Computational Processes for General Intelligence

The purpose of this study was to evaluate the effect of exercise training intensity relative to the ventilatory threshold (VT) on changes in work (watts) and VO2 at the ventilatory threshold and at maximal exercise in previously sedentary participants in the HERITAGE Family Study. We hypothesized that those who exercised below their VT would improve less in VO2 at the ventilatory threshold (VO2vt) and VO2max than those who trained at an intensity greater than their VT. Supervised cycle ergometer training was performed at the 4 participating clinical centers, 3 times a week for 20 weeks. Exercise training progressed from the HR corresponding to 55% VO2max for 30 minutes to the HR associated with 75% VO2max for 50 minutes for the final 6 weeks. VT was determined at baseline and after exercise training using standardized methods. 432 sedentary white and black men (n = 224) and women (n = 208), aged 17 to 65 years, were retrospectively divided into groups based on whether exercise training was initiated below, at, or above VT. 1) Training intensity (relative to VT) accounting for about 26% of the improvement in VO2vt (R2 = 0.26, p < 0.0001). 2) The absolute intensity of training in watts (W) accounted for approximately 56% of the training effect at VT (R2 = 0.56, p < 0.0001) with post-training watts at VT (VT(watts)) being not significantly different than W during training (p > 0.70). 3) Training intensity (relative to VT) had no effect on DeltaVO2max. These data clearly show that as a result of aerobic training both the VO2 and W associated with VT respond and become similar to the absolute intensity of sustained (3 x /week for 50 min) aerobic exercise training. Higher intensities of exercise, relative to VT, result in larger gains in VO2vt but not in VO2max.

Primary central nervous system (CNS) germinoma is readily curable with relatively large volume/high dose radiotherapy but the late effects of treatment may alter neurocognitive functioning and quality of life. Prior studies have associated radiation therapy with deficits in the domains of intelligence, attention, memory, and psychomotor processing speed, with risk factors including young age at irradiation and increased irradiation volume and dosage level. Furthermore, cranial irradiation may also lead to diminished height, neuroendocrine dysfunction, and hearing loss.

We strongly believe that agent-oriented approaches to system development come with a natural level of abstraction and therefore have something valuable to offer. However, in doing so, any comprehensive agent-oriented methodology necessarily has to be grounded in issues and solutions of relevance in contemporary research and development areas such as Grid computing and autonomic computing - in order to realize the visions of ambient intelligence. Current efforts of AOSE, however, mostly focus on traditional methods of software development, provides implementations of stand-alone agent systems, or isolated experimental platforms. These efforts are, of course, worthwhile in themselves but have clear limitations when it comes to their contribution and fulfillment of visions such as ambient intelligence. Consequently, in this chapter we introduce the methodological approach of online engineering. As such, this methodology has explicitly been designed to meet what we conceive as the major challenges and limitations in contemporary approaches of AOSE. In fact, we argue that these limitations primarily are due to a strong focus on current practice in software engineering, rather than on engineering of grounded open computational systems. In this respect, online engineering provides us with the models, methods, and tools to facilitate the necessary transition from programming of abstract machines towards development of grounded physical systems, e.g., from software engineering to engineering of open computational systems.

Intelligent control is an attempt to specify the function of a controller in ways which mimic the decision-making capabilities of humans. Traditionally, issues relating to the emulation of human-like capabilities have fallen in the domain of artificial intelligence. Intelligent processing is a specific form of intelligent control in which the system to be controlled is a process rather than the more conventional mechanical or electrical system. The National Institute of Standards and Technology’s program on intelligent processing of metal powders is a multi-disciplinary research initiative investigating the application of intelligent control technologies to improve the state of the art of metal powder manufacturing. This paper reviews the design of the institute’s supersonic inert-gas metal-atomizer control system.

The present study examined the genetic and environmental contributions to the temporal stability of verbal, non-verbal and general intelligence across a developmental period spanning childhood and adolescence (5-18 years). Longitudinal twin data collected in four different studies on a total of 1,748 twins, comprising 4,641 measurement points in total, were analyzed using genetic adaptations of the simplex model. The heterogeneity in the type of instrument used to assess psychometric intelligence across the different subsamples and ages allowed us to address the auxiliary question of how to optimally utilize the existing longitudinal data in the context of gene-finding studies. The results were consistent across domains (verbal, non-verbal and general intelligence), and indicated that phenotypic stability was driven primarily by the high stability of additive genetic factors, that the stability of common environment was moderate, and that the unique environment contributed primarily to change. The cross-subscale stability was consistently low, indicating a small overlap between different domains of intelligence over time. The high stability of additive genetic factors justifies the use of a linear combination of scores across the different ages in the context of gene-finding studies.

Ten adult volunteers participated in Id weeks of cardiovascular exercise training (EG) to determine the effects of training on resting prostacyclin (PGI2) and thromboxane A2 (TXA2). Six volunteers of similar age served as sedentary controls (CG). Blood was collected in tubes after training and eicosanoids were measured by standard 125I RIA methods. Over the 16 weeks of the study, PGI2 decreased 48% for EG and 33% for CG. There were no between-group differences for PGI2 values. No significant within-group changes in TXA2 were found, whereas between-group pretraining TXA2 values were significantly different. A time main effect for PGI2 may indicate a seasonal shift in this eicosanoid: however, the additional 15% decrease in PGI2 for EG may be due to a training-induced reduction in PGI2 substrate and/or endothelial sensitivity to agonists. The lack of within-group changes in TXA2 may be due to a combination of high platelet turnover and a training stimulus inadequate to alter platelet function.

BackgroundGenerational IQ gains in the general population (termed the Flynn effect) show an erratic pattern across different nations as well as across different domains of intelligence (fluid vs crystallized). Gains of fluid intelligence in different countries have been subject to extensive research, but less attention was directed towards gains of crystallized intelligence, probably due to evidence from the Anglo-American sphere suggesting only slight gains on this measure. In the present study, development of crystallized intelligence in the German speaking general population is assessed.Methodology/Principal FindingsTo investigate whether IQ gains for crystallized intelligence are in progress in German-speaking countries, two independent meta-analyses were performed. By means of a cited reference search in ISI Web of Science, all studies citing test manuals and review articles of two widely-used salient measures of crystallized intelligence were obtained. Additionally, the electronic database for German academic theses was searched to identify unpublished studies employing these tests. All studies reporting participants mean IQ or raw scores of at least one of the two measures were included in the present analyses, yielding over 500 studies (>1,000 samples; >45,000 individuals). We found a significant positive association between years of test performance and intelligence (1971–2007) amounting to about 3.5 IQ points per decade.Conclusions/SignificanceThis study clearly demonstrates that crystallized IQ gains are substantial and of comparable strength as Flynn effects typically observed for measures of fluid intelligence in Central Europe. Since mean IQ was assessed in a large number of small, non-representative samples, our evidence suggests a remarkable robustness of these gains. Moreover, in both meta-analyses strength of gains was virtually identical. On the whole, results of the present study demonstrate a pervasive and generalizing Flynn effect in German-speaking countries.

The term intelligence has historically referred to individual differences in the assessment of school-related abilities. Recently, however, the term has been broadened to include individual differences in a number of different domains. Academic intelligence, for example, is not correlated with measures of practical intelligence, defined as the ability to solve problems that arise in natural, nonschool settings (Wagner & Sternberg, 1986). Broadening the definition even further, Gardner (1983) suggested seven different types of intelligence, including traditional academic domain, (e.g., logical-mathematical intelligence), bodily kinesthetic intelligence, musical intelligence, and social intelligence (both intrapersonal and interpersonal). The domain of intelligence that is the focus of this chapter is infants' social cognitions regarding self and other. How do infants construct understandings of themselves and others? A long theoretical tradition suggests that infants create the self by differentiating self from nonself (Bretherton, 1985; Mahler, Pine, & Bergman, 1975; Stern, 1985). In a review of current theories of self-development, Brownell and Kopp (1991) suggest that with development, infants establish boundaries that define the self compared to others and objects. The core function of self is “to define, locate, demarcate the world from a consistent perspective by organizing, integrating and representing experiences from that vantage point” (p. 288). By creating boundaries between self and other, the construction of the self is hypothesized to parallel construction of the other (Baldwin, 1899). The process of differentiating self from other may follow a different developmental course in twins compared to singletons.

Neural networks have enabled applications in artificial intelligence through machine learning, and neuromorphic computing. Software implementations of neural networks on conventional computers that have separate memory and processor (and that operate sequentially) are limited in speed and energy efficiency. Neuromorphic engineering aims to build processors in which hardware mimics neurons and synapses in the brain for distributed and parallel processing. Neuromorphic engineering enabled by photonics (optical physics) can offer sub-nanosecond latencies and high bandwidth with low energies to extend the domain of artificial intelligence and neuromorphic computing applications to machine learning acceleration, nonlinear programming, intelligent signal processing, etc. Photonic neural networks have been demonstrated on integrated platforms and free-space optics depending on the class of applications being targeted. Here, we discuss the prospects and demonstrated applications of these photonic neural networks.

Offshoring is a widely used practice in the software development. It is mainly employed to reduce development costs. However, as in a number of studies have been shown, about 40 percent of offshore software development projects are flops. One predominant reason for it is the lack of standardized and practicable methods of risk management due to the inherent complexity of software development offshoring. Therefore, suitable methods and tools for the risk management specific to such projects are required. Firstly, this workshop will provide an insight into various aspects of the risk management of offshore software development. Secondly, tools and methods for the risk management will be discussed and presented. Thirdly, priorities for further research will be identified. The results of this workshop will, on the one hand, benefit companies sharing in the software development offshoring and, on the other hand, academics to identify the demand in the further research.

A critical factor in successful project management and effective planning is the analysis of software development complexity and effort. The use of industry-standard methods, such as Function Point Analysis, serves as an effective means of improving estimation accuracy while simultaneously reducing the cost of the estimation process itself. However, standard methods, most of which were developed several decades ago, are not sufficiently adapted to modern realities, including agile software development and the use of pre-built or standardized solutions. This study proposes knowledge representation model that combine production and frame-based approaches to address the challenge of assessing the complexity and effort of software development involving SaaS (Software as a Service) and PaaS (Platform as a Service) solutions. A knowledge base model has been developed, integrating both frame-based and production models while ensuring compatibility with Function Point Analysis. The developed models and their interactions can serve as the foundation for a decision-making model within an information technology framework for software development complexity assessment, considering environmental factors and evaluation criteria. The application of the proposed models will enable the creation of automated algorithms for software development complexity estimation under conditions of incomplete functional requirements. The proposed approach improves effort estimation by considering real-world implementation contexts, which is particularly relevant for modern IT projects. Additionally, the combination of frame-based and production models lays the groundwork for further integration with artificial intelligence and machine learning to automate effort estimation processes. Future research should focus on refining the decision-making model, conducting experimental validation against traditional methods, and expanding its capabilities using fuzzy logic and neural networks for dynamic complexity assessment. The integration of this approach into decision support systems (DSS) for software project and resource management also remains a promising direction.

No one believes that g is the only construct needed to describe individual differences in intelligence. Many believe that g is a dispensable construct. Others object to what they construe as its hegemonic position in the domain of intelligence. In this paper I defend the hegemonic status of g by a brief consideration of diverse criticisms of the g construct. I argue that g is a heritable component of intelligence that accounts for approximately 50% of the covariance among diverse measures of intelligence. It derives from a core information processing ability and it influences a diverse set of social outcomes. The covariances between g and information processing ability and social outcomes are, in large measure, attributable to common genetic influences.

Aerial images have attracted attention from researcher community since long time. Generating a caption for an aerial image describing its content in comprehensive way is less studied but important task as it has applications in agriculture, defence, disaster management and many more areas. Though different approaches were followed for natural image caption generation, generating a caption for aerial image remains a challenging task due to its special nature. Use of emerging techniques from Artificial Intelligence (AI) and Natural Language Processing (NLP) domains have resulted in generation of accepted quality captions for aerial images. However lot needs to be done to fully utilize potential of aerial image caption generation task. This paper presents detail survey of the various approaches followed by researchers for aerial image caption generation task. The datasets available for experimentation, criteria used for performance evaluation and future directions are also discussed.

Differential response to resistance training in CHF according to ACE genotype

Methods of processing information transmitted through wireless networks with software development are investigated in the work. Innovative methods of data transmission such as optical technologies, quantum data transmission and wireless data transmission technologies are disclosed. It is noted that in the modern understanding, the concept of distributed computing defines the process of convergence (convergence) of distributed processing methods, such as GRID, cloud and fog computing, with the combination of virtual cluster systems (grid clusters, cloud clusters and fog clusters) into a single information communication and computing system . It is emphasized that, unlike cellular modems, ZigBee technology nodes have microcontrollers with a pre-installed operating system and flash memory, which allows solving simple computational tasks in real time before sending data. It is advisable to solve such tasks within the framework of a multi-agent approach, which will increase the efficiency of the use of sensor nodes and the entire sensor network. The advantages of the multi-agent technology of fog computing based on sensor nodes of the wireless network of the ZigBee standard are revealed. The method of multi-agent processing of sensory information and its main components are described. The architecture of the system of distributed sensor data processing is outlined, which includes 4 hardware and software levels: Terminal sensor nodes and controllers of measuring devices and automation devices that implement fuzzy calculations; Coordinators, sensor segment routers and cellular modems that collect, protect and transmit sensor data to the processing center; A data processing center that includes a cluster of servers for GRID calculations and a cloud data storage server; Client devices to access cloud storage, computing cluster servers, and distributed fog computing terminals. It is emphasized that indicators and forecast results can be stored on distributed sensor nodes or transmitted for accumulation in cloud storage for further extraction and intelligent processing in the GRID cluster of the data center.