Rapid evolution of the cerebellum in humans and other great apes

Humans’ unique cognitive abilities are usually attributed to a greatly expanded neocortex, which has been described as “the crowning achievement of evolution and the biological substrate of human mental prowess” [1]. The human cerebellum, however, contains four times more neurons than the neocortex [2] and is attracting increasing attention for its wide range of cognitive functions. Using a method for detecting evolutionary rate changes along the branches of phylogenetic trees, we show that the cerebellum underwent rapid size increase throughout the evolution of apes, including humans, expanding significantly faster than predicted by the change in neocortex size. As a result, humans and other apes deviated significantly from the general evolutionary trend for neocortex and cerebellum to change in tandem, having significantly larger cerebella relative to neocortex size than other anthropoid primates. These results suggest that cerebellar specialization was a far more important component of human brain evolution than hitherto recognized and that technical intelligence was likely to have been at least as important as social intelligence in human cognitive evolution. Given the role of the cerebellum in sensory-motor control and in learning complex action sequences, cerebellar specialization is likely to have underpinned the evolution of humans’ advanced technological capacities, which in turn may have been a preadaptation for language.

The structure and infrastructure of Mexico's science and technology

The structure and infrastructure of the Mexican technical literature was determined. A representative database of technical articles was extracted from the Science Citation Index for the year 2002, with each article containing at least one author with a Mexican address. Many different manual and statistical clustering methods were used to identify the structure of the technical literature (especially the science and technology core competencies). One of the pervasive technical topics identified from the clustering, thin films research, was analyzed further using bibliometrics, in order to identify the infrastructure of this technology. Published by Elsevier Inc.

The success of technical college students in relation to scores on attitude, personality and intelligence tests

DUE TO COPYRIGHT RESTRICTIONS ONLY AVAILABLE FOR CONSULTATION AT ASTON UNIVERSITY LIBRARY AND INFORMATION SERVICES WITH PRIOR ARRANGEMENT

Is ambient intelligence a truly human-centric paradigm in industry? Current research and application scenario

Based on the paper presented at the International Conference “Autonomous Systems: inter-relations of technical and societal issues”, organized by IET with the support of the Portuguese-German collaboration project on “Technology Assessment of Autonomous Robotics” (DAAD/CRUP) at FCT-UNL, Biblioteca da UNL, Campus de Caparica on 5-6 November 2009.

Environmental Decision Support: a Distributed Artificial Intelligence Approach

Decision making in any environmental domain is a complex and demanding activity, justifying the development of dedicated decision support systems. Every decision is confronted with a large variety and amount of constraints to satisfy as well as contradictory interests that must be sensibly accommodated. The first stage of a project evaluation is its submission to the relevant group of public (and private) agencies. The individual role of each agency is to verify, within its domain of competence, the fulfilment of the set of applicable regulations. The scope of the involved agencies is wide and ranges from evaluation abilities on the technical or economical domains to evaluation competences on the environmental or social areas. The second project evaluation stage involves the gathering of the recommendations of the individual agencies and their justified merge to produce the final conclusion. The incorporation and accommodation of the consulted agencies opinions is of extreme importance: opinions may not only differ, but can be interdependent, complementary, irreconcilable or, simply, independent. The definition of adequate methodologies to sensibly merge, whenever possible, the existing perspectives while preserving the overall legality of the system, will lead to the making of sound justified decisions. The proposed Environmental Decision Support System models the project evaluation activity and aims to assist developers in the selection of adequate locations for their projects, guaranteeing their compliance with the applicable regulations.

Dados de reconhecimento facial em Business Intelligence

Vivemos cada vez mais numa era de crescentes avanços tecnológicos em diversas áreas. O que há uns anos atrás era considerado como praticamente impossível, em muitos dos casos, já se tornou realidade. Todos usamos tecnologias como, por exemplo, a Internet, Smartphones e GPSs de uma forma natural. Esta proliferação da tecnologia permitiu tanto ao cidadão comum como a organizações a sua utilização de uma forma cada vez mais criativa e simples de utilizar. Além disso, a cada dia que passa surgem novos negócios e startups, o que demonstra o dinamismo que este crescimento veio trazer para a indústria. A presente dissertação incide sobre duas áreas em forte crescimento: Reconhecimento Facial e Business Intelligence (BI), assim como a respetiva combinação das duas com o objetivo de ser criado um novo módulo para um produto já existente. Tratando-se de duas áreas distintas, é primeiramente feito um estudo sobre cada uma delas. A área de Business Intelligence é vocacionada para organizações e trata da recolha de informação sobre o negócio de determinada empresa, seguindo-se de uma posterior análise. A grande finalidade da área de Business Intelligence é servir como forma de apoio ao processo de tomada de decisão por parte dos analistas e gestores destas organizações. O Reconhecimento Facial, por sua vez, encontra-se mais presente na sociedade. Tendo surgido no passado através da ficção científica, cada vez mais empresas implementam esta tecnologia que tem evoluído ao longo dos anos, chegando mesmo a ser usada pelo consumidor final, como por exemplo em Smartphones. As suas aplicações são, portanto, bastante diversas, desde soluções de segurança até simples entretenimento. Para estas duas áreas será assim feito um estudo com base numa pesquisa de publicações de autores da respetiva área. Desde os cenários de utilização, até aspetos mais específicos de cada uma destas áreas, será assim transmitido este conhecimento para o leitor, o que permitirá uma maior compreensão por parte deste nos aspetos relativos ao desenvolvimento da solução. Com o estudo destas duas áreas efetuado, é então feita uma contextualização do problema em relação à área de atuação da empresa e quais as abordagens possíveis. É também descrito todo o processo de análise e conceção, assim como o próprio desenvolvimento numa vertente mais técnica da solução implementada. Por fim, são apresentados alguns exemplos de resultados obtidos já após a implementação da solução.

Orthogonal higher order structure and confirmatory factor analysis of the French Wechsler Adult Intelligence Scale (WAIS-III).

According to the most widely accepted Cattell-Horn-Carroll (CHC) model of intelligence measurement, each subtest score of the Wechsler Intelligence Scale for Adults (3rd ed.; WAIS-III) should reflect both 1st- and 2nd-order factors (i.e., 4 or 5 broad abilities and 1 general factor). To disentangle the contribution of each factor, we applied a Schmid-Leiman orthogonalization transformation (SLT) to the standardization data published in the French technical manual for the WAIS-III. Results showed that the general factor accounted for 63% of the common variance and that the specific contributions of the 1st-order factors were weak (4.7%-15.9%). We also addressed this issue by using confirmatory factor analysis. Results indicated that the bifactor model (with 1st-order group and general factors) better fit the data than did the traditional higher order structure. Models based on the CHC framework were also tested. Results indicated that a higher order CHC model showed a better fit than did the classical 4-factor model; however, the WAIS bifactor structure was the most adequate. We recommend that users do not discount the Full Scale IQ when interpreting the index scores of the WAIS-III because the general factor accounts for the bulk of the common variance in the French WAIS-III. The 4 index scores cannot be considered to reflect only broad ability because they include a strong contribution of the general factor.

On advancing business intelligence in the electricity retail market

In recent decades, business intelligence (BI) has gained momentum in real-world practice. At the same time, business intelligence has evolved as an important research subject of Information Systems (IS) within the decision support domain. Today’s growing competitive pressure in business has led to increased needs for real-time analytics, i.e., so called real-time BI or operational BI. This is especially true with respect to the electricity production, transmission, distribution, and retail business since the law of physics determines that electricity as a commodity is nearly impossible to be stored economically, and therefore demand-supply needs to be constantly in balance. The current power sector is subject to complex changes, innovation opportunities, and technical and regulatory constraints. These range from low carbon transition, renewable energy sources (RES) development, market design to new technologies (e.g., smart metering, smart grids, electric vehicles, etc.), and new independent power producers (e.g., commercial buildings or households with rooftop solar panel installments, a.k.a. Distributed Generation). Among them, the ongoing deployment of Advanced Metering Infrastructure (AMI) has profound impacts on the electricity retail market. From the view point of BI research, the AMI is enabling real-time or near real-time analytics in the electricity retail business. Following Design Science Research (DSR) paradigm in the IS field, this research presents four aspects of BI for efficient pricing in a competitive electricity retail market: (i) visual data-mining based descriptive analytics, namely electricity consumption profiling, for pricing decision-making support; (ii) real-time BI enterprise architecture for enhancing management’s capacity on real-time decision-making; (iii) prescriptive analytics through agent-based modeling for price-responsive demand simulation; (iv) visual data-mining application for electricity distribution benchmarking. Even though this study is from the perspective of the European electricity industry, particularly focused on Finland and Estonia, the BI approaches investigated can: (i) provide managerial implications to support the utility’s pricing decision-making; (ii) add empirical knowledge to the landscape of BI research; (iii) be transferred to a wide body of practice in the power sector and BI research community.

Add a Dash of Rhetoric, a Pinch of Technical Communication, a Handful of Pedagogy, and Mix Well: Cookbooks and Recipes as Instructional Texts, and What Domestic Texts from 1870 to 1935 Can Teach Us About Technical Communication

Through the use of rhetoric centered on authority and risk avoidance, scientific method has co-opted knowledge, especially women's everyday and experiential knowledge in the domestic sphere. This, in turn, has produced a profound affect on technical communication in the present day. I am drawing on rhetorical theory to study cookbooks and recipes for their contributions to changes in instructional texts. Using the rhetorical lenses of metis (cunning intelligence), kairos (timing and fitness) and mneme (memory), I examine the way in which recipes and cookbooks are constructed, used and perceived. This helps me uncover lost voices in history, the voices of women who used recipes, produced cookbooks and changed the way instructions read. Beginning with the earliest cookbooks and recipes, but focusing on the pivotal temporal interval of 1870-1935, I investigate the writing and rhetorical forces shaping instruction sets and domestic discourse. By the time of scientific cooking and domestic science, everyday and experiential knowledge were being excluded to make room for scientific method and the industrial values of the public sphere. In this study, I also assess how the public sphere, via Cooperative Extension Services and other government agencies, impacted the domestic sphere, further devaluing everyday knowledge in favor of the public scientific model. I will show how the changes in the production of food, cookbooks and recipes were related to changes in technical communication. These changes had wide rippling effects on the field of technical communication. By returning to some of the tenets and traditions of everyday and experiential knowledge, technical communication scholars, practitioners and instructors today can find new ways to encounter technical communication, specifically regarding the creation of instructional texts. Bringing cookbooks, recipes and everyday knowledge into the classroom and the field engenders a new realm of epistemological possibilities.

Job Intelligence-Services für Hochschulen

Internetbasierte Jobportale liefern in Form von Stellenanzeigen eine interessante Datengrundlage, um Qualifikationsanforderungen von nachfragenden Unternehmen an potenzielle Hochschulabsolventen transparent zu machen. Hochschulen können durch Analyse dieser Qualifikationsanforderungen das eigene Aus- und Weiterbildungsangebot arbeitsmarktorientiert weiterentwickeln und sich somit in der Hochschullandschaft profilieren. Hierfür ist es indes erforderlich, die Stellenanzeigen aus Jobportalen zu extrahieren und mithilfe adäquater analytischer Informationssysteme weiter zu verarbeiten. In diesem Beitrag zum CampusSource White Paper Award wird ein Konzept für Job Intelligence-Services vorgestellt, die die systematische Analyse von Qualifikationsanforderungen auf Grundlage von Stellenanzeigen aus Jobportalen gestatten.

A vision based aerial rbot solution for the IARC 2014 by the Technical University of Madrid

The IARC competitions aim at making the state of the art in UAV progress. The 2014 challenge deals mainly with GPS/Laser denied navigation, Robot-Robot interaction and Obstacle avoidance in the setting of a ground robot herding problem. We present in this paper a drone which will take part in this competition. The platform and hardware it is composed of and the software we designed are introduced. This software has three main components: the visual information acquisition, the mapping algorithm and the Aritificial Intelligence mission planner. A statement of the safety measures integrated in the drone and of our efforts to ensure field testing in conditions as close as possible to the challenge?s is also included.

Demand bibliography : machine intelligence /

"Results from a search of the technical report database over a 10-year period ... references cover only unclassified, unlimited document references with abstracts."

Technical data digest.

Title from cover.

Sharing secrets with lawmakers : Congress as a user of intelligence /

"February 1997."

Customer information system data pre-processing with feature selection techniques for non-technical losses prediction in an electricity market

Non-technical losses (NTL) identification and prediction are important tasks for many utilities. Data from customer information system (CIS) can be used for NTL analysis. However, in order to accurately and efficiently perform NTL analysis, the original data from CIS need to be pre-processed before any detailed NTL analysis can be carried out. In this paper, we propose a feature selection based method for CIS data pre-processing in order to extract the most relevant information for further analysis such as clustering and classifications. By removing irrelevant and redundant features, feature selection is an essential step in data mining process in finding optimal subset of features to improve the quality of result by giving faster time processing, higher accuracy and simpler results with fewer features. Detailed feature selection analysis is presented in the paper. Both time-domain and load shape data are compared based on the accuracy, consistency and statistical dependencies between features.