Equivalence Rule Research Articles

The Scaling of Abundance in Consumers and Their Resources: Implications for the Energy Equivalence Rule

The negative scaling of plant and animal abundance with body mass is one of the most fundamental relationships in ecology. However, theoretical approaches to explain this phenomenon make the unrealistic assumption that species share a homogeneous resource. Here we present a simple model linking mass and metabolism with density that includes the effects of consumer size on resource characteristics (particle size, density, and distribution). We predict patterns consistent with the energy equivalence rule (EER) under some scenarios. However, deviations from EER occur as a result of variation in resource distribution and productivity (e.g., due to the clumping of prey or variation in food particle size selection). We also predict that abundance scaling exponents change with the dimensionality of the foraging habitat. Our model predictions explain several inconsistencies in the observed scaling of vertebrate abundance among ecological and taxonomic groups and provide a broad framework for understanding variation in abundance.

A Novel Generic Hebbian Ordering-Based Fuzzy Rule Base Reduction Approach to Mamdani Neuro-Fuzzy System

There are two important issues in neuro-fuzzy modeling: (1) interpretability--the ability to describe the behavior of the system in an interpretable way--and (2) accuracy--the ability to approximate the outcome of the system accurately. As these two objectives usually exert contradictory requirements on the neuro-fuzzy model, certain compromise has to be undertaken. This letter proposes a novel rule reduction algorithm, namely, Hebb rule reduction, and an iterative tuning process to balance interpretability and accuracy. The Hebb rule reduction algorithm uses Hebbian ordering, which represents the degree of coverage of the samples by the rule, as an importance measure of each rule to merge the membership functions and hence reduces the number of the rules. Similar membership functions (MFs) are merged by a specified similarity measure in an order of Hebbian importance, and the resultant equivalent rules are deleted from the rule base. The rule with a higher Hebbian importance will be retained among a set of rules. The MFs are tuned through the least mean square (LMS) algorithm to reduce the modeling error. The tuning of the MFs and the reduction of the rules proceed iteratively to achieve a balance between interpretability and accuracy. Three published data sets by Nakanishi (Nakanishi, Turksen, & Sugeno, 1993), the Pat synthetic data set (Pal, Mitra, & Mitra, 2003), and the traffic flow density prediction data set are used as benchmarks to demonstrate the effectiveness of the proposed method. Good interpretability, as well as high modeling accuracy, are derivable simultaneously and are suitably benchmarked against other well-established neuro-fuzzy models.

Правило эквивалентности в полевой и силовой магнитостатике

Правило эквивалентности в полевой и силовой магнитостатике

The Scaling of Abundance in Consumers and Their Resources: Implications for the Energy Equivalence Rule

The negative scaling of plant and animal abundance with body mass is one of the most fundamental relationships in ecology. However, theoretical approaches to explain this phenomenon make the unrealistic assumption that species share a homogeneous resource. Here we present a simple model linking mass and metabolism with density that includes the effects of consumer size on resource characteristics (particle size, density, and distribution). We predict patterns consistent with the energy equivalence rule (EER) under some scenarios. However, deviations from EER occur as a result of variation in resource distribution and productivity (e.g., due to the clumping of prey or variation in food particle size selection). We also predict that abundance scaling exponents change with the dimensionality of the foraging habitat. Our model predictions explain several inconsistencies in the observed scaling of vertebrate abundance among ecological and taxonomic groups and provide a broad framework for understanding variation in abundance.

Estimating Heterogeneous EBA and Economic Screening Rule Choice Models

Consumer choice in surveys and in the marketplace reflects a complex process of screening and evaluating choice alternatives. Behavioral and economic models of choice processes are difficult to estimate when using stated and revealed preferences because the underlying process is latent. This paper introduces Bayesian methods for estimating two behavioral models that eliminate alternatives using specific attribute levels. The elimination by aspects theory postulates a sequential elimination of alternatives by attribute levels until a single one, the chosen alternative, remains. In the economic screening rule model, respondents screen out alternatives with certain attribute levels and then choose from the remaining alternatives, using a compensatory function of all the attributes. The economic screening rule model gives an economic justification as to why certain attributes are used to screen alternatives. A commercial conjoint study is used to illustrate the methods and assess their performance. In this data set, the economic screening rule model outperforms the EBA and other standard choice models and provides comparable results to an equivalent conjunctive screening rule model.

The best currently known class of dynamically equivalent cellular automata rules for density classification

The possibility of performing computations with cellular automata (CAs) opens up new conceptual issues in emergent computation. Driven by this motivation, a recurring problem in this context is the automatic search for good one-dimensional, binary CA rules that can perform well in the density classification task (DCT), that is, the ability to discover which cell state outnumbers the other state. In the past, the most successful attempts to reach this target have relied on evolutionary searches in the space of possible rules. Along this line, a multiobjective, heuristic evolutionary approach, implemented as a distributed cooperative system, is presented here, which yielded outstanding results, including a rule that led to the characterisation of a class of four equivalent rules, all of them with the best performance currently available in the literature for the DCT.

The interspecific relationship between abundance and body size in central European land snail assemblages

Summary The distributions of abundance and body size and the interspecific relationship between abundance and body size in Central European assemblages of terrestrial snails were analysed to investigate whether the characteristics of land snails, especially their limited active dispersal abilities, result in differences from the macroecological patterns mainly found in analyses of vertebrates. The distributions of crude density (number of specimens divided by the sum of the sampled areas) and ecological density (number of specimens divided by the sum of the areas sampled in the habitat types where a given species had been recorded) and of body size are approximately log-normal. Controlling for phylogenetic relationships there was a significant positive correlation between the number of habitat types occupied by a species and its crude and ecological density. The negative relationship between the two measures of abundance and body size found in the across-species analyses could not be confirmed in the phylogenetic contrasts analyses. The slopes of the body size–abundance relations are shallower than predicted by the energetic equivalence rule, even if only the upper bound slopes are considered and irrespective of the regression method used. This indicates that large snail species control a greater proportion of available resources than smaller species. Most of the macroecological patterns found in land snails are similar to those of other animal groups. An exception is the approximately log-normal distribution of log-transformed body sizes which may be a consequence of the better passive dispersal ability of smaller snails.

Packet classifiers in ternary CAMs can be smaller

Serving as the core component in many packet forwarding, differentiating and filtering schemes, packet classification continues to grow its importance in today's IP networks. Currently, most vendors use Ternary CAMs (TCAMs) for packet classification. TCAMs usually use brute-force parallel hardware to simultaneously check for all rules. One of the fundamental problems of TCAMs is that TCAMs suffer from range specifications because rules with range specifications need to be translated into multiple TCAM entries. Hence, the cost of packet classification will increase substantially as the number of TCAM entries grows. As a result, network operators hesitate to configure packet classifiers using range specifications. In this paper, we optimize packet classifier configurations by identifying semantically equivalent rule sets that lead to reduced number of TCAM entries when represented in hardware. In particular, we develop a number of effective techniques, which include: trimming rules, expanding rules, merging rules, and adding rules. Compared with previously proposed techniques which typically require modifications to the packet processor hardware, our scheme does not require any hardware modification, which is highly preferred by ISPs. Moreover, our scheme is complementary to previous techniques in that those techniques can be applied on the rule sets optimized by our scheme. We evaluate the effectiveness and potential of the proposed techniques using extensive experiments based on both real packet classifiers managed by a large tier-1 ISP and synthetic data generated randomly. We observe significant reduction on the number of TCAM entries that are needed to represent the optimized packet classifier configurations.

Numerical simulation study of the state variable correlation function of a bistable system subject to cross-correlated noises

We apply a numerical simulation method to study a normalized correlation function C(t) of a bistable system driven by cross-correlated noises. Based on a stochastic equivalent rule, we get a stochastic equivalent Stratonovich stochastic differential equation driven by Gaussian white noise for a bistable system driven by cross-correlated noises. Making use of a differential equation, C(t) was calculated by the numerical simulation procedure. Comparing C(t) calculated by the projection operator method of theoretics approximation to C(t) by the numerical simulation procedure, we find: (i) the difference in C(t) between the result of the theoretics approximation and that of the numerical simulation procedure is very small, i.e. the two results are approximately consistent; (ii) there is no difference in C(t) between the result of the theoretics approximation and the result of the numerical simulation procedure when the decay time t is large, i.e. they are entirely consistent; (iii) when the projection operator method is used to calculate C(t), the effects of higher orders of memory can be neglected.

Energetic equivalence in a soil arthropod community from an aspen–conifer forest

Summary We evaluated the energetic equivalence rule for a community of litter and soil arthropods from an aspen–conifer forest in the Sangre de Cristo Mountains of southwestern North America. We found that across taxa and within trophic groups the number of arthropods per square meter, N , scaled with body mass, M , raised to the −0.78 power and that primary and secondary decomposers, combined, were 8.51 times more abundant than carnivores. Given that arthropod abundance scaled as M −0.78 and that soil invertebrate metabolic rates, Q , scale approximately as M 0.78 , it appears that within coarse trophic groups at our study site, energy use by soil arthropod populations, Q tot ∝ NQ , is approximately independent of body size, Q tot ∝ M −0.78 M 0.78 ∝ M 0 .

Selected Papers from InTech'04

The main objective of the annual International Conference on Intelligent Technologies (InTech) is to bring together researchers and practitioners who implement intelligent and fuzzy technologies in real-world environment. The Fifth International Conference on Intelligent Technologies InTech'04 was held in Houston, Texas, on December 2-4, 2004. Topics of InTech'04 included mathematical foundations of intelligent technologies, traditional Artificial Intelligent techniques, uncertainty processing and methods of soft computing, learning/adaptive systems/data mining, and applications of intelligent technologies. This special issue contains versions of 15 selected papers originally presented at InTech'04. These papers cover most of the topics of the conference. Several papers describe new applications of the existing intelligent techniques. R. Aló{o} et al. show how traditional <I>statistical</I> hypotheses testing techniques – originally designed for processing measurement results – need to be modified when applied to simulated data – e.g., when we compare the quality of two algorithms. Y. Frayman et al. use <I>mathematical morphology</I> and <I>genetic algorithms</I> in the design of a machine vision system for detecting surface defects in aluminum die casting. Y. Murai et al. propose a new faster <I>entropy</I>-based placement algorithm for VLSI circuit design and similar applications. A. P. Salvatore et al. show how <I>expert system</I>-type techniques can help in scheduling botox treatment for voice disorders. H. Tsuji et al. propose a new method, based on <I>partial differential equations</I>, for automatically identifying and extracting objects from a video. N. Ward uses <I>Ordered Weighted Average</I> (OWA) techniques to design a model that predicts admission of computer science students into different graduate schools. An important aspect of intelligence is ability to <I>learn</I>. In A. Mahaweerawat et al., neural-based machine learning is <I>used</I> to identify and predict software faults. J. Han et al. show that we can drastically <I>improve</I> the quality of machine learning if, in addition to discovering traditional (positive) rules, we also search for negative rules. A serious problem with many neural-based machine learning algorithms is that often, the results of their learning are un-intelligible rules and numbers. M. I. Khan et al. show, on the example of robotic arm applications, that if we allow neurons with different input-output dependencies – including linear neurons – then we can <I>extract</I> meaningful <I>knowledge</I> from the resulting network. Several papers analyze the Equivalent Transformation (ET) model, that allows the user to <I>automatically generate code from specifications</I>. A general description of this model is given by K. Akama et al. P. Chippimolchai et al. describe how, within this model, we can transform a user's query into an equivalent more efficient one. H. Koike et al. apply this approach to <I>natural language processing</I>. Y. Shigeta et al. show how the existing <I>constraint</I> techniques can be translated into equivalent transformation rules and thus, combined with other specifications. I. Takarajima et al. extend the ET approach to situations like <I>parallel computations</I>, where the order in which different computations are performed on different processors depends on other processes and is, thus, non-deterministic. Finally, a paper by J. Chandra – based on his invited talk at InTech'04 – describes a <I>general framework</I> for robust and resilient critical infrastructure systems, with potential applications to transportation systems, power grids, communication networks, water resources, health delivery systems, and financial networks. We want to thank all the authors for their outstanding work, the participants of InTech'04 for their helpful suggestions, the anonymous reviewers for their thorough analysis and constructive help, and – last but not the least – to Professor Kaoru Hirota for his kind suggestion to host this issue and to the entire staff of the journal for their tireless work.

Converting Constraint Handling Rules to Equivalent Transformation Rules

We present a way to convert constraint handling rules (CHRs) to equivalent transformation rules (ETRs) and demonstrate the correctness of the conversion in equivalent transformation (ET) theory. In the ET computation model, computation is regarded as equivalent transformations of a description. A description is transformed successively by ETRs. Extensively used in the domain of first-order terms, the ET computation model has also been applied to knowledge processing in such data domains as RDF, UML, and XML. A CHR is a multiheaded guarded rule that rewrites constraints into simpler ones until they are solved. CHRs and ETRs are similar in syntax but they have completely different theoretical bases for the correctness of their computation. CHRs are based on the logical equivalence of logical formulas, while ETRs are based on the set equivalence of descriptions. We convert CHRs to rules used in the ET model and demonstrate converted rules to be correct ETRs, i.e., they preserve meanings of descriptions. We discuss correspondences and differences between CHRs and ETRs in theories, giving examples of correct ETRs that cannot be represented as CHRs.

Hippocampal lesions impair performance on a conditional delayed matching and non-matching to position task in the rat

The hippocampus is thought to be involved in a range of cognitive processes, from the ability to acquire new memories, to the ability to learn about spatial relationships. Humans and monkeys with damage to the hippocampus are typically impaired on delayed matching to sample tasks, of which the operant delayed matching to position task (DMTP) is a rat analogue. The reported effects of hippocampal damage on DMTP vary, ranging from delay-dependent deficits to no deficit whatsoever. The present study investigates a novel memory task; the conditional delayed matching/non-matching to position task (CDM/NMTP) in the Skinner box. CDM/NMTP uses the presence of specific stimulus cues to signify whether a particular trial is matching or non-matching in nature. Thus, it incorporates both the task contingencies within one session, and supplements the requirement for remembering the side of the lever in the sample phase with attending to the stimulus and remembering the conditional discrimination for the rule. Rats were trained preoperatively and the effects of bilateral excitotoxic lesions of the hippocampus were examined on postoperative retention of the task. Rats with lesions of the hippocampus incurred a significant impairment on the task that was manifest at all delays intervals. Despite a bias towards matching during training, trials of either type were performed with equivalent accuracy and neither rule was affected differentially by the lesion. This task may prove useful in determining the cognitive roles of a range of brain areas.

Equivalences and optimizations in an expressive XSLT subset

XML is the standard data interchange format and XSLT is the W3C proposed standard for transforming and restructuring XML documents. It turns out that XSLT has very powerful query capabilities as well. Hovewer, due to its complex syntax and lack of formal specification, it is not a trivial task to decide whether two XSLT stylesheets yield the same result, even if for an XSLT subset. We isolate such fragment, powerful enough for expressing several interesting queries and for manipulating XML documents and show how to translate them into queries expressed in a properly extended version of TAX, a powerful XML query algebra, for which we provide a collection of equivalence rules. It is then possible to reason about XSLT equivalences, by translating XSLT stylesheets into XTAX expressions and then statically verifying their equivalence, by means of the mentioned equivalence rules.

Equivalence and transformation of extended algebraic operators in fuzzy relational databases

Relational algebra serves as the theoretical basis for database design and queries. This paper extends our efforts on fuzzy relational algebraic operations under a fuzzy relational data model, namely, extended-possibility-based model. With a more general setting of fuzzy relational algebraic operators, some properties of the operators are investigated including equivalent definitions and transformation rules of the operators. These properties are important and desirable for processing queries in an effective and efficient manner.

HORIZONTAL SIMULATING ROTARY TABLE INTELLIGENT SYNCHRONIZATION-DISTURBANCE CONTROLLER

For friction of hyraulic motors, disturbance from load and synchronizing drive of outer gimbal dual hyraulic motors which are three primary factors affected on performance of hydraulic simulating rotary-table, analysis and summarize fuzzy control rules for synchronizing drive of outer gimbal and rules switch on different control models, fuzzy control rules include equat ion rules and principal and subordinate rules; Establish direct adaptive fuzzy controller(DAFC) based on PID control experiences, present synchronization-disturbance fuzzy controller. Since the deficiency of poor ability of self-learning of fuzzy controller, fuzzy neural net(FNN) controllers for multi-input multi-output (MIMO) system are induced to the above two fuzzy controllers to resolve this problems, and used to noliner system is more suitable. Simulation results of FNN controllers show that the proposed approach can achieve high displacement tracking accuracy and dynamic performance when the loads of the simulating rotary-table are changeable or two hydraulic motors' rotate speeds are different greatly.

Pre-trial publicity: Freedom of the press versus fair trial rights in South Africa?

This article focuses on the impact upon the pending and trial criminal process by potentially prejudicial statements, or information of alleged fact, or opinion, published by the printed media, and its constitutional ramifications in both South African law and foreign law. The discussion centres on the conflict between the constitutional guarantee of a free press to report crime news in the written media, and the constitutional criminal procedural rights of an accused person to a fair trial. It investigates the sub judice rule as a mechanism to limit the prejudgement of issues in pending or imminent criminal litigation, which when offended, may constitute contempt of court ex facie curiae. The sub judice rule applied in South African criminal courts is compared to equivalent rules in Australia, United States, England and New Zealand, and the constitutionality of the South African sub judice rule is reconsidered.

Cooperative clustering based on grid and density

Based on the analysis of features of the grid-based clustering method-clustering in quest (CLIQUE) and density-based clustering method-density-based spatial clustering of applications with noise (DBSCAN), a new clustering algorithm named cooperative clustering based on grid and density (CLGRID) is presented. The new algorithm adopts an equivalent rule of regional inquiry and density unit identification. The central region of one class is calculated by the grid-based method and the margin region by a density-based method. By clustering in two phases and using only a small number of seed objects in representative units to expand the cluster, the frequency of region query can be decreased, and consequently the cost of time is reduced. The new algorithm retains positive features of both grid-based and density-based methods and avoids the difficulty of parameter searching. It can discover clusters of arbitrary shape with high efficiency and is not sensitive to noise. The application of CLGRID on test data sets demonstrates its validity and higher efficiency, which contrast with traditional DBSCAN with R* tree.

Pre-trial publicity: Freedom of the press versus fair trial rights in South Africa?

This article focuses on the impact upon the pending and trial criminal process by potentially prejudicial statements, or information of alleged fact, or opinion, published by the printed media, and its constitutional ramifications in both South African law and foreign law. The discussion centres on the conflict between the constitutional guarantee of a free press to report crime news in the written media, and the constitutional criminal procedural rights of an accused person to a fair trial. It investigates the sub judice rule as a mechanism to limit the prejudgement of issues in pending or imminent criminal litigation, which when offended, may constitute contempt of court ex facie curiae. The sub judice rule applied in South African criminal courts is compared to equivalent rules in Australia, United States, England and New Zealand, and the constitutionality of the South African sub judice rule is reconsidered.

Evolution of body size in food webs: does the energetic equivalence rule hold?

The energetic equivalence rule (EER), which is derived from empirical observations linking population density and body size and from the allometric law linking metabolism and body size, predicts that the amount of energy used by the various species should be independent of body size. Here, we examine this hypothesis using a model that allows entire food webs to emerge from coevolution of interacting species. Body size influences both individual metabolism and interactions among species in the model. Overall, population density does decrease with body size roughly following a power law whose exponent is variable. We discuss this variability in the light of empirical data sets. The emerging relationship between the flux of resources exploited by the various species and their body size follows a decreasing power law, thus contradicting the EER. Our model emphasizes the importance of considering the influence of body size on species interactions in attempting to explain large-scale patterns related to body size.