Simplified Variants Research Articles

Visualization of volume of tissue activated modeling in a clinical planning system for deep brain stimulation.

Pathway activating models try to describe stimulation spread in deep brain stimulation (DBS). Volume of tissue activated (VTA) models are simplified model variants allowing faster and easier computation. Our study aimed to investigate, how VTA visualization can be integrated into a clinical workflow applying directional electrodes using a standard clinical DBS planning system. Twelve patients underwent DBS, using directional electrodes for bilateral subthalamic nucleus (STN) stimulation in Parkinson's disease. Preoperative 3T magnetic resonance imaging was used for automatic visualization of the STN outline, as well as for fiber tractography. Intraoperative computed tomography was used for automatic lead detection. The Guide XT software, closely integrated into the DBS planning software environment, was used for VTA calculation and visualization. VTA visualization was possible in all cases. The percentage of VTA covering the STN volume ranged from 25% to 100% (mean: 60±25%) on the left side and from 0% to 98% (51±30%) on the right side. The mean coordinate of all VTA centers was: 12.6±1.2 mm lateral, 2.1±1.2 mm posterior, and 2.3±1.4 mm inferior in relation to the midcommissural point. Stimulation effects can be compared to the VTA visualization in relation to surrounding structures, potentially facilitating programming, which might be especially beneficial in case of suboptimal lead placement. VTA visualization in a clinical planning system allows an intuitive adjustment of the stimulation parameters, supports programming, and enhances understanding of effects and side effects of DBS.

On a Continuum Model for Avalanche Flow and Its Simplified Variants

Mathematical models of different degrees of complexity, describing the motion of a snow avalanche along a path with given center line and spatially varying width, are formulated and compared. The most complete model integrates the balance equations for mass and momentum over the cross-section and achieves closure through an entrainment function based on shock theory and a modified Voellmy bed friction law where the Coulombic contribution to the bed shear stress is limited by the shear strength of the snow cover. A simplified model results from integrating these balance equations over the (time-dependent) length of the flow and postulating weak similarity of the evolving avalanche shape. On path segments of constant inclination, it can be solved for the flow depth and speed of the front in closed form in terms of the imaginary error function. Finally, the very simplest model assumes constant flow height and length. On an inclined plane, the evolution of flow depth and velocity predicted by the simplified model are close to those from the full model without entrainment and with corresponding parameters, but the simplest model with constant flow depth predicts much higher velocity values. If the friction coefficient is varied in the full model with entrainment, there can be non-monotonous behavior due to the non-linear interplay between entrainment and the limitation on the Coulomb friction.

Optimal combining of seismic data with different spectral characteristics

When it comes to sharing overlapping seismic surveys and testing various energy sources, geophysicists have to deal with data having different spectral characteristics. It is very important to note that such data share the same information on the reflectivity of the medium, which is of interest to us. In order to combine such redundant data optimally and estimate the reflectivity of the medium more effectively, this article proposes using multichannel reverse Wiener filtering. To avoid the problems associated with a possible difference in the data acquisition systems of overlapping surveys, it is proposed to reduce the amount of information processed and to combine the final seismic images obtained from each of the independent surveys or from different sources. The theory of the optimal method is presented and the structure of the solution obtained is analyzed. It is shown that the method can be represented as a combination of the optimal frequency-dependent weighted summation of images with the subsequent single-channel inverse Wiener filtering (deconvolution) of the summation result. A theoretical comparison of the optimal method with simplified analogues wherein the first step is a simple unweighted summation without and with elimination of the wavelet phase spectra of images is performed. It is shown that the greater the difference between the spectra of the signal components of images at a given frequency, the greater the advantage of the optimal method of combining them over the simplified variants. The article stresses that since seismic exploration capabilities basically allow only signal parameters to be changed, the greatest effect from the optimal method can be achieved due to maximum mutual displacement (minimum mutual overlap) along the frequency axis of the spectra of the wavelets of combined images. This is theoretically confirmed by the calculation of the spectrum of the optimal complementary signal the addition of which to the existing set to participate in optimally combining ensures maximum efficiency of this procedure. The rationale is given that the optimal procedure should be performed only within the frequency interval where the signal averaged over the number of images prevails over the averaged noise. The method is tested on synthetic data. It is shown that its efficiency monotonously increases with increasing the input signal-to-noise ratio, the number of images involved in processing, and the mutual frequency shift of their spectra, i.e. as the degree of overlap of these spectra decreases. Moreover, the effectiveness of the method is confirmed on a field line from the Dnieper-Donets depression, which was independently worked out with dynamite and vibratory sources. It is shown that the optimal method provides the most regular and resolved reflections across the entire image, which significantly exceeds the results of independent single-channel deconvolutions of the images obtained with both types of sources and of their simplified combination.

Algebraic Attacks Against Several Weak Variants of GVW’13 ABE

Attribute-based encryption (ABE) is an active research area in the public-key cryptography. Among large amount of ABE schemes, the scheme GVW’13 (STOC13) is an well-known candidate for realizing ABE via lattice mechanism, whose security relies on learning with errors (LWE). This ABE scheme has very exquisite structure, and its crucial component lies in using that two-to-one recoding (TOR) algorithm. However, the main shortcoming of GVW’13 is the use of the huge key-size. Therefore, it encourages people to find out some more simplified variants of GVW’13. In this paper, we first propose three variants of GVW’13 for reducing the size of secret key, which would be the feasible strategies to improve GVW’13 with great possibility. Unfortunately, we can still present three related attacks against these three proposals under the same collusion scenario, respectively.

Solving the travelling salesman problem using fuzzy and simplified variants of ant supervised by PSO with local search policy, FAS-PSO-LS, SAS-PSO-LS

Solving the travelling salesman problem using fuzzy and simplified variants of ant supervised by PSO with local search policy, FAS-PSO-LS, SAS-PSO-LS

INFLUENCE OF A TYPE OF CONTROLLING FUNCTIONS OF NON-STATIONARY PROBLEM OF THERMAL CONDUCTING ON THE RESOURCE STRENGTH OF THE PISTON

The analysis of calculation and experimental data of the temperature and thermo-stressed state of the piston in the transient processes of the engine is performed. The control functions are determined in the zone of the first and second porous rings. The results of the temperature state of the piston have been obtained taking into account certain control functions. The obtained results coincide with the experimental data with an error in the admissible mediums. A one-step change in control functions is considered in comparison with the obtained type of control functions. The influence of the type of control functions of the non-stationary heat conduction problem on the temperature and thermo-stressed state of the edge of the combustion chamber of the piston is shown. The simplified variants of control functions are offered on the basis of one-step change of the type of control functions. The estimation of the resource strength of the piston is taken into account taking into account the peculiarities of the change of simplified control functions. A simplified version of control functions is defined, which corresponds to the concept of guaranteed maintenance of the resource of the edge of the combustion chamber of the piston.

Theoretically optimal forms for very long-span bridges under gravity loading.

Long-span bridges have traditionally employed suspension or cable-stayed forms, comprising vertical pylons and networks of cables supporting a bridge deck. However, the optimality of such forms over very long spans appears never to have been rigorously assessed, and the theoretically optimal form for a given span carrying gravity loading has remained unknown. To address this we here describe a new numerical layout optimization procedure capable of intrinsically modelling the self-weight of the constituent structural elements, and use this to identify the form requiring the minimum volume of material for a given span. The bridge forms identified are complex and differ markedly to traditional suspension and cable-stayed bridge forms. Simplified variants incorporating split pylons are also presented. Although these would still be challenging to construct in practice, a benefit is that they are capable of spanning much greater distances for a given volume of material than traditional suspension and cable-stayed forms employing vertical pylons, particularly when very long spans (e.g. over 2 km) are involved.

Considerations for The Selection of Written Chinese Variants In The Process of Translating and Linguistically Validating Clinical Outcome Assessments (COAS)

There are several predominant variants of both written and spoken Chinese. The written variants are Traditional and Simplified Chinese, and well-known spoken variants include Standard Mandarin, Cantonese, and Taiwanese. Understanding the relationship between these written and spoken variants and the appropriate circumstances for usage is vital to successful translation and linguistic validation of COAs targeted for use in populations that speak and write these variants of modern Chinese. Modern spoken Chinese is divided into at least seven major dialectical groups containing over 200 total dialects. Although many of these spoken dialects are not mutually intelligible, historically, there has been a common written system underlying the spoken variants. This common written system officially diverged in 1956 into two variants, Traditional and Simplified Chinese. Confusion frequently arises from the fact that use of these variants is not interchangeable, but dictated largely by national boundaries and political tensions. Traditional Chinese is used predominantly in Hong Kong, Taiwan, Macau, and overseas Chinese-speaking communities. Simplified Chinese is used predominantly in mainland China, Singapore, and Malaysia. Furthermore, formal education is typically given in only one of the written variants, and although the two are related, and most speakers are exposed to both in daily life, they differ enough that knowledge of and literacy in one variant does not perfectly transfer to the other. There are important differences between the Traditional and Simplified variants of written Chinese, as well as geographic and national variation in their use. Additionally, most formal education occurs in only one variant, and there is no clear relationship between spoken variants and their underlying written forms. Together, these factors necessitate careful consideration of the written variant and the subject population requested for translation services and linguistic validation of COAs in locations where modern Chinese is used.

Cube Attacks on the Stream Cipher Grain-v1

The Cube Attack was introduced by Itai Dinur and Adi Shamir. As a known plaintext attack on symmetric primitives, it is efficient to stream cipher, block cipher and hash functions. In this paper, we proposed a new method to find all the cubes U which could produce linear relations, and it is applied to simplified Grain-v1 variants with 60, 65 initialization rounds, from which we can obtain at least 25, 11 key bits respectively. Our results show that the Grain-v1 with reduced initialization rounds can be broken with Cube Attack, and the complexity is significantly lower than exhaustive search.

Vector model of wind for performance analysis of stand-alone wind power systems

A statistical model of speed of horizontal wind in the atmosphere, intended for estimating the efficiency of stand-alone wind power systems treated as nonlinear stochastic dynamic systems, is developed. The model is based on the representation of wind as a two-dimensional Gaussian---Markov random process. The method of calculating model parameters by using observation results of the wind magnitude and direction on the land-based weather station is presented. The model parameters are calculated for several locations in Russia. More precise and simplified variants of the model are proposed. The model adequacy is analyzed by comparing the system's efficiency indexes with their reference values.

The bi-objective quadratic multiple knapsack problem: Model and heuristics

The single objective quadratic multiple knapsack problem (QMKP) is a useful model to formulate a number of practical problems. However, it is not suitable for situations where more than one objective needs to be considered. In this paper, we extend the single objective QMKP to the bi-objective case such that we simultaneously maximize the total profit of the items packed into the knapsacks and the ’makespan’ (the gain of the least profit knapsack). Given the imposing computational challenge, we propose a hybrid two-stage (HTS) algorithm to approximate the Pareto front of the bi-objective QMKP. HTS combines two different and complementary search methods — scalarizing memetic search (first stage) and Pareto local search (second stage). Experimental assessments on a set of 60 problem instances show that HTS dominates a standard multi-objective evolutionary algorithm (NSGA II), and two simplified variants of HTS. We also present a comparison with two state-of-the-art algorithms for the single objective QMKP to assess the quality of the extreme solutions of the approximated Pareto front.

On melting density gap and non-congruence of phase transitions in models of dusty and colloid plasmas

Two simplified variants of a dusty, condensed dispersed phase and colloid plasmas models are considered as a thermodynamically equilibrium combination of classical Coulomb particles: a 2-component electroneutral system of macro- and micro-ions (+Z, – 1) and a 3-component electroneutral mixture of macro-ions and two kinds of micro-ions (+Z, –1, +1). The base for a consideration is a phase diagram of dusty plasma by Hamaguchi et al (1997 Phys. Rev. E 56 4671) for an equilibrium charged system with the Yukawa potential. Parameters of a splitting the one-dimensional melting boundaries of the Hamaguchi diagram (i.e. hypothetical melting density gap between separate freezing liquid line (liquidus) and melting crystal line (solidus)) are discussed. Estimation of a density gap value is made. Additional splitting of all phase boundaries in the three-component model because of so-called non-congruency of all phase transitions in this model is discussed also.

Low-Complexity Implementation of the Improved Multiband-Structured Subband Adaptive Filter Algorithm

Previously, we proposed an improved multiband-structured subband adaptive filter (IMSAF) algorithm to accelerate the convergence rate of the MSAF algorithm. When the projection order and/or the number of subbands is increased, the convergence rate of the IMSAF algorithm improves at the cost of increased complexity. Thus, this paper proposes several approaches to reduce the complexity of the IMSAF algorithm, both in error vector calculation and matrix inversion operation. Specifically, three approaches are developed to efficiently calculate error vector. The first approach gives an approximate filtering, whereas the other two approaches can provide a fast exact filtering with or without update of the weight vector explicitly based on a recursive scheme. The decorrelation property of IMSAF is determined, and two simplified variants are developed to reduce the complexity as by-products, i.e., the simplified IMSAF (SIMSAF) and pseudo IMSAF algorithms. Then, we discuss the problem of solving a linear system of equations. The performance advantages, limitations, and preferable applications of various methods are analyzed and discussed. Computer simulations are conducted in the context of system identification to determine the principle and efficiency of the proposed fast algorithms.

The mean photon energy ĒF at the point of measurement determines the detector-specific radiation quality correction factor kQ,M in 192Ir brachytherapy dosimetry

The application of various radiation detectors for brachytherapy dosimetry has motivated this study of the energy dependence of radiation quality correction factor kQ,M, the quotient of the detector responses under calibration conditions at a 60Co unit and under the given non-reference conditions at the point of measurement, M, occurring in photon brachytherapy. The investigated detectors comprise TLD, radiochromic film, ESR, Si diode, plastic scintillator and diamond crystal detectors as well as ionization chambers of various sizes, whose measured response-energy relationships, taken from the literature, served as input data. Brachytherapy photon fields were Monte-Carlo simulated for an ideal isotropic 192Ir point source, a model spherical 192Ir source with steel encapsulation and a commercial HDR GammaMed Plus source. The radial source distance was varied within cylindrical water phantoms with outer radii ranging from 10 to 30cm and heights from 20 to 60cm. By application of this semiempirical method - originally developed for teletherapy dosimetry - it has been shown that factor kQ,M is closely correlated with a single variable, the fluence-weighted mean photon energy ĒF at the point of measurement. The radial profiles of ĒF obtained with either the commercial 192Ir source or the two simplified source variants show little variation. The observed correlations between parameters kQ,M and ĒF are represented by fitting formulae for all investigated detectors, and further variation of the detector type is foreseen. The herewith established close correlation of radiation quality correction factor kQ,M with local mean photon energy ĒF can be regarded as a simple regularity, facilitating the practical application of correction factor kQ,M for in-phantom dosimetry around 192Ir brachytherapy sources. ĒF values can be assessed by Monte Carlo simulation or measurement. A technique describing the local measurement of ĒF will be published separately.

Sparse Multinomial Logistic Regression via Approximate Message Passing

For the problem of multi-class linear classification and feature selection, we propose approximate message passing approaches to sparse multinomial logistic regression (MLR). First, we propose two algorithms based on the Hybrid Generalized Approximate Message Passing (HyGAMP) framework: one finds the maximum a posteriori (MAP) linear classifier and the other finds an approximation of the test-error-rate minimizing linear classifier. Then we design computationally simplified variants of these two algorithms. Next, we detail methods to tune the hyperparameters of their assumed statistical models using Stein's unbiased risk estimate (SURE) and expectation-maximization (EM), respectively. Finally, using both synthetic and real-world datasets, we demonstrate improved error-rate and runtime performance relative to existing state-of-the-art approaches to sparse MLR.

An integer programming model for protein structure prediction using the 3D-HP side chain model

In spite of the fact that many simplified model variants of protein structure prediction have been widely studied in the past years, few attention has been given to discrete models with side chains, for which there is no specific benchmark. In this paper, we propose an integer programming model for the 3D-HP side chain protein structure prediction problem. The model accounts for the energy resulting from all types of interactions, between pairs of backbone elements, hydrophilic side chains and hydrophobic side chains. Three sets of instances, modified from the literature, were used in the experiments, and the maximum number of non-local hydrophobic contact was found using the ILOG CPLEX optimization package. We offer the optimal solution found for several instances of the benchmark. It is expected that the mathematical model allow further studies of the protein structure prediction with side chains and may, for some cases, provide new optimal values or new bounds that would rekindle the interest to this fascinating problem domain.

Accept & reject statement-based uncertainty models

We develop a framework for modelling and reasoning with uncertainty based on accept and reject statements about gambles. It generalises the frameworks found in the literature based on statements of acceptability, desirability, or favourability and clarifies their relative position. Next to the statement-based formulation, we also provide a translation in terms of preference relations, discuss—as a bridge to existing frameworks—a number of simplified variants, and show the relationship with prevision-based uncertainty models. We furthermore provide an application to modelling symmetry judgements.

An Adaptive Variable Neighborhood Search for a Heterogeneous Fleet Vehicle Routing Problem with Three-Dimensional Loading Constraints

The paper addresses the heterogeneous fleet vehicle routing problem with three-dimensional (3D) loading constraints (3L-HFVRP), a new practical variant of the combined routing and loading problem. In this problem, the loads consist of a set of three-dimensional, rectangular shaped items. The fleet is composed of heterogeneous vehicles with different weight and space capacities. The objective is to serve all customers by selecting a set of vehicles such that the total transportation cost is minimized. The cost consists of the fixed cost of the selected vehicles and their travel cost. In addition, loading sequence related constraints frequently encountered in realistic applications are respected when loading and unloading the items. To solve this challenging problem, we develop an adaptive variable neighborhood search (AVNS) which utilizes an extreme point based first fit heuristic to find a feasible loading pattern for each route. We design two strategies to accelerate the loading and routing processes. The Trie data structure is used to record the loading information of routes already visited and to control the computational effort spent for each route. The Fibonacci heap data structure is used to maintain all of the possible moves and vehicle type assignments, which avoids the duplicated evaluation of some moves and unnecessary loading check of unpromising solutions. The robustness and effectiveness of the proposed algorithm is validated by computational tests performed both on some newly generated 3L-HFVRP instances and well-known benchmark instances from the literature for two simplified VRP variants: the capacitated vehicle routing problem with 3D loading constraints (3L-CVRP) and the pure heterogeneous fleet vehicle routing problem (HFVRP). The numerical experiments show that the proposed AVNS outperforms other algorithms in 3L-CVRP and improves several best known solutions reported in the literature. The results obtained for the pure HFVRP are very close to the best known solutions.

Cryptanalysis of Two GOST Variants with 128-Bit Keys

GOST is a well-known Russian encryption standard. Until 2010, no researcher found a single-key attack on GOST. In 2010, GOST was submitted to ISO 18033 to become a worldwide industrial encryption standard. Since 2011, many attacks on GOST faster than brute force have been found [3, 4, 5, 10, 12]. By default, GOST has 256-bit keys. However, in many applications 128-bit keys are required. The authors should note that GOST is an exceptionally economical cipher in implementation: Even as a 128-bit cipher, GOST requires about four times less gates to implement than AES-128 (see [16]). There are two very natural 128-bit variants of GOST: Either the same 128-bit key is repeated, or it is repeated with inversion of the 32-bit words. Both variants are natural simplified variants fully compliant with the standard which have already been considered as potentially interesting targets for advanced slide attacks [2]. In this article, the authors show that both these variants are insecure. All of their attacks are nearly practical.

Simpler Bounded Suboptimal Search

It is commonly appreciated that solving search problems optimally can take too long. Bounded suboptimal search algorithms trade increased solution cost for reduced solving time. Explicit Estimation Search (EES) is a recent state-of-the-art algorithm specifically designed for bounded suboptimal search. Although it tends to expand fewer nodes than alternative algorithms, such as weighted A* (WA*), its per-node expansion overhead is higher, causing it to sometimes take longer. In this paper, we present simplified variants of EES (SEES) and an earlier algorithm, A*epsilon (SA*epsilon), that use different implementations of the same motivating ideas to significantly reduce search overhead and implementation complexity. In an empirical evaluation, we find that SEES, like EES, outperforms classic bounded suboptimal search algorithms, such as WA*, on domains tested where distance-to-go estimates enable better search guidance. We also confirm that, while SEES and SA*epsilon expand roughly the same number of nodes as their progenitors, they solve problems significantly faster and are much easier to implement. This work widens the applicability of state-of the-art bounded suboptimal search by making it easier to deploy.