Non-numerical Information Research Articles

Exchange rate prediction with non-numerical information

Exchange rate prediction is an important yet challenging problem in financial time series analysis. Although the historical exchange rates can provide valuable information, other factors will also affect the prediction significantly. These factors could be numerical or non-numerical ones, which are related to politics, economics, military, or even market psychology. Previous automatic exchange rate prediction merely considers numerical data (or simply the historical rates) for predicting the next day value. In this paper, we show how to utilize and combine many related factors, both numerical and non-numerical factors, for exchange rate prediction. With an example on forecasting exchange rate between US dollar and Japanese yen, we investigate how to exploit the information from non-numerical factors. We then engage a novel integrated approach which successfully combines information obtained from both numerical and non-numerical factors. We show how to quantify the non-numerical fundamental information, provide details steps on how to construct single predictors on different kinds of information separately, and finally describe how to integrate these separate predictors. Experimental results showed that our method can achieve the Directional Symmetry (DS) accuracy of 86.96%, which is much higher than only exploiting numerical information.

Use of Number by Fish

BackgroundResearch on human infants, mammals, birds and fish has demonstrated that rudimentary numerical abilities pre-date the evolution of human language. Yet there is controversy as to whether animals represent numbers mentally or rather base their judgments on non-numerical perceptual variables that co-vary with numerosity. To date, mental representation of number has been convincingly documented only for a few mammals.Methodology/Principal FindingsHere we used a training procedure to investigate whether mosquitofish could learn to discriminate between two and three objects even when denied access to non-numerical information. In the first experiment, fish were trained to discriminate between two sets of geometric figures. These varied in shape, size, brightness and distance, but no control for non-numerical variables was made. Subjects were then re-tested while controlling for one non-numerical variable at a time. Total luminance of the stimuli and the sum of perimeter of figures appeared irrelevant, but performance dropped to chance level when stimuli were matched for the cumulative surface area or for the overall space occupied by the arrays, indicating that these latter cues had been spontaneously used by the fish during the learning process. In a second experiment, where the task consisted of discriminating 2 vs 3 elements with all non-numerical variables simultaneously controlled for, all subjects proved able to learn the discrimination, and interestingly they did not make more errors than the fish in Experiment 1 that could access non-numerical information in order to accomplish the task.Conclusions/SignificanceMosquitofish can learn to discriminate small quantities, even when non-numerical indicators of quantity are unavailable, hence providing the first evidence that fish, like primates, can use numbers. As in humans and non-human primates, genuine counting appears to be a ‘last resort’ strategy in fish, when no other perceptual mechanism may suggest the quantity of the elements. However, our data suggest that, at least in fish, the priority of perceptual over numerical information is not related to a greater cognitive load imposed by direct numerical computation.

Naming speed and effortful and automatic inhibition in children with arithmetic learning disabilities

We report a two-year longitudinal study aimed at investigating the rate of access to numerical and non-numerical information in long-term memory and the functioning of automatic and effortful cognitive inhibition processes in children with arithmetical learning disabilities (ALDs). Twelve children with ALDs, of age 9.3 years, and twelve gender–age-matched controls were involved in the study. Rate of access was measured through digit- and letter-naming tasks, automatic cognitive inhibition was measured using a negative priming paradigm, and effortful cognitive inhibition was measured rating intrusion errors in a working memory task. Children with ALDs suffered from a deficit in the speed of activating both numerical and non-numerical information from long-term memory and in effortful inhibition mechanisms. No evidence for dysfunction of the automatic inhibition processes was found.

Forecast with the use of statistical and expert methods

Consideration is given to a combination of different methods for the forecast of values of the social-economic index. One group of methods estimate the value of the index in the future by econometric analysis basing on its dynamics in the past. A new notion of optimal initial vector of forecast is introduced. Other methods are based on experts' forecast whose conclusions accumulate nonnumerical, incomplete, and inexact information. The final estimate is delivered by a combination of econometric and expert forecasts with weighting coefficients; they are chosen by a researcher taking the volume and quality of the used expert and statistical information into account.

Robot Brains. Circuits and Systems for Conscious Machines (P. Haikonen; 2007) [Book review

In the past few years, various attempts to define the problem of consciousness from engineering or computational perspective have emerged. This book explores the topic of what will make a robot conscious. It outlines an engineering approach that should lead toward cognitive and conscious machines. Some of the topics covered include: a vector representation of information as a substitute for nonnumerical information processing by brains; neuron models and associate neural networks; circuit assemblies; machine perception; motor control; machine cognition; machine emotions; natural language understanding; cognitive architecture; and machine consciousness. The book should be interesting to people working in computational intelligence and cognitive robots. Researchers in computational neuroscience, who usually focus on details, may also benefit from the integrative approach presented in this book. While the book introduces a number of interesting points of view, no breakthrough technologies are proposed and no software or hardware demonstration is provided.

Does Using Nonnumerical Terms to Describe Risk Aid Violence Risk Communication?

Actuarial risk assessments yield valid numerical information about violence risk, but research suggests that forensic clinicians prefer to communicate risk using nonnumerical information (i.e., verbal terms such as high risk). In an experimental questionnaire study, 60 forensic clinicians disagreed on the interpretation of nonnumerical terms, and their nonnumerical risk estimates for one group of violent offenders were influenced by comparison with another group. Adding nonnumerical terms to numerical probability statements had no effect on hypothetical forensic decisions. These findings suggest that nonnumerical descriptive terms do not aid effective communication of violence risk and that contextual information might artificially affect estimated risk.

Cognitive Impairments of Children with SevereArithmetic Difficulties: Cognitive Deficit orDevelopmental Lag?

An age-matched/achievement-matched design was utilized to examine the cognitive functioning of children with severe arithmetic difficulties. A battery of cognitive tasks was administered to three groups of elementary aged children: 20 children with severe arithmetic difficulties (SAD), 20 children matched in age (CAM) to the children with SAD, and 20 younger children matched in arithmetic achievement (AAM) to the children with SAD. Measures were related to processing speed, short-term memory, verbal working memory, and visual-spatial working memory. Results suggest three important fi ndings. First, in contrast to previous studies, children with SAD did not show a processing speed impairment. Second, children with SAD were impaired in short-term memory for numerical and non-numerical information. And third, while children with SAD displayed working memory impairments, these impairments were not uniform within verbal working memory or visualspatial working memory. Taken together, findings indicate that previous studies that have reported differences between children with SAD and their normally achieving peers might have overestimated or mischaracterized the differential cognitive functioning of these groups. Results are discussed within a framework that views the cognitive functioning impairments of children with SAD as representative of a developmental lag rather than a cognitive deficit.

Measurement of a Discrete Indicator Utilizing Nonnumerical, Inaccurate, and Incomplete Information

In accordance with the requirements of the international Guide to the Expression of Uncertainty in Measurement, a new Bayes model has been developed for estimating the mathematical expectation and variance of a random quantity modeling the uncertainty of the result of a measurement of a discrete indicator. The model makes it possible to utilize nonnumerical, inaccurate, and incomplete information concerning the probability distribution of this random quantity.

Agro-Librex; Agro-Agen; Agro-Konf: Bibliographic Database

Review: Agro-Librex; Agro-Agen; Agro-Konf: Bibliographic Database By The University of Agriculture Library in Poznan Reviewed by Maria Anna Jankowska University of Idaho Library, USA University of Agriculture Library in Poznan. Agro-Librex; Agro-Agen; Agro- Konf: Bibliographic Data Base (3rd ed.). Poznan, Poland: Main Library, University of Agriculture, 2000. US$100. To order: Main Library, 45 Witosa Street, 61-693 Poznan, Poland, TEL: 4861-8487809. CD-ROM database and searching program; Hardware requirements: Windows 95/98: 16Mb RAM, 8- bit color display, 15Mb free hard-disk space, CDS/ISIS software, and CD- ROM drive. The AGRO database is the largest Polish index to literature on biology, agriculture, horticulture, forestry, animal science, veterinary, food, wood, technology, and environmental science. One Agro CD-ROM contains three separate databases: Agro-Librex, Agro-Agen, and Agro-Konf. The first database, Agro-Librex, provides bibliographic citations from more than 600 Polish periodicals. The second index, Agro-Agen, offers citations from around one hundred periodicals published in English. The third database, Agro-Konf, makes available citations from more than 8,000 published conference proceedings. The entire Agro database, with over 128,000 bibliographic records, is updated quarterly and produced by librarians from the Main Library and Information Center of the Agriculture University in Poznan. Micro CDS/ISIS advanced non-numerical information storage and retrieval software is used to create the Agro database. Extensive keyword indexing permits users to search the three databases by authors, titles of articles, journals, conference name and place, and keywords. The retrieved citation presents detailed information on title, author, journal title, volume, issue, year, pages, publisher, the main words used in the article, contact addresses for authors or publishers, and language. The Agro database does not contain abstracts but each citation includes carefully selected keywords that represent the main concept of the indexed record. The index has been produced since 1992, when Wlodzimierz Golab, director of the Agriculture University Library, convinced the staff about the importance of creating an electronic tool for locating Polish literature in all areas of agriculture from agricultural administration, laws and legislation, regulations, economics, education and training, engineering, products to horticulture, animal science, entomology, aquatic science, fisheries, food science, food products, forestry, geography, meteorology, climatology, history, home economics, human ecology, household textiles and clothing,

Accounting for language differences

Human numerical abilities are characterized by an advanced concept of number that appears to be fundamentally different from that of other mammals. The ultimate intellectual and cultural result of these abilities, perhaps, is formal mathematics, which has its own language. Intriguingly, many people who are fluent in a second spoken and written language nonetheless fall into their native tongue when they have to do arithmetic. So what exactly is the nature of the relationship between human concepts of number and language? Recent experiments involving Russian–English bilingual college students have provided some fascinating insights 1. In these experiments, subjects were taught new arithmetic operations and equations, and numerical or non-numerical historical and geographical information, in both English and Russian. The tasks that subjects had to learn and perform included addition, multiplication, estimation of logarithms and cube roots, and questions on (fictitious) approximate historical dates. Measures of performance included response speed and accuracy. A key result was that subjects retrieved information about exact numbers more effectively in the language of training, whereas retrieval in both languages was equally effective for approximate number and non-numerical information.

A multivariate qualitative model for the prediction of daily global radiation from three hourly global radiation values

A new model for the prediction of daily global radiation using three hourly radiation values is proposed. This model is obtained by multivariate regression analysis. The hourly clearness index and various qualitative variables are used as independent variables. The hourly values are obtained from net ground measures of hourly global radiation corresponding to the hours in which Meteosat secondary images are available over Europe. The qualitative variables allow us to include additional non-numerical information, specifically, the season of the year. The proposed model is the same for all the locations analysed. This model can be used for the prediction of daily global radiation based on hourly global radiation data obtained from satellite images.

Language and number: a bilingual training study

Three experiments investigated the role of a specific language in human representations of number. Russian–English bilingual college students were taught new numerical operations (Experiment 1), new arithmetic equations (Experiments 1 and 2), or new geographical or historical facts involving numerical or non-numerical information (Experiment 3). After learning a set of items in each of their two languages, subjects were tested for knowledge of those items, and new items, in both languages. In all the studies, subjects retrieved information about exact numbers more effectively in the language of training, and they solved trained problems more effectively than untrained problems. In contrast, subjects retrieved information about approximate numbers and non-numerical facts with equal efficiency in their two languages, and their training on approximate number facts generalized to new facts of the same type. These findings suggest that a specific, natural language contributes to the representation of large, exact numbers but not to the approximate number representations that humans share with other mammals. Language appears to play a role in learning about exact numbers in a variety of contexts, a finding with implications for practice in bilingual education. The findings prompt more general speculations about the role of language in the development of specifically human cognitive abilities.

Bayesian reasoning on qualitative descriptions from images and speech

Image understanding denotes not only the ability to extract specific, non-numerical information from images, but it implies also reasoning about the extracted information. We propose a qualitative representation for image understanding results, which is suitable for reasoning with Bayesian networks. Our qualitative representation is enhanced with probabilistic information to represent uncertainties and errors in the understanding of noisy sensory data. The probabilistic information is supplied to a Bayesian network in order to find the most plausible interpretation. We apply this approach for the integration of image and speech understanding in a scenario where we want to find objects in a visually observed scene which are verbally described by a human. Results demonstrate the performance of our approach.

Knowledge‐Based Generation of the Activity Process in Wooden Construction Systems

In order to develop new, improved systems for building construction, it is necessary to evaluate the various factors related to construction methodology. This paper focuses on nonnumerical information such as the assembly order and activity procedures for building members used in wooden construction systems and aims at developing a knowledge‐based system (KBS) for generation and control of this information. The process involves dividing the building construction system into basic units, defining and describing those units, and then inputting this information into a computer‐based KBS. The system then produces a detailed output of the assembly order and processing steps for each of the wooden members used in the structure. This system is applied to various model structures, and the assembly order and activity procedures generated are demonstrated to be accurate. Therefore, the system can be used as a tool for evaluating new wooden building construction systems.

Decision making in complex systems

Individuals, organizations, and governments are often expected to make decisions of far-reaching consequences. Judgment and decision-making capabilities are important facets of human intelligence. Systematic studies of these topics have commenced only in the 1960s. Simultaneous developments in computer hardware and software and in fields such as artificial intelligence have given impetus to the study of human decision making from descriptive, normative, and prescriptive points of view. Realworld decision problems are often unstructured and difficult to formulate. There are multiple objectives, distributed decision makers and difficulties in acquiring different types of knowledge needed for problem solving. Human knowledge is often available in natural language with its inherent ambiguity and vagueness. While a human being has only “bounded rationality,” his intuition and common sense enable him to make good decisions in using qualitative nonnumerical information in narrow domains of expertise such as medical diagnosis. He has to be supported by decision aids when confronted with situations in complex systems. In this paper, we briefly review decision making in complex systems from the point of view of intelligent decision support systems, which applications to the project management task.

Optical content-addressable parallel processor: architecture, algorithms, and design concepts

Associative processing based on content-addressable memories has been argued to be the natural solution for nonnumerical information processing applications. Unfortunately, the implementation requirements of these architectures when one uses conventional electronic technology have been cost prohibitive; therefore associative processors have not been realized. Instead, software methods that emulate the behavior of associative processing have been promoted and mapped onto conventional locationaddressable systems. However, this does not bring about the natural parallelism of associative processing, namely, the ability to access many data words simultaneously. Optics has the advantage over electronics of directly supporting associative processing by providing economic and efficient interconnects, massive parallelism, and high-speed processing. The principles of designing an optical content-addressable parallel processor (OCAPP) for the efficient support of parallel symbolic computing are presented. The architectu re is designed to exploit optics advantages fully in interconnects and high-speed operations. Several parallel search-and-retrieval algorithms are mapped onto an OCAPP to illustrate its capability of supporting parallel symbolic computing. A theoretical performance analysis of these algorithms is presented. This analysis reveals that the execution times of the parallel algorithms presented are independent of the problem size, which makes the OCAPP suitable for applications in which the number of data sets to be operated on is high (e.g., massive parallel processing). A preliminary optical implementation of the architecture with currently available optical components is also presented.

The computer and non-numerical information: on the evolution of the class of landlords in Romania (1857-1918)

The computer and non-numerical information: on the evolution of the class of landlords in Romania (1857-1918)

An Axiomatic Theory of Accounting Measurement

The article suggests a descriptive, axiomatic type of conceptual framework for conventional accounting measurement practice. The disclosure problem in financial accounting is caused by the need to decide what, of all the available numerical and nonnumerical information, to include in a set of financial reports. The measurement problem in financial accounting is chiefly concerned with explaining the nature of the specifically numerical information produced by accounting systems, whether or not it is disclosed in financial statements. The problems of measuring the accounting attribute remain constant even though the resulting numerical information may be disclosed to differing third parties such as management, investors and creditors. The common assumptions which are made by different user groups concerning the numerical information contained in financial statements are arithmetic in character. As soon as these arithmetic properties are questioned, however, it becomes clear that they are not self-evident. The problems raised in interpreting the arithmetic properties of accounting data appear to be due to the accountant's lack of understanding of the attribute which is being measured in financial statements.

Information Processing with an Associative Parallel Processor

Research into new computer structures, which would be better suited to non-numerical information processing tasks, has been in progress for some years.1,2,3The problem has been to design a computing system with high hardware efficiency and low software complexity over a wide range of these applications. Recent research4,5,6has indicated that these apparently conflicting requirements could possibly be achieved by a parallel processing system containing content-addressable storage. Hence there is a revival of interest in associative memories and associative processors.

Insight, Not Numbers

Insight, Not Numbers