent Agents executing HYDRA computer architecture could be applied in E-Commerce.

Improved Methods for Intelligent Learning Environment Architecture: A Case Study of Technological Frame

The higher education of Taiwan in the last decade has experienced the new wave of rapidly developing intelligent learning environment for providing all users of educational and learning purposes. This study observes that the developed environment provided by intelligent learning technologies brings about the superior functionality and efficiency of message transformation. However, through an observation on H University during the 1996-2012 years, the adoption of intelligent learning environment can not satisfy users’ needs regarding environment architecture. Brown (1998) adopts the technology viewpoint to learning participation; otherwise it would reduce learning efforts and exhaust mental power. In addition, Russell (1999) proposes that the use of too much information technology would not improve learning effectiveness since educational field’s perception and behavior do not always meet the needs of users. This study finds that Orlikowski and Gash (1994)’s technological frame will be different due to various purposes of application of leaders and pioneers. Technological frame is a human made product of society. Therefore, this study suggests that technological frame can be used as the analysis tool for intelligent learning environment architecture. The propositions are three proposed, the main aim is to seek improved methods for the existing intelligent learning environment using case study methodology. The focus groups are utilized as research samples to establish the intelligent learning environment framework. By using the card sorting to establish intelligent learning environmental framework, the study attempts to explore the gap between intelligent learning environmental framework and user needs. Based on the theory of technological frame by Orlikowski and Gash (1994) to analyze the frame, this study proposes the recommendations as advanced references for improving intelligent learning environment framework.

Design and Implementation of Intelligent Shelf System Based on Internet of Things Technology

In order to solve the problem of the desynchronized between entity flow and information flow in space and time, the paper puts forward the intelligent shelf system based on IOT tech. Through the deployment design of the hardware structure and analyzing of intelligent shelf architecture systematically, it realizes entity flow and information flow synchronization in business process, which makes the warehouse management more efficient and visible.

The Intelligent Quality Control Technology System Based on the Integration Methods of SPC and EPC

SPC (statistical process control) and EPC (engineering process control) is the scientific methods of quality quality control and quality improvement. It is the difficult problems of quality control process for network manufacturing enterprise how to effectively solve the dynamic quality fluctuation monitoring and the fluctuation abnormal diagnostic analysis and timely process adjustments, this paper designs the intelligent quality control mode and function system architecture, the modes expatiates quality management network based on quality control network of the workshop level and enterprise class network, and researches the integration applications of statistical process control and enterprise ERP quality system, and applies J2EE technology to achieve the system organic combination of design and development.

Reconfigurable Intelligent Control Architecture of a Small-Scale Unmanned Helicopter

Over the past decades, substantial research has been undertaken in the design of intelligent architecture for the rotorcraft-based unmanned aerial vehicles (RUAV). Designing intelligent architecture is a challenging problem because future RUAVs are utterly autonomous and their performance is comparable with that of manned vehicles. This paper deals with the design and development of a layered architectural framework that addresses the issue arising in autonomous intelligent control systems. The architecture consists of two layers. The high-level layer is occupied by planning routines. In this level, the waypoints and mission tasks from the command center are executed. The function of the low-level layer is to stabilize the flight and follow the commanded trajectory from the upper layer. These layers integrate the following functionalities: (1) waypoint navigation and control, which includes auto-landing; (2) obstacle detection and avoidance; (3) fault detection and identification; and (4) system reconfiguration in two levels (high-level and low-level controllers). The resulting layered architecture is discussed in detail. Moreover, the novel fault detection and identification method is developed to address multiplicative and additive faults. A testing environment for RUAV is developed to validate this architecture. Complete setup is carried out using an embedded board run under a real-time operating system. The algorithms are tested and evaluated using hardware-in-the-loop simulation (HILS). The simulation result proves that the proposed architecture demonstrates the desired efficiency and reliability.

Toward Intelligent Security Robots: A Survey

In this paper, a survey is being conducted on the investigation of a four-class taxonomy related to security robots that appeared over the past three decades. The survey emphasizes on state-of-the-art mobile technologies that have been developed for crime-fighting robots, capable of crafting critical situations with confrontation strategies. Throughout this investigation, 60 projects are being examined with respect to faculties and sensor apparatus being used. A statistical analysis, which is carried on the historical developments of the most attractive frameworks, reveals the popularity of the four security robot categories and their chronological progress over the past 30 years. The categories being evaluated regard teleoperated, distributed, surveillance, and law-enforcement robot architectures. In the survey, an attempt is made to explain the importance of intelligent methodologies, and their emergent effects in security tasks. The major findings of this analysis illustrate the minor contribution of intelligent architectures in crime-fighting robots, and what constitutes an intelligent security robot.

New Optimal Solutions for Real-Time Reconfigurable Periodic Asynchronous Operating System Tasks with Minimizations of Response Time

Scheduling tasks is an essential requirement in most real-time and embedded systems, but leads to unwanted central processing unit (CPU) overheads. The authors present a real-time schedulability algorithm for preemptable, asynchronous and periodic reconfigurable task systems with arbitrary relative deadlines, scheduled on a uniprocessor by an optimal scheduling algorithm based on the earliest deadline first (EDF) principles and on the dynamic reconfiguration. A reconfiguration scenario is assumed to be a dynamic automatic operation allowing addition, removal or update of operating system’s (OS) functional asynchronous tasks. When such a scenario is applied to save the system at the occurrence of hardware-software faults, or to improve its performance, some real-time properties can be violated. The authors propose an intelligent agent-based architecture where a software agent is used to satisfy the user requirements and to respect time constraints. The agent dynamically provides precious technical solutions for users when these constraints are not verified, by removing tasks according to predefined heuristic, or by modifying the worst case execution times (WCETs), periods, and deadlines of tasks in order to meet deadlines and to minimize their response time. They implement the agent to support these services which are applied to a Blackberry Bold 9700 and to a Volvo system and present and discuss the results of experiments.

Technical Factors for Implementing SOA-Based Business Intelligence Architecture: An Exploratory Study

Business intelligence (BI) architecture based on service-oriented architecture (SOA) concept enables enterprises to deploy agile and reliable BI applications. However, the key factors for implementing a SOA-based BI architecture from technical perspectives have not yet been systematically investigated. Most of the prior studies focus on organisational and managerial perspectives rather than technical factors. Therefore, this study explores the key technical factors that are most likely to have an impact on the implementation of a SOA-based BI architecture. This paper presents a conceptual model of BI architecture built on SOA concept. Drawing on academic and practitioner literature related to SOA and software architectural design, we propose fourteen key factors that may influence the implementation of a SOA-based BI architecture. This study bridges the gap between academic and practitioners.

An integrative architecture for general intelligence and executive function revealed by lesion mapping

Although cognitive neuroscience has made remarkable progress in understanding the involvement of the prefrontal cortex in executive control, the broader functional networks that support high-level cognition and give rise to general intelligence remain to be well characterized. Here, we investigated the neural substrates of the general factor of intelligence (g) and executive function in 182 patients with focal brain damage using voxel-based lesion-symptom mapping. The Wechsler Adult Intelligence Scale and Delis-Kaplan Executive Function System were used to derive measures of g and executive function, respectively. Impaired performance on these measures was associated with damage to a distributed network of left lateralized brain areas, including regions of frontal and parietal cortex and white matter association tracts, which bind these areas into a coordinated system. The observed findings support an integrative framework for understanding the architecture of general intelligence and executive function, supporting their reliance upon a shared fronto-parietal network for the integration and control of cognitive representations and making specific recommendations for the application of the Wechsler Adult Intelligence Scale and Delis-Kaplan Executive Function System to the study of high-level cognition in health and disease.

Intelligent libraries and apomediators: Distinguishing between Library 3.0 and Library 2.0

Using the ‘point oh’ naming system for developments in librarianship is attracting debate about its appropriateness, basis and syntax and the meaning and potential of Library 2.0. Now a new term, Library 3.0, has emerged. Is there is any significant difference between the two models? Using documentary analysis to explore the terms, the authors conclude that Library 2.0 and Library 3.0 are different. Whereas Library 2.0 could be seen as attempting to weaken the role of librarians in the emerging information environment, Library 3.0 projects librarians as prominent apomediaries guiding library users on how best to locate, access and use credible information in myriad formats from diverse sources, at the point of need. The Library 3.0 model has revived hope amongst those who were uncomfortable with the crowd intelligence architecture on which the Library 2.0 model was founded. It provides the tools and framework to organize the infosphere that the Library 2.0 threw into disarray. The authors see the 3.0 library as a personalizable, intelligent, sensitive and living institution created and sustained by a seamless engagement of library users, librarians and subject experts on a federated network of information pathways.

REDES SOCIAIS DIGITAIS, EPISTEMOLOGIAS RETICULARES E A CRISE DO ANTROPOMORFISMO SOCIAL

O surgimento das redes digitais delineia-se, em nível teórico, como uma oportunidade para uma análise, não apenas sobre a importância do papel da comunicação na nossa sociedade, mas, também, sobre as transformações do conhecimento e das dinâmicas de inovação na nossa contemporaneidade. A partir desse contexto, o presente artigo propõe uma reflexão conceitual ao apresentar a perspectiva reticular como uma ruptura epistêmica, que tem suas origens em diversos campos do conhecimento científico desde a primeira metade do século XX, delineando-se, aos poucos, como uma nova forma explicativa da complexidade que encontra na forma tecnológico-comunicativa sua expressão concreta. A difusão da arquitetura reticular informativa de uma inteligência planetária aponta para a necessidade do repensamento do antropomorfismo social, tornando-se um dos desafios hermenêuticos da nossa época.

A Scalable Distributed Architecture for Intelligent Vision System

The complexity of intelligent computer vision systems demands novel system architectures that are capable of integrating various computer vision algorithms into a working system with high scalability. The real-time applications of human-centered computing are based on multiple cameras in current systems, which require a transparent distributed architecture. This paper presents an application-oriented service share model for the generalization of vision processing. Based on the model, a vision system architecture is presented that can readily integrate computer vision processing and make application modules share services and exchange messages transparently. The architecture provides a standard interface for loading various modules and a mechanism for modules to acquire inputs and publish processing results that can be used as inputs by others. Using this architecture, a system can load specific applications without considering the common low-layer data processing. We have implemented a prototype vision system based on the proposed architecture. The latency performance and 3-D track function were tested with the prototype system. The architecture is scalable and open, so it will be useful for supporting the development of an intelligent vision system, as well as a distributed sensor system.

Energy efficiency in logistics - SmartKanban as an intelligent intra-logistics architecture for Kanban scenarios

Abstract Information technology offers a high potential in achieving the climate protection goals by encouraging the reduction of energy consumption associated with a decrease of greenhouse gas emissions. This article shows how processes in logistics can be optimized by means of information technology. Using the example of SmartKanban, the additional energy consumption caused by information technology is compared to achievable potential energy savings.