Pseudo-random Method Research Articles

Cross and local optimal avoidance of RIME algorithm: A segmentation study for COVID-19 X-ray images

Image segmentation is a crucial technique in analyzing X-ray medical images as it aids in uncovering relevant information concealed within a patient's body, a pivotal aspect of the diagnostic process. The effectiveness of computer-aided diagnosis systems largely depends on the accuracy of the image processing methods. In recent years, multi-threshold image segmentation methods have found widespread application in medical image analysis. Despite the effectiveness of some renowned methods for binary threshold segmentation, the field still faces challenges due to the high cost of threshold computation. Metaheuristic algorithms hold the potential to address this issue as they can produce sufficiently reasonable solutions with manageable computational overheads. While some similar methods have been proposed, the imbalance between exploration and exploitation results in instability as the number of thresholds increases. Consequently, these solutions suffer from reduced efficiency in computing thresholds. In this study, a variant of the latest RIME algorithm, termed SLCRIME, is proposed. This paper replaces the pseudo-random method with low-discrepancy Sobol sequences for solution initialization. Additionally, two methods aimed at avoiding local optima and promoting information exchange within the solution set are introduced, further enhancing its capability to search for optimal threshold sets for IS systems. Subsequently, a multi-threshold image segmentation model based on SLCRIME is proposed and applied to segment 6 COVID-19 X-ray images. In the experiments, SLCRIME is compared with 6 peer algorithms, and the results are evaluated using image segmentation accuracy, feature similarity index metrics (FSIM), peak signal-to-noise ratio (PSNR), and structural similarity index metrics (SSIM). The analysis indicates that SLCRIME achieves optimal thresholds at reasonable computational costs and outperforms other algorithms in terms of performance.

DIMASS: A Delaunay-Inspired, Hybrid Approach to a Team of Agents Search Strategy.

This article describes an approach for multiagent search planning for a team of agents. A team of UAVs tasked to conduct a forest fire search was selected as the use case, although solutions are applicable to other domains. Fixed-path (e.g., parallel track) methods for multiagent search can produce predictable and structured paths, with the main limitation being poor management of agents’ resources and limited adaptability (i.e., based on predefined geometric paths, e.g., parallel track, expanding square, etc.). On the other hand, pseudorandom methods allow agents to generate well-separated paths; but methods can be computationally expensive and can result in a lack of coordination of agents’ activities. We present a hybrid solution that exploits the complementary strengths of fixed-pattern and pseudorandom methods, i.e., an approach that is resource-efficient, predictable, adaptable, and scalable. Our approach evolved from the Delaunay triangulation of systematically selected waypoints to allocate agents to explore a specific region while optimizing a given set of mission constraints. We implement our approach in a simulation environment, comparing the performance of the proposed algorithm with fixed-path and pseudorandom baselines. Results proved agents’ resource utilization, predictability, scalability, and adaptability of the developed path. We also demonstrate the proposed algorithm’s application on real UAVs.

Application of Pseudo-random electrical exploration method in mineral exploration: a case study of skarn-type ore body

Skarn-type ore body containing rich mineral resources, which is a type of deposit with important industrial significance and a wide distribution, is formed by metasomatism of mineral gas-bearing hydrothermal fluids on or near the contact zone between intermediate-acid-medium-basic intrusive rocks and carbonate rocks. It is hard to obtain stable data by using conventional electrical prospecting method because of strong electromagnetic interference. A new pseudo-random method is used to do geological survey work in Northeast China for interference avoidance.

Authentication Key-Exchange Using SMS for Web-Based Platforms

One of the advantages of One Time Password (OTP) is that it’s free from brute force, replay, and shoulder attacks. The codes may originate from different entropy attributes and schemes, such as true random and digital random number generators. Businesses, organizations, and academic institutions have adopted OTP methods for credit card transaction confirmation, recalling forgotten passwords, and validating web portal accounts. This paper proposed a new method in authenticating login credentials using a 3 × 3 matrix and random system key as Two-Factor Authentication (2FA) with an SMS-enabled feature. We used the 6-codes pseudorandom method and a 4-codes validation to allow mobile flexibility and ensure that the user has the required access. The page link and evaluation form are sent to students, IT professionals, and researchers. The results showed respondents are satisfied in terms of functionality, usability, efficiency, and reliability. The developed system could safeguard information, disallow unauthorized access, and impose acceptable data protection measures and minimal system requirements to use the system.

Interpretation of clinical trial results: a committee opinion

This document provides guidance, background, and tips on how to recognize quality trials and focuses on evaluating the validity, importance, and relevance of clinical trial results. This document replaces the document of the same name, last published in 2008 (Fertil Steril® 2008;90:S114-20).

基于伪随机的图像水印算法

基于伪随机的图像水印算法

Multi-criteria optimization of tracked vehicle transmissions

The article is devoted to the problem of computer modeling of rational design of tracked vehicle transmissions with multiple criteria. The problems of finding optimal geometric parameters that satisfy several quality criteria. All the complexity of the layout and the relationship of the parameters make difficult their choice, which is simplified when using approaches of mathematical optimization. Using the famous pseudo-random method LPτ-search with the author's modification made it possible to avoid problems associated with the discreteness and the number of parameters. The main optimization criteria for transmission are minimum center distance, minimum length, minimum mass, and maximum uptime probability. To solve this problem, the problem was formulated and design parameters with constraints were specified, criteria were recorded and a transformation from multicriteria to a single criterion was proposed. The approach is based on analysis of test points that obtained using LPτ-search, and further processing of the information received. The approach of transformation from many criteria to one is proposed by introducing the scale of importance by the designer and assigning the importance of each of the criteria, finding the desired solution for each trial point of relative offset, which is proposed to be used as a unifying criterion. Basic schemes and flowcharts of the algorithm elements are provided. The implementation of the computer model was carried out in the Delphi 7 environment.

Example of rational design of toothed cylindrical gears using pseudo-random method search with multiple criteria

Example of rational design of toothed cylindrical gears using pseudo-random method search with multiple criteria

IMPLEMENTED TO BLUETOOTH CONNECTIONS - FIXED SITUATION

Bluetooth has basically complete requirement for short collection wireless transportations consuming unrestricted manufacturing, technical, medicinal (ISM) 2.4GHz wireless group. Bluetooth works on seventy-nine frequencies in 2.4GHz group by 1MHz transporter arrangement. Individually scheme completes occurrence skipping with 1600 hops/s in Pseudo Random method. Bluetooth relates Frequency Hopping Systems (FHSS) used for intervention modification Frequency Hopping Code Division Multiple Access (FH-CDMA for departure of systems). Additional feature is described in this paper around Bluetooth's radio layer. An actual significant term in setting of Bluetooth has Piconet. A Piconet has gathering of Bluetooth strategies which were corresponding to similar skipping arrangement. Bluetooth connections are implemented by different techniques. These techniques are using to wireless networks.

Predicting Lexical Priming Effects from Distributional Semantic Similarities: A Replication with Extension.

In two experiments, we attempted to replicate and extend findings by Günther et al. (2016) that word similarity measures obtained from distributional semantics models—Latent Semantic Analysis (LSA) and Hyperspace Analog to Language (HAL)—predict lexical priming effects. To this end, we used the pseudo-random method to generate item material while systematically controlling for word similarities introduced by Günther et al. (2016) which was based on LSA cosine similarities (Experiment 1) and HAL cosine similarities (Experiment 2). Extending the original study, we used semantic spaces created from far larger corpora, and implemented several additional methodological improvements. In Experiment 1, we only found a significant effect of HAL cosines on lexical decision times, while we found significant effects for both LSA and HAL cosines in Experiment 2. As further supported by an analysis of the pooled data from both experiments, this indicates that HAL cosines are a better predictor of priming effects than LSA cosines. Taken together, the results replicate the finding that priming effects can be predicted from distributional semantic similarity measures.

A Study on Data Collection Behaviors for a Class of Multi-Hop Wireless Sensor Networks Based on Probability Model

This paper presents an approach to analyze data collection behavior for a class of multi-hop wireless sensor networks (WSNs). Based on probabilistic modeling of the IEEE 802.15.4 MAC protocol, the collected data is estimated using a pseudo-random method of Monte Carlo simulation. Then data collection behavior is modeled as the mean and variation of the probability distribution function curves. Effects of expanding the network size on reception rate were studied by varying the number of nodes in each cluster and hop count. Estimating the amount of data to be collected at the sink node, survivor function and confidence interval have been proposed as metrics for the reliability of data collection.

Novel Phase-Shift Control Technique for Full-Bridge Converter to Reduce Thermal Imbalance Under Light-Load Condition

A new phase-shift control technique for the phase-shift full-bridge converter is proposed to reduce thermal imbalance of power devices. For the full-bridge converter with phase-shift control, zero-voltage switching (ZVS) can be realized. However, the power devices for the leading leg are with higher thermal temperature since the related current to achieve ZVS is much higher than that for the lagging leg. The proposed new phase-shift control technique is to swap the leading leg and the lagging leg with each other by either alternating control, temperature feedback, or pseudo random method. Experimental results derived from a digital signal processor-controlled full-bridge converter are presented for confirmation. It will be shown that thermal balance among power devices can be achieved, thereby confirming the effectiveness of the proposed control technique.

A random forest approach for competing risks based on pseudo‐values

Random forest is a supervised learning method that combines many classification or regression trees for prediction. Here we describe an extension of the random forest method for building event risk prediction models in survival analysis with competing risks. In case of right-censored data, the event status at the prediction horizon is unknown for some subjects. We propose to replace the censored event status by a jackknife pseudo-value, and then to apply an implementation of random forests for uncensored data. Because the pseudo-responses take on values on a continuous scale, the node variance is chosen as split criterion for growing regression trees. In a simulation study, the pseudo split criterion is compared with the Gini split criterion when the latter is applied to the uncensored event status. To investigate the resulting pseudo random forest method for building risk prediction models, we analyze it in a simulation study of predictive performance where we compare it to Cox regression and random survival forest. The method is further illustrated in two real data sets.

Pseudorandomness in Central Force Optimization

Central Force Optimization is a deterministic metaheuristic for an evolutionary algorithm that searches a decision space by flying probes whose trajectories are computed using a gravitational metaphor. CFO benefits substantially from the inclusion of a pseudorandom component (a numerical sequence that is precisely known by specification or calculation but otherwise arbitrary). The essential requirement is that the sequence is uncorrelated with the decision space topology, so that its effect is to pseudorandomly distribute probes throughout the landscape. While this process may appear to be similar to the randomness in an inherently stochastic algorithm, it is in fact fundamentally different because CFO remains deterministic at every step. Three pseudorandom methods are discussed (initial probe distribution, repositioning factor, and decision space adaptation). A sample problem is presented in detail and summary data included for a 23-function benchmark suite. CFO’s performance is quite good compared to other highly developed, state-of-the-art algorithms. Ver. 2 (typographical errors in Step (c) of Fig. 1 and discussion of Fig. 8 corrected; clarification of definition of best R r ; error in Table 2 test function f12 corrected; f12 source code in Appendix 3, page 60 corrected). 3 February 2010 Saint Augustine, Florida

A Novel Coded Excitation Sequence for Ultrasonic Life Location System

A simple and feasible modulation scheme called Continuous Pulse Sequence Width Modulation (CPSWM) is proposed to eliminate the crosstalk among multiple ultrasonic sensors in ultrasonic life location system. To improve the performance of multi-life location system (i.e. sharp autocorrelation and flat cross-correlation characteristics), both the continuous pulse sequence (CPS) width and the duration between two CPSs can be modulated using chaotic, pseudorandom or other methods. The duty cycle of each pulse is fixed to be 50%. To adapt to the intrinsic inertia property of ultrasonic transducers, only central work frequency is used in the CPSWM sequence scheme. The CPSWM scheme only uses digital signal generated by a FPGA processor, no D/A converter is used. The experimental results of ultrasonic multi-life location system consisting of two-channel SensComp 600 series electrostatic sensors with the proposed excitation sequences demonstrate that the ultrasonic multi-life location system with the proposed method can realize multi-life location simultaneously.

Balancing treatment allocations by clinician or center in randomized trials allows unacceptable levels of treatment prediction

Randomized controlled trials are the standard method for comparing treatments because they avoid the selection bias that might arise if clinicians were free to choose which treatment a patient would receive. In practice, allocation of treatments in randomized controlled trials is often not wholly random with various 'pseudo-randomization' methods, such as minimization or balanced blocks, used to ensure good balance between treatments within potentially important prognostic or predictive subgroups. These methods avoid selection bias so long as full concealment of the next treatment allocation is maintained. There is concern, however, that pseudo-random methods may allow clinicians to predict future treatment allocations from previous allocation history, particularly if allocations are balanced by clinician or center. We investigate here to what extent treatment prediction is possible. Using computer simulations of minimization and balanced block randomizations, the success rates of various prediction strategies were investigated for varying numbers of stratification variables, including the patient's clinician. Prediction rates for minimization and balanced block randomization typically exceed 60% when clinician is included as a stratification variable and, under certain circumstances, can exceed 80%. Increasing the number of clinicians and other stratification variables did not greatly reduce the prediction rates. Without clinician as a stratification variable, prediction rates are poor unless few clinicians participate. Prediction rates are unacceptably high when allocations are balanced by clinician or by center. This could easily lead to selection bias that might suggest spurious, or mask real, treatment effects. Unless treatment is blinded, randomization should not be balanced by clinician (or by center), and clinician-center effects should be allowed for instead by retrospectively stratified analyses.

Bidirectional Ray Tracing for the Integration of Illumination by the Quasi-Monte Carlo Method

Algorithms used to generate physically accurate images are usually based on the Monte Carlo methods for the forward and backward ray tracing. These methods are used to numerically solve the light energy transport equation (the rendering equation). Stochastic methods are used because the integration is performed in a high-dimensional space, and the convergence rate of the Monte Carlo methods is independent of the dimension. Nevertheless, modern studies are focused on quasi-random samples that depend on the dimension of the integration space and make it possible to achieve, under certain conditions, a high rate of convergence, which is necessary for interactive applications. In this paper, an approach to the development of an algorithm for the bidirectional ray tracing is suggested that reduces the overheads of the quasi-Monte Carlo integration caused by the high effective dimension and discontinuity of the integrand in the rendering equation. The pseudorandom and quasi-random integration methods are compared using the rendering equations that have analytical solutions.

Digital image watermarking based on discrete wavelet transform

This paper aims at digital watermark which is a new popular research topic recently, presents some methods to embed digital watermark based on modifying frequency coefficients in discrete wavelet transform (DWT) domain. First, the present progress of digital watermark is briefly introduced; after that, starting from Pitas's method and discarding his pseudo random number method, the authors use a digital image scrambling technology as preprocessing for digital watermarking. Then the authors discuss how to embed a l-bit digital image as watermark in frequency domain. Finally another digital watermarking method is given in which 3-D DWT is used to transform a given digital image. Based on the experimental results, it is shown that the proposed methods are robust to a large extent.

Quasi-random maximum simulated likelihood estimation of the mixed multinomial logit model

This paper proposes the use of a quasi-random sequence for the estimation of the mixed multinomial logit model. The mixed multinomial structure is a flexible discrete choice formulation which accommodates general patterns of competitiveness as well as heterogeneity across individuals in sensitivity to exogenous variables. The estimation of this model has been achieved in the past using the pseudo-random maximum simulated likelihood method that evaluates the multi-dimensional integrals in the log-likelihood function by computing the integrand at a sequence of pseudo-random points and taking the average of the resulting integrand values. We suggest and implement an alternative quasi-random maximum simulated likelihood method which uses cleverly crafted non-random but more uniformly distributed sequences in place of the pseudo-random points in the estimation of the mixed logit model. Numerical experiments, in the context of intercity travel mode choice, indicate that the quasi-random method provides considerably better accuracy with much fewer draws and computational time than does the pseudo-random method. This result has the potential to dramatically influence the use of the mixed logit model in practice; specifically, given the flexibility of the mixed logit model, the use of the quasi-random estimation method should facilitate the application of behaviorally rich structures in discrete choice modeling.

Accuracy estimation for quasi-Monte Carlo simulations

The conventional Monte Carlo approach to integration and simulation is a useful alternative to analytic or quadrature methods. It has been recognized through theory and practice that a variety of uniformly distributed sequences provide more accurate results than a purely pseudorandom sequence. The improvement in accuracy depends on the number of dimensions and the discrepancy of the sequence, which are known, and the variation of the function, which is often not known. Unlike pseudorandom methods, the accuracy of a quasirandom simulation cannot be estimated using the sample variance of the evaluations or by bootstrapping. The improvement in time-to-accuracy using quasirandom methods can be as large as several orders of magnitude, so even an empirical accuracy estimator is worth pursuing. In this paper, we discuss several methods for quasirandom empirical accuracy estimation and evaluate a modified empirical technique that appears to be useful.