Longer Word Lengths Research Articles

Predicting second language listening functor comprehension probability with usage-based and embodiment approaches

Aims and Objectives: Embodiment is a major paradigm of first language (L1) research but has not yet been widely adopted in second language (L2) research. The main objective of this research was to find evidence for the effects of sensorimotor embodiment on L2 listening functor comprehension rates. Research Hypothesis: Frequency, word length, and Minkowski3 sensorimotor norms are significantly predictive of functor comprehension probability in an L2 listening task. Methodology: 129 Japanese participants were administered a paused transcription test that contained twelve target phrases. Data and analysis: Transcription of functors was the dependent variable. The independent variables were frequency, word length, and Minkowski3 sensorimotor ratings. These variables were analyzed with logit mixed-effects regressions. Findings/conclusions: Greater frequency, longer word length, and higher Minkowski3 ratings were found to facilitate comprehension and significantly increase the probability that a functor was transcribed. Frequency rates derived from spontaneous L1 oration and conversations were found to be significant, whereas frequency derived from written texts was not significant despite being from a much larger corpus. Originality: No L2 study has used Minkowski3 sensorimotor ratings to predict L2 performance. Minkowski3 ratings quantify the relationship between language and the body. Few researchers have yet to incorporate embodiment theories into models of L2 comprehension. Implications: Embodiment theories complement usage-based approaches and should be incorporated into existing L2 theories. Researchers should be aware of textual differences between corpora and choose corpora appropriate for their analyses.

Finite Alphabet Iterative Decoders for LDPC Codes: Optimization, Architecture and Analysis

Low-density parity-check (LDPC) codes are adopted in many applications due to their Shannon-limit approaching error-correcting performance. Nevertheless, belief-propagation (BP) based decoding of these codes suffers from the error-floor problem, i.e., an abrupt change in the slope of the error-rate curve that occurs at very low error rates. Recently, a new type of decoders termed finite alphabet iterative decoders (FAIDs) were introduced. The FAIDs use simple Boolean maps for variable node processing, and can surpass the BP-based decoders in the error floor region with very short word length. We restrict the scope of this paper to regular dv=3 LDPC codes on the BSC channel. This paper develops a low-complexity implementation architecture for the FAIDs by making use of their properties. Particularly, an innovative bit-serial check node unit is designed for the FAIDs, and a small-area variable node unit is proposed by exploiting the symmetry in the Boolean maps. Moreover, an optimized data scheduling scheme is proposed to increase the hardware utilization efficiency. From synthesis results, the proposed FAID implementation needs only 52% area to reach the same throughput as one of the most efficient standard Min-Sum decoders for an example (7807, 7177) LDPC code, while achieving better error-correcting performance in the error-floor region. Compared to an offset Min-Sum decoder with longer word length, the proposed design can achieve higher throughput with 45% area, and still leads to possible performance improvement in the error-floor region.

Resolving Prokaryotic Taxonomy without rRNA: Longer Oligonucleotide Word Lengths Improve Genome and Metagenome Taxonomic Classification

Oligonucleotide signatures, especially tetranucleotide signatures, have been used as method for homology binning by exploiting an organism’s inherent biases towards the use of specific oligonucleotide words. Tetranucleotide signatures have been especially useful in environmental metagenomics samples as many of these samples contain organisms from poorly classified phyla which cannot be easily identified using traditional homology methods, including NCBI BLAST. This study examines oligonucleotide signatures across 1,424 completed genomes from across the tree of life, substantially expanding upon previous work. A comprehensive analysis of mononucleotide through nonanucleotide word lengths suggests that longer word lengths substantially improve the classification of DNA fragments across a range of sizes of relevance to high throughput sequencing. We find that, at present, heptanucleotide signatures represent an optimal balance between prediction accuracy and computational time for resolving taxonomy using both genomic and metagenomic fragments. We directly compare the ability of tetranucleotide and heptanucleotide world lengths (tetranucleotide signatures are the current standard for oligonucleotide word usage analyses) for taxonomic binning of metagenome reads. We present evidence that heptanucleotide word lengths consistently provide more taxonomic resolving power, particularly in distinguishing between closely related organisms that are often present in metagenomic samples. This implies that longer oligonucleotide word lengths should replace tetranucleotide signatures for most analyses. Finally, we show that the application of longer word lengths to metagenomic datasets leads to more accurate taxonomic binning of DNA scaffolds and have the potential to substantially improve taxonomic assignment and assembly of metagenomic data.

Addition Aware Quantization for Low Complexity and High Precision Constant Multiplication

Multiplication by constants can be efficiently realized using shifts, additions, and subtractions. In this work we consider how to select a fixed-point value for a real valued, rational, or floating-point coefficient to obtain a low-complexity realization. It is shown that the process, denoted addition aware quantization, often can determine coefficients that has as low complexity as the rounded value, but with a smaller approximation error by searching among coefficients with a longer wordlength.

Kolmogorov-Chaitin complexity of digital controller implementations

The complexity of linear, fixed-point arithmetic digital controllers is investigated from a Kolmogorov-Chaitin perspective. Based on the idea of Kolmogorov-Chaitin complexity, practical measures of complexity are developed for statespace realizations, parallel and cascade realizations, and for a newly proposed generalized implicit state-space realization. The complexity of solutions to a restricted complexity controller benchmark problem is investigated using this measure. The results show that from a Kolmogorov-Chaitin viewpoint, higher-order controllers with a shorter word-length may have lower complexity and better performance, than lower-order controllers with longer word-length.

Graphical Design Techniques for Fixed-point Multiplication

This is a tutorial paper that examines the problem of performing fixed-point constant integer multiplications using as few adders as possible. The driving application is the design of digital filters, where it is often required that several products of a single multiplicand are produced. Thus two specific problems are examined in detail, i.e., the one-input/one-output case and the one-input/several-output case. The latter is of interest because it can take advantage of redundancy in the different coefficient multipliers. Graphical methods can be used to design multipliers in both cases.For the one-input/one-output case, both optimal and sub-optimal algorithms introduced by the author are shown to be the best methods for the design of these multipliers. The key to the new methods' success is the use of different graph topologies to those available under standard methods. The optimal method uses an exhaustive search and is limited to short wordlengths, so the suboptimal methods must be used for long wordlengths. The design is shown to be analogous to the design of algorithms for exponentiation, which is becoming increasingly important in cryptography.For the one-input/several-output (“multiplier block”) case, again new algorithms designed by the author are shown to be the best. When used for designing digital filters, the multiplier block method is more efficient (uses fewer adders) than any other method that has been examined. It is so successful at reducing the number of adders used for multiplication that the non-multiplier elements begin to dominate the overall filter cost. It also allows previously unpopular filter structures to compete with structures like the lattice wave structure, despite having more coefficients of longer wordlength. The use of multiplier blocks in filter banks is also described.A third case is examined briefly, that of matrix multiplication (several-input/several-output), which is an area of further research.

A method for calculation of the square root using combinatorial logic

If the bit variables involved in the equation A = g2 are constrained in a set of equations, then the bit variables of Q can be solved recursively, and an approximation for Q obtained. The accuracy depends on the number of bits of A used. Implementation can be achieved by a tree of carry-save adders. An associated method for successive iterations is described, and can be used when longer word lengths are needed. Implementation is described and comparisons are presented.

MT-SIM a mixed-level transition fault simulator based on parallel patterns

This paper describes a mixed level, (i.e., switch-level and gate-level) transition fault simulator based on parallel patterns: MT-SIM. The switch-level allows the simulator to treat faults at the transistor level, while the gate-level conserves the simulation speed and the parallel pattern strategy further enhances the simulation speed for more than one order of magnitude. The simulator is built based on a set of operators which translate the switch-level signal propagation into Boolean operations and transform the gate-level logic elements into symbolic logic representations. The experimental results of the simulator show that it can exhibit a linear performance for the logic-level simulation if a longer word length is adopted.

Optical analog to digital converter using optical logic and table look-up

The need for high performance analog to digital (AID) converters, the advantages of optics, and current approaches to AID conversion are reviewed. A novel method, for which a U.S. patent was recently awarded, is proposed that uses comparators, optical logic, and a table look-up to provide optical digital output from an optical analog input. The advantage of the new method is the ability to produce any digital code, optical input! output, and longer word lengths at high speed. Implementations of the optical logic are proposed that use 1-D spatial light modulator devices under development, including self-electro-optic effect devices (SEEDs), double heterostructure optoelectronic switch (DOES) devices, and spatial light rebroadcasters (SLRs). Optical AID converters could make digital multiplication by analog convolution competitive with electronic systems.

The Gaver-Stehfest algorithm for approximate inversion of Laplace transforms

An approximate technique for the inversion of Laplace transforms is represented and some simple applications are given. The limitations of the method were explored and it is clear that functions which have oscillatory inverses present difficulty for the method. Better approximations result from the use of computers with longer word lengths and there is considerable improvement when an averaging algorithm is employed. Eight-bit microcomputers are generally sufficiently accurate for nonoscillatory time functions but transforms for lightly damped sinusoids and Bessel functions require large main-frame computers with relatively long word length.

Digital filters using round‐off noise control in frequency domain

AbstractThis paper proposes and discusses the noise feedback rounding using an integral‐coefficient digital filter in order to reduce round‐off noise caused by fixed point arithmetic. The following conventions are used; ΓX(z) and ΔX(z) denote the integer and fractional part of a sampled signal X(z), respectively; X(z) is abbreviated as X; N denotes a noise caused by rounding × to Γ (X + R) (R = z‐1 GΔ (X + R)); and the round‐off noise HN under ΔG = 0 at an output is given by HN = K≥, K = ‐H (1 ‐ z‐1 ΓG), N = Δ (1 ‐ z‐1 ΓG)‐1 X where H is the transfer function from a rounding point to the output point. Since N is ordinarily nearly at random, the power of HN can be controlled by determining G for the zeroes of (1 ‐ z‐1 ΓG) to be in the vicinity of the poles of H. In addition, the maximum value Po of the power HN is in the range of 2−2 μ (K) ≤ P0 < μ (K) and therefore μ(K) can be used as an estimator for the worst design value where μ(K) is the maximum value of K(z) K(z‐1) on a unit circle. Both multipliers and combinatorial digital filters described in this paper are simpler in construction and more economical than the ordinary rounding using longer word length or the random rounding.

Children's reproductions: Effects of syntactic emphasis, length, and delay interval

Children were asked to retell stories in which the focus of the semantic structure was either on nouns, on verbs, or on prepositions, or had no special emphasis. Also, in order to investigate whether the limited memory capacity of young children causes them to adjust their response strategies, the length of the stories and the recall interval were varied. Reproductions of the preposition-emphasis stories retained the least semantic content and, moreover, the preposition-emphasis delay-testing procedure resulted in the greatest number of refusals to retell the stories. Contrary to previous findings, however, prepositions were not differentially eliminated in the children's response protocols. In fact, there was a remarkably close correspondence between the reproductions and the original stories in the relative distribution of nouns, verbs, and prepositions. Memory was poorest for the middle segments, and longer word length and the delay-testing procedure both produced greater changes in the meaning, composition, and structure of the stories.

Word length and exposure time effects on the recognition of bilaterally presented words

Word length (two, three, four, and five letters) and exposure time (25, 50, and 100 msec) effects on visual half-field recognition performances were studied in a bilateral word presentation paradigm. Significant right-field recognition superiority (RFRS) obtained for all length-exposure time conditions except that for two-letter words exposed for 100 msec. RFRS was significantly greater for each of the two longer word lengths than for the two shorter lengths and for the 25-msec exposures than for the 50- or 100-msec exposures. The magnitude of RFRS was substantially correlated with a “perceptual difficulty” measure (the ratio of the number of milliseconds available for viewing to the number of letters to be viewed). Results were seen as compatible with a hemispheric asymmetry hypothesis and a differential half-fields masking susceptibility mechanism.

Thinking of a word under different retrieval constraints

Subjects were given, as stimuli, either letters or bigrams and asked to think of a word beginning with those stimuli. Words emitted were to be 3, 4, or 5 letters in length. Each of the six groups contained 100 Ss. Subjects were given 60 sec per stimulus to produce a word. Response measures were the number of words emitted, latency of response, and language frequency of emitted words. It was found that responses were fewer, latencies were longer, and word frequencies were lower for bigram than for letter stimuli, and for longer vs. shorter word lengths. It was pointed out that the effective pool of acceptable words is smaller for bigram than for letter stimuli and is probably smaller for longer than for shorter words. The findings with all response measures were interpreted leager terms of a greater difficulty in thinking of words as pool size is reduced.

The growth of a commercial programming language

Publisher Summary This chapter discusses the growth of a commercial programming language SEAL (Standard Electronic Accounting Language), which is designed for use initially with the Stantec Data Processing System. In general, SEAL is a one or two address language, in that one or two operands may be specified in each command, that is, in each line of coding. The manner in which the lengths of numeric fields are given on Data Descriptions ensures that they may be transferred to another machine of different word length, if the new machine has a longer word length the object program will be more efficient, if shorter then it will be less efficient. The rules of SEAL merely ensure that no packing of operands, several to a word, takes place in machines where this packing would be uneconomic. The users of data processing equipment might be induced to consider their requirements for a programming language in the light of current developments in business languages. The current fashion, of which SEAL is an example, is for English language programming.