String Length Research Articles

Consistent truncation and de Sitter space from gravitational instantons

We construct a four-dimensional consistent truncation to the bosonic part of the universal sector of Calabi-Yau IIA compactification (i.e. the gravity multiplet, one vectormultiplet, and one hypermultiplet) in the presence of background flux and fermionic condensates generated by gravitational instantons. The condensates are controlled by the ratio of the characteristic length of the Calabi-Yau to the string length, and can be finetuned to be dominant in a region of large volume and small string coupling. The consistent truncation admits de Sitter solutions supported by the condensates, subject to certain validity conditions that we discuss.

Reconfiguration method of tensegrity units using infinitesimal mechanisms

PurposeThis paper aims to present a reconfiguration strategy for actuated tensegrity structures. The main idea is to use the infinitesimal mechanisms of the structure to generate a path along which the tensegrity can change its shape while maintaining the equilibrium.Design/methodology/approachCombining the force density method with a marching procedure, the solution to the equilibrium problem is given by a set of differential equations. Beginning from an initial stable position, the algorithm calculates a small displacement until a new stable configuration is reached, and recurrently repeats the process during a given interval of time.FindingsBy means of three numerical simulations and their respective experimental example, the efficacy of this algorithm for reconfiguring the well-known three-bar tensegrity prism along different directions is shown. The proposed method shows efficiency only for small changes of string length. Further work should consider the application of this method to more complex tensegrity structures.Originality/valueThe advantage of this reconfiguration method is its simplicity for finding new stable positions for tensegrity structures, and the fact that it doesn’t need the information of the material of the structure for the computations.

Collatz on the Dyadic Rationals in [0.5, 1) with Fractals: How Bit Strings Change Their Length Under 3x + 1

The reduced Collatz map (Syracuse function) can be stated as “for any odd positive integer x, calculate and then divide by 2 until the result is odd.” We calculate the change in bit string length caused by this map. The result arises from a novel reformulation of the Collatz process “for any fraction in [0.5, 1) with a binary representation of finite length, append If the resulting number is smaller than 2/3 then multiply by 3/2 otherwise multiply by 3/4.” The domain is where strings may shrink versus for may grow. If the Collatz map has non-trivial periodic orbits then they will arise from a fractal that has been added to a map that lacks periodic orbits. If there are an infinite number of such orbits then as their length increases, they will make roughly 0.71 visits to the may-shrink domain for each visit to the may-grow domain.

Experimental demonstration of quantum finite automaton

In quantum information science, a major task is to find the quantum models that can outperform their classical counterparts. Automaton is a fundamental computing model that has wide applications in many fields. It has been shown that the quantum version of automaton can solve certain problem using a much smaller state space compared to the classical automaton. Here we report an experimental demonstration of an optical quantum automaton, which is used to solve the promise problems of determining whether the length of an input string can be divided by a prime number P with no remainder or with a remainder of R. Our quantum automaton can solve such problem using a state space with only three orthonormal states, whereas the classical automaton needs no less than P states. Our results demonstrate the quantum benefits of a quantum automaton over its classical counterpart and paves the way for implementing quantum automaton for more complicated and practical applications.

Pythagorean triangles analysis of the conical pendulum based on lengths, forces and times, to obtain equations for the principal physical parameters

An original approach using three appropriate Pythagorean triangles is presented for the detailed mathematical analysis of an ideal conical pendulum. The triangles that are used in this analysis relate specifically to the physical dimensions of the conical pendulum, the magnitudes of the forces acting during the conical pendulum motion and a triangular construction involving the conical pendulum period. It is assumed that known values for the conical pendulum mass, local value for the acceleration due to gravity and the conical pendulum string length are readily available. The following physical parameters can then be calculated directly from accurate experimental measurements of the conical pendulum period only: string tension force, centripetal force (and consequently the centripetal acceleration), orbital radius, orbital speed, apex angle, magnitude of the angular momentum, potential and kinetic energies. The analysis concludes with the very straightforward derivation of a well-known simple trigonometric identity, which serves to support the internal self-consistency of the Pythagorean triangles technique that is presented here.

XWM: a high-speed matching algorithm for large-scale URL rules in wireless surveillance applications

Large-scale high-speed URL matching is a key operation in many network security systems and surveillance applications in Wireless Sensor Networks. Classic string matching algorithms are unsuitable for large-scale URL filtering due to speed or memory consumption. This paper proposes an extend Wu-Manber algorithm (XWM) which takes advantage of the encoding characteristics of the URL greatly to improve the matching performance of the algorithm. It first adopts the pattern string window selection method to optimize Wu-Manber’s hash process, and then combines hash tables and associative containers to optimize the string comparison process. The experimental results on actual 10 million patterns show that XWM can achieve speeds that are twice as fast as traditional algorithms, especially when the shortest pattern string length is longer, it is more advantageous.

Applying Discriminant and Cluster Analyses to Separate Allergenic from Non-allergenic Proteins

AbstractAs a result of increased healthcare requirements and the introduction of genetically modified foods, the problem of allergies is becoming a growing health problem. The concept of allergies has prompted the use of new methods such as genomics and proteomics to uncover the nature of allergies. In the present study, a selection of 1400 food proteins was analysed by PLS-DA (Partial Least Square-based Discriminant Analysis) after suitable transformation of structural parameters into uniform vectors. Then, the resulting strings of different length were converted into vectors with equal length by Auto and Cross-Covariance (ACC) analysis. Hierarchical and non-hierarchical (K-means) Cluster Analysis (CA) was also performed in order to reach a certain level of separation within a small training set of plant proteins (16 allergenic and 16 non-allergenic) using a new three-dimensional descriptor based on surface protein properties in combination with amino acid hydrophobicity scales. The novelty of the approach in protein differentiation into allergenic and non-allergenic classes is described in the article.The general goal of the present study was to show the effectiveness of a traditional chemometric method for classification (PLS–DA) and the options of Cluster Analysis (CA) to separate by multivariate statistical methods allergenic from non-allergenic proteins.

String correction using the Damerau-Levenshtein distance

BackgroundIn the string correction problem, we are to transform one string into another using a set of prescribed edit operations. In string correction using the Damerau-Levenshtein (DL) distance, the permissible edit operations are: substitution, insertion, deletion and transposition. Several algorithms for string correction using the DL distance have been proposed. The fastest and most space efficient of these algorithms is due to Lowrance and Wagner. It computes the DL distance between strings of length m and n, respectively, in O(mn) time and O(mn) space. In this paper, we focus on the development of algorithms whose asymptotic space complexity is less and whose actual runtime and energy consumption are less than those of the algorithm of Lowrance and Wagner.ResultsWe develop space- and cache-efficient algorithms to compute the Damerau-Levenshtein (DL) distance between two strings as well as to find a sequence of edit operations of length equal to the DL distance. Our algorithms require O(s min{m,n}+m+n) space, where s is the size of the alphabet and m and n are, respectively, the lengths of the two strings. Previously known algorithms require O(mn) space. The space- and cache-efficient algorithms of this paper are demonstrated, experimentally, to be superior to earlier algorithms for the DL distance problem on time, space, and enery metrics using three different computational platforms.ConclusionOur benchmarking shows that, our algorithms are able to handle much larger sequences than earlier algorithms due to the reduction in space requirements. On a single core, we are able to compute the DL distance and an optimal edit sequence faster than known algorithms by as much as 73.1% and 63.5%, respectively. Further, we reduce energy consumption by as much as 68.5%. Multicore versions of our algorithms achieve a speedup of 23.2 on 24 cores.

Computational completeness of simple semi-conditional insertion–deletion systems of degree (2,1)

Insertion–deletion (or ins–del for short) systems are simple models of bio-inspired computing. They are well studied in formal language theory, especially regarding their computational completeness. This concerns the question if all recursively enumerable languages can be generated. This ultimately addresses the question if one can build general-purpose computers rooted in this formalism. The descriptional complexity of an ins–del system is typically measured by its size, a 6-dimensional tuple of non-negative integers $$(e,e',e'';d,d',d'')$$ where e is the maximum length of the insertion string, $$e'$$ (and $$e''$$ ) is the maximum length of the left (and right) context used for insertion; the last three parameters $$d,d',d''$$ are similarly understood for deletion rules. Computational completeness for ins–del systems can even be achieved with rule size (1, 1, 1; 1, 1, 1) but with no rule size strictly smaller than this. This fact has motivated to study ins–del systems in combination with regulation mechanisms. In this context, the six-tuple explained above is called the ID size of a system. Several regulations like graph-control, matrix and semi-conditional have been imposed on ins–del systems. Typically, the computational completeness results are obtained as trade-offs, reducing the ID size, say, to (1, 1, 0; 1, 1, 0) at the expense of increasing other measures of descriptional complexity. In this paper, we study simple semi-conditional ins–del systems, where an ins–del rule can be applied only in the presence or absence of substrings of the derivation string. This brings along two further natural parameters to measure descriptional complexity, namely, the maximum permitting string length p and the maximum forbidden string length f, usually summarized as the degree $$d=(p,f)$$ . We show that simple semi-conditional ins–del systems of degree (2, 1) and with ID sizes $$(1+e,e',e'';1+d,d',d'')$$ are computationally complete for any $$e,e',e'',d,d',d''\in \{0,1\}$$ , with $$e+e'+e''=1$$ and $$d+d'+d''=1$$ . The obtained results complement and improve on the existing results known from the literature. To prove our results, we also show a new normal form for type-0 grammars that appears to be interesting in its own right.

Damage caused by multiple impacts of litchi fruits during vibration harvesting

Mechanical damage caused by fruit-to-fruit impact is a major challenge for mechanical harvesting of litchi (Litchi chinensis Sonn) fruits. Guiwei litchi fruits were used to study the impact behavior and damage degree due to multiple fruit-to-fruit impacts. The effect of impact times and impact energy absorbed by fruits on fruits damage degree were studied by using a pendulum device. The damage degree of fruits was determined with the modulus of elasticity of fruits. A comb-shaped shaker was used for mechanical detaching tests while the detaching time, impact times and impact energy absorbed of litchi fruits during vibration process at three frequencies of 18 Hz, 25 Hz and 32 Hz were investigated based on a high-speed camera. The results of the pendulum tests showed that the damage degree of litchi fruits increased with the increase of the string length from 0.1 m to 0.35 m at all impact times and most of the damage was caused before 10 times of impacts. Furthermore, the damage degree increased according to a power function (R2 = 0.9433) with the total impact energy absorbed of all impacts, which can be used to estimate the damage degree of a fruit after multiple impacts. The mechanical detaching tests showed that 90% fruits were detached in 1.2 s, 0.9 s and 0.5 s at 18 Hz, 25 Hz and 32 Hz respectively and the average impact times decreased from 13.1 times to 6.6 times with the increase of frequency. The calculation results showed that a vibration frequency of 32 Hz induced the lowest average estimated damage degree, which was 5.69%. Therefore, harvesting litchi fruits mechanically at high rate and low damage might be feasible with a proper shaking frequency.

Superionic UO2: A model anharmonic crystalline material.

Crystalline materials at elevated temperatures and pressures can exhibit properties more reminiscent of simple liquids than ideal crystalline materials. Superionic crystalline materials having a liquidlike conductivity σ are particularly interesting for battery, fuel cell, and other energy applications, and we study UO2 as a prototypical superionic material since this material is widely studied given its commercial importance as reactor fuel. Using molecular dynamics, we first investigate basic thermodynamic and structural properties. We then quantify structural relaxation, dynamic heterogeneity, and average ion mobility. We find that the non-Arrhenius diffusion and structural relaxation time of this prototypical superionic material can be described in terms of a generalized activated transport model ("string model") in which the activation energy varies with the average string length. Our transport data can also be described equally well by an Adam-Gibbs model in which the excess entropy density of the crystalline material is estimated from specific heat and thermal expansion data, consistent with the average scale of stringlike collective motion scaling inversely with the excess entropy of the crystal. Strong differences in the temperature dependence of the interfacial mobility from nonionic materials are observed, and we suggest that this difference is due to the relatively high cohesive interaction of ionic materials. In summary, the study of superionic UO2 provides insight into the role of cooperative motion in enhancing ion mobility in ionic materials and offers design principles for the development of new superionic materials for use in diverse energy applications.

QUANTITATIVE DIAGNOSTICS METHODS FOR ASPHALT-RESIN-PARAFFIN DEPOSITS IN WELLS AND OIL PIPELINES

Background The formation of asphalt-resin-paraffin deposits in oil-producing wells and oil collectors depends largely on the temperature and pressure conditions for transporting the gas-liquid mixture; therefore, monitoring the temperature and pressure at oil producing facilities along the entire length of the facilities becomes relevant. The appearance of organic deposits in the well leads to a change in the speed of movement of the well production, retains its thermal energy, increases the pressure in the pipes. The equilibrium in the «reservoir - well - pump» system changes due to the increase in pressure at the discharge of the submersible electric centrifugal pump. Temperature sensors, installed evenly along the length of the lifting pipe string, provide important information on the temperature distribution in the pipe string without deposits and with deposits. Thermometry during the well operation will show the effect of fluctuations in the dynamic level of the fluid on the formation of sediments, will increase the informational content of measures for the inhibition and removal of sediments from wells. Aims and Objectives: to justify different methods of using pressure and temperature sensors in wells and oil gathering pipelines for evaluating their internal state; show the possibility of thermometry on a stationary basis for the implementation of a quantitative diagnosis of deposits in the tubing string of an oil producing well. Methods The known dependences of the state of the gas-liquid mixture on the thermobaric conditions in the tubing string of the well pipes and the continuity equation of the pipeline products are used. Results A method has been developed to monitor the formation of asphalt-resin-paraffin deposits in a tubing string according to temperature sensors, which are uniformly distributed along the length of the tubing on a stationary basis.

Deterministic Computing Techniques for Perfect Density Classification

The aim of this paper is to solve the density classification task (DCT), an extensively studied classical problem, using one-dimensional nonuniform Cellular Automata (CA) rules. A perfect solution of DCT requires searching for CA rules for binary strings of all possible lengths. But the generic problem is still open though the solution exists only for a specific fixed length CA. This paper provides two fundamental ideas to solve this problem in a better way. The first technique solves this problem using deterministic Turing machines which ultimately leads to generation of different CA rules under periodic boundary conditions. In the second technique, the existence of DCT solution by analyzing the state transition diagrams (STDs) of number conserving CA rules is investigated. The possibility of finding the exact solutions of DCT using Turing machine, STD and number conservation property of CA rules can be viewed as an improvement over the approximate solutions obtained by evolutionary techniques.

(Invited) Elucidating Ion Transport Mechanisms in Polymerized Ionic Liquids

Poor ionic conductivity typically hinders the utilization of ion containing polymers from functioning as a single ion conductor for energy storage or conversion applications. A provocative sub class of these materials are polymerized ionic liquids (polyILs) which have the potential to combine the desirable ion transport of an ionic liquid with the favorable mechanical properties of a polymer. However, the room temperature conductivity of polyILs is usually 2 or 3 orders of magnitude lower than that of low molecular weight ionic liquids, yet a decoupling of conductivity and structural dynamics in polyILs demonstrates the opposite at the normalized glass transition temperature (T g/T). This seemingly conflicting observation can be reconciled by the fact that polyILs have higher T g and lower dielectric permittivity at the same T g/T than their molecular counterparts. Moreover, ionic conductivity of polyILs is found to be significantly slower than ion diffusion. Inverse Haven ratio shows a strong temperature dependence: saturating at 0.2 at higher temperature and decreasing at lower T. Pronounced reduction in conductivity is attributed to the cross correlation between the mobile ions since the ion pair diffusion is infeasible in polyILs. This speculation remains unverified. We have recently undertaken atomistic molecular dynamics (MD) simulations to elucidate transport mechanism in polyILs and demonstrate the dynamical heterogeneity and cooperative motion of ion transport in polyILs establishing for the first time quantitative evidence of mobile ion hopping. The hopping of anions is found to be dominantly interchain in nature and is generally facilitated by five associating cations from two different chains. Intrachain hopping was found to be much less significant being mediating with fewer chains. The mobile anions tend to form string-like structures and move cooperatively; and the string length of concerted motion of mobile anions increases with decreasing temperature. Our results reveal the important role of a distance criterion in defining hopping events to correctly elucidate the components of the ion transport mechanism. This molecular-level information will provide an important step in both rationalizing experimental observations and the design of novel ion-containing polymers with superior transport properties.

The Influence of Linguistic Demand on Symptom Expression in Adductor Spasmodic Dysphonia

Adductor Spasmodic Dysphonia (ADSD), a form of focal dystonia, has been defined as a neurogenic, task-specific disorder characterized by abrupt spasms of intrinsic laryngeal muscles that result in phonatory breaks. Voice breaks are typically isolated to propositional speech, and reported to increase in severity as speaking demand or complexity increases. Research to date has focused on variations in phonologic contexts and their influence on voice breaks. The influences of variables at lexical and syntactic levels of analysis have been less well-researched and yet may provide insight into observed variability of symptom manifestation in this rare voice disorder. This study investigated frequency of voice breaks over 20 standard sentences in 38 individuals with ADSD according to linguistic complexity measures including lexical density and a four-level lexical frequency and type paradigm. Two research questions about linguistic influences and ADSD symptom manifestation were posed: (1) does the frequency of voice breaks vary according to the lexical density of a string? and (2) does the frequency of voice breaks vary according to a measure of lexical frequency/type? Results revealed a nonsignificant relationship between string length and voice break frequency, whereas a significant relationship was found between lexical density and voice break frequency (P = 0.029, r = 0.488). Lexical analysis results revealed a significant relationship between lexical frequency and voice breaks, with words within technical/academic classes relating to the highest rates of voice break across 38 subjects with ADSD. Results from this secondary analysis provide support for the hypothesis that variation in linguistic demand may modulate symptom expression in SD. Specifically, lexical density and lexical frequency modulated the frequency of symptom expression in classic forms of SD in this purposive sample.

Well-posedness of a class of hyperbolic partial differential equations on the semi-axis

In this article we study a class of hyperbolic partial differential equations of order one on the semi-axis. The so-called port-Hamiltonian systems cover for instance the wave equation and the transport equation, but also networks of the aforementioned equations fit into this framework. Our main results firstly characterize the boundary conditions which turn the corresponding linear operator into the generator of a strongly continuous semigroup. Secondly, we equip the equation with inputs (control) and outputs (observation) at the boundary and prove that this leads to a well-posed boundary control system. We illustrate our results via an example of coupled transport equations on a network, that allows to model transport from and to infinity. Moreover, we study a vibrating string of infinite length with one endpoint. Here, we show that our results allow to treat cases where the physical constants of the string tend to zero at infinity.

Permuted Pattern Matching Algorithms on Multi-Track Strings

A multi-track string is a tuple of strings of the same length. Given the pattern and text of two multi-track strings, the permuted pattern matching problem is to find the occurrence positions of all permutations of the pattern in the text. In this paper, we propose several algorithms for permuted pattern matching. Our first algorithm, which is based on the Knuth–Morris–Pratt (KMP) algorithm, has a fast theoretical computing time with O ( m k ) as the preprocessing time and O ( n k log σ ) as the matching time, where n, m, k, σ , and occ denote the length of the text, the length of the pattern, the number of strings in the multi-track, the alphabet size, and the number of occurrences of the pattern, respectively. We then improve the KMP-based algorithm by using an automaton, which has a better experimental running time. The next proposed algorithms are based on the Boyer–Moore algorithm and the Horspool algorithm that try to perform pattern matching. These algorithms are the fastest experimental algorithms. Furthermore, we propose an extension of the AC-automaton algorithm that can solve dictionary matching on multi-tracks, which is a task to find multiple multi-track patterns in a multi-track text. Finally, we propose filtering algorithms that can perform permuted pattern matching quickly in practice.

Bayesian prediction of rotational torque to operate horizontal drilling

Horizontal directional drilling is usually used in drilling engineering. In a variety of conditions, it is necessary to predict the torque required for performing the drilling operation. Nevertheless, there is presently not a convenient method available to accomplish this task. In order to overcome this difficulty, the current work aims at predicting the required rotational torque (RT) to operate horizontal directional drilling on the 7 effective parameters including the length of drill string in the borehole (L), axial force on the cutter/bit (P), total angular change of the borehole (KL), radius for the ith reaming operation (Di), rotational speed (rotation per minute) of the bit (N), mud flow rate (W), and mud viscosity (V). In this paper, we propose an approach based on the model selection criteria such as various statistical performance indices mean squared error (MSE), variance account for (VAF), root mean squared error (RMSE), squared correlation coefficient (R2), and mean absolute percentage error (MAPE) to select the most appropriate model among a set of 20 candidate ones to estimate RT, given a set of observed data. Once the most appropriate model is selected, a Bayesian framework is employed to develop the predictive distributions of RT, and to update them with new project-specific data that significantly reduce the associated predictive uncertainty. Overall, the results obtained indicate that the proposed RT model possesses a satisfactory predictive performance.

Zero-Day Signature Extraction for High-Volume Attacks

We present a basic tool for zero day attack signature extraction. Given two large sets of messages, $P$ the messages captured in the network at peacetime (i.e., mostly legitimate traffic) and $A$ the messages captured during attack time (i.e., contains many attack messages), we present a tool for extracting a set $S$ of strings that are frequently found in $A$ and not in $P$ , thus allowing the identification of the attack packets. This is an important tool in protecting sites on the Internet from worm attacks and distributed denial of service attacks and may also be useful for other problems, including command and control identification and the DNA-sequences analysis. The main contributions of this paper are the system we developed to extract the required signatures together with the string-heavy hitters problem definition and the algorithm for solving this problem. This algorithm finds popular strings of variable length in a set of messages, using, in a tricky way, the classic heavy-hitter algorithm as a building block. The algorithm runs in linear time requiring one-pass over the input. Our system makes use of this algorithm to extract the desired signatures. Furthermore, we provide an extended algorithm which is able to identify groups of signatures, often found together in the same packets, which further improves the quality of signatures generated by our system. Using our system, a yet unknown attack can be detected and stopped within minutes from attack start time.

Automata Technique for The LCS Problem

In this paper, we introduce two efficient algorithms in practice for computing the length of a longest common subsequence of two strings, using automata technique, in sequential and parallel ways. For two input strings of lengths m and n with m ≤ n, the parallel algorithm uses k processors (k ≤ m) and costs time complexity O(n) in the worst case, where k is an upper estimate of the length of a longest common subsequence of the two strings. These results are based on the Knapsack Shaking approach proposed by P. T. Huy et al. in 2002. Experimental results show that for the alphabet of size 256, our sequential and parallel algorithms are about 65.85 and 3.41m times faster than the standard dynamic programming algorithm proposed by Wagner and Fisher in 1974, respectively.