Simple Algorithm Research Articles

New two-microphone simplified sub-band forward algorithm based on separated variable step-sizes for acoustic noise reduction

This paper presents an extended two-microphone adaptive filtering algorithm implemented on the sub-band simplified forward technique using new separated variable step-sizes parameters (denoted SSF-SVS: Simplified Sub-band Forward Separated Variable Step-sizes). This algorithm is proposed to reduce the acoustic noise and enhance the quality of estimated speech signal. Firstly, a sub-signal decomposition processing strategy is used to facilitating effective noise reduction with very fast convergence rate using two analysis filter banks. Secondly, a two-microphone simplified forward blind source separation (BSS) structure updated by the normalized least-mean-square algorithm (NLMS) for extracting the estimated speech signal. To guarantee a very fast convergence rate with high level of enhanced speech quality, thirdly we proposed new separated variable step-sizes parameters for controlling the adaptation of sub-band filters. The concept involves suggesting individual variable step-size parameter for each adaptive sub-filter, which are updated independently using the input sub-signal and the estimated output sub-signal. Experimental results confirm significant improvements in terms of convergence rate based on the mean square error criterion (MSE) in diverse acoustical environments. In other hand, the good performance of the proposed SSF-SVS algorithm in terms of speech quality is verified by on output signal-to-noise ratio (Output-SNR). The proposed algorithm compared with six two-microphone adaptive filtering algorithms in term of convergence rate, speech quality and computational complexity.

Efficient function approximation in enriched approximation spaces

Abstract An enriched approximation space is the span of a conventional basis with a few extra functions included, for example to capture known features of the solution to a computational problem. Adding functions to a basis makes it overcomplete and, consequently, the corresponding discretized approximation problem may require solving an ill-conditioned system. Recent research indicates that these systems can still provide highly accurate numerical approximations under reasonable conditions. In this paper we propose an efficient algorithm to compute such approximations. It is based on the AZ algorithm for overcomplete sets and frames, which simplifies in the case of an enriched basis. In addition, analysis of the original AZ algorithm and of the proposed variant gives constructive insights on how to achieve optimal and stable discretizations using enriched bases. We apply the algorithm to examples of enriched approximation spaces in literature, including a few nonstandard approximation problems and an enriched spectral method for a 2D boundary value problem, and show that the simplified AZ algorithm is indeed stable, accurate and efficient.

Skill-Based Matchmaking for Competitive Two-Player Games

Skill-based matchmaking is a crucial component of competitive multiplayer games and it is directly tied to how the players would enjoy the game. We present a simple matchmaking algorithm that aims to achieve a target win rate for all players, making long win/loss streaks less probable. It is based on the estimated skill levels of players. Therefore, we also present a rating estimation for players that does not require any game-specific information and purely relies on game outcomes. Our evaluation shows that our methods are effective in estimating a player's rating, responding to changes in rating, and achieving a desirable win rate that avoids long win/loss streaks in competitive two-player games.

Proposing a new control method for active stabilizer bars using an intelligent self-learning algorithm

This article’s main content is directed toward designing and applying a new control algorithm for automotive stabilizer bars. Previous studies often only used classical control algorithms or simple fuzzy algorithms to control hydraulic anti-roll systems on cars based on safety criteria. In this article, a self-learning algorithm (ANFIS) is established based on inheriting the advantages of previous algorithms. Additionally, this algorithm is modified and improved to increase the convergence of the results after the end of the steering process. Simulations show that when the self-learning solution is applied to active anti-roll bars, the roll angle value and the attenuation of the vertical force at wheels decrease significantly. In complex motion conditions (second case, v3), rollover occurs if the automobile does not have an anti-roll bar. However, roll stability and road holding ability are always ensured when applying the ANFIS algorithm to control active anti-roll bars. According to these findings, the minimum value of the vertical force at the rear wheel can be up to 1384.02 N even when the car is traveling in extremely harsh conditions (second case, v4). In addition, the response speed and convergence of values are always well-controlled when the intelligent self-learning algorithm is applied to the anti-roll control system.

Sudan's rheumatic fever and rheumatic heart disease guidelines: a simplified approach in an endemic country

BackgroundRheumatic heart disease (RHD) is a preventable sequelae of group A beta hemolytic streptococcal infection leading to an immune reaction: acute rheumatic fever (ARF) and progressive heart valve dysfunction. RHD is the leading cause of acquired heart disease in children and young adults in Sudan and many low/middle-income countries. In 2018, the World Health Organization (WHO) issued a resolution for RHD mandating that each country adopt updated guidelines for ARF and RHD management. These current guidelines are mainly directed to primary healthcare workers.MethodsSudan’s Federal Ministry of Health (FMOH) in collaboration with the WHO East Mediterranean Regional Office (EMRO) assembled a committee for updating RHD guidelines. We conducted a systematic literature search from 2000 to 2022 in National Institute of Health Database (PubMed) under the following titles: streptococcal pharyngitis, acute rheumatic fever, rheumatic heart disease, benzathine penicillin. Best available, evidence-based practices for diagnosis and management of ARF/RHD were selected and adapted to Sudan's situation. The guidelines were critically appraised by the committee then endorsed to the FMOH and WHO EMRO Noncommunicable Disease Departments in January 2023. This paper describes the updated guidelines.ResultsSimplified algorithms are provided for diagnosis of bacterial pharyngitis including two clinical criteria: sore throat and the absence of viral symptoms in the target age group. A simplified algorithm for diagnosis and management of ARF is adopted using two levels of diagnosis: suspected case at primary level where penicillin prophylaxis is started and secondary/tertiary care where echocardiography is performed and diagnosis confirmed or excluded. Echocardiography screening is recognized as the standard method for early diagnosis of RHD; however, due to the anticipated limitations, its implementation was not adopted at this time. Streptococcal skin infection is included as a precursor of ARF and a detailed protocol for benzathine penicillin administration is described.ConclusionThe Sudan guidelines for ARF/RHD management were updated. Endorsement of these guidelines to FMOH and WHO EMRO is expected to improve control of RHD in the region.

A Comparison of Myoelectric Control Modes for an Assistive Robotic Virtual Platform

In this paper, we propose a daily living situation where objects in a kitchen can be grasped and stored in specific containers using a virtual robot arm operated by different myoelectric control modes. The main goal of this study is to prove the feasibility of providing virtual environments controlled through surface electromyography that can be used for the future training of people using prosthetics or with upper limb motor impairments. We propose that simple control algorithms can be a more natural and robust way to interact with prostheses and assistive robotics in general than complex multipurpose machine learning approaches. Additionally, we discuss the advantages and disadvantages of adding intelligence to the setup to automatically assist grasping activities. The results show very good performance across all participants who share similar opinions regarding the execution of each of the proposed control modes.

Advancing electromagnetic field modeling in axially anisotropic media with conformal method in 3D cylindrical coordinate systems

A conformal methodology for solving electromagnetic fields in axially anisotropic media in 3D cylindrical coordinate systems is proposed for the investigation of high-power microwave devices filled with such media. This method leverages the material properties of axially anisotropic media and employs the finite integral technique for solution. A simplified conformal algorithm is utilized for the boundaries of the computational region, extending the traditional conformal method for axially anisotropic media in 3D cylindrical coordinates. The proposed methodology is validated through simulations of TM01 and TE01 mode propagation in a circular waveguide filled with the medium. Subsequently, the method is integrated into particle-in-cell simulations, and an X-band relativistic backward wave oscillator filled with an axially anisotropic medium exhibiting azimuthal conductivity is numerically modeled. The results demonstrate that the medium with azimuthal conductivity effectively mitigates asymmetric modes in the relativistic backward wave oscillator, aligning with published literature. This study offers technical insights for research on high-power microwave devices incorporating axially anisotropic media, potentially facilitating the development of innovative microwave devices with enhanced performance characteristics.

Vector-Algebra Algorithms to Draw the Curve of Alignment, the Great Ellipse, the Normal Section, and the Loxodrome

This paper recasts four geodetic curves—the great ellipse, the normal section, the loxodrome, and the curve of alignment—into a parametric form of vector-algebra formula. These formulas allow these curves to be drawn using simple, efficient, and robust algorithms. The curve of alignment, which seems to be quite obscure, ought not to be. Like the great ellipse and the loxodrome, and unlike the normal section, the curve of alignment from point A to point B (both on the same ellipsoid) is the same as the curve of alignment from point B to point A. The algorithm used to draw the curve of alignment is much simpler than any of the others and its shape is quite similar to that of the geodesic, which suggests it would be a practical surrogate when drawing these curves.

Influence of Clinician-Related Factors on Adherence to the American Heart Association Guidelines for Acute Coronary Syndrome among Clinicians at Kenya Ports Authority Clinics in Mombasa, Kenya

Purpose: The aim of the study was to assess influence of clinician-related factors on adherence to the American heart association guidelines for acute coronary syndrome among clinicians at Kenya Ports Authority clinics in Mombasa, Kenya. Methodology: A descriptive cross-sectional study involving quantitative methods of data collection was adopted. An interviewer administered questionnaire was used for data collection. The study was carried out in Kenya Ports Authority clinics in Mombasa, Kenya. The target population was 106 clinicians attending to patients who present with Acute Coronary Syndrome at the KPA clinics in Mombasa. A census method was used to determine the study participants. The sample size was made up of a hundred and six participants. The clinicians who consented to participate in the study were included while those who were on sick off, leave or who recently joined the clinic were excluded. Pretesting of the study tool was done at the Kenya Pipeline Clinic Mombasa. Data analysis was done using Statistical Package for Social Sciences version 25 and presented via tables. Findings: The study results showed that at 95% level of confidence (ρ-value = 0.05%), there was a significant association between gender (ᾳ=0.025), work experience (ᾳ=0.016), job cadre (ᾳ=0.014) and training received (ᾳ=0.022) on adherence to the American Heart Association Guidelines for Acute Coronary Syndrome among clinicians at Kenya Ports Authority clinics in Mombasa, Kenya. The association was insignificant between age (ᾳ=0.178), education level (ᾳ=0.439) and specialization (ᾳ=0.489) on adherence to the AHA guidelines. Unique Contribution to Theory, Practice and Policy: The study recommends that the KPA management should increase the medical budget to ensure availability of adequate resources for ACS patient management. These resources include adequate staffing, medication, equipment, and staff training costs. The clinic management should ensure that medications such as aspirin, morphine and nitroglycerine are readily available and accessible at patients care points. The KPA clinic management to formulate a simple algorithm that outlines the steps to be taken when managing ACS patients. The study recommends that the clinics should assess their equipment reqularly for maintenance controls to ensure efficiency. The study further recommends random assessments and post care audits to assess the adherence to ACS guidelines among clinicians. Training associated with adherence to the AHA guidelines and as such, KPA should continue offering training and education on the latest AHA guidelines for ACS to ensure updated guidelines for practice.

Implementation of IDEAL algorithm based on Delaunay triangular mesh for 2D-compressible flows

PurposeTo present the detailed implementation processes of the IDEAL algorithm for two-dimensional compressible flows based on Delaunay triangular mesh, and compare the performance of the SIMPLE and IDEAL algorithms for solving compressible problems. What’s more, the implementation processes of Delaunay mesh generation and derivation of the pressure correction equation are also introduced.Design/methodology/approachProgramming completely in C++.FindingsFive compressible examples are used to test the SIMPLE and IDEAL algorithms, and the comparison with measurement data shows good agreement. The IDEAL algorithm has much better performance in both convergence rate and stability over the SIMPLE algorithm.Originality/valueThe detail solution procedure of implementing the IDEAL algorithm for compressible flows based on Delaunay triangular mesh is presented in this work, seemingly first in the literature.

Algebraic classification of 2+1 geometries: a new approach

We present a convenient method of algebraic classification of 2+1 spacetimes into the types I, II, D, III, N and O, without using any field equations. It is based on the 2+1 analogue of the Newman–Penrose curvature scalars ΨA of distinct boost weights, which are specific projections of the Cotton tensor onto a suitable null triad. The algebraic types are then simply determined by the gradual vanishing of such Cotton scalars, starting with those of the highest boost weight. This classification is directly related to the specific multiplicity of the Cotton-aligned null directions and to the corresponding Bel–Debever criteria. Using a bivector (that is 2-form) decomposition, we demonstrate that our method is fully equivalent to the usual Petrov-type classification of 2+1 spacetimes based on the eigenvalue problem and determining the respective canonical Jordan form of the Cotton–York tensor. We also derive a simple synoptic algorithm of algebraic classification based on the key polynomial curvature invariants. To show the practical usefulness of our approach, we perform the classification of several explicit examples, namely the general class of Robinson–Trautman spacetimes with an aligned electromagnetic field and a cosmological constant, and other metrics of various algebraic types.

Boosting self-efficacy and improving practices for smoking prevention and cessation among South American cancer care providers with a web-based algorithm

BackgroundDigital technologies have positively impacted the availability and usability of clinical algorithms through the advancement in mobile health. Therefore, this study aimed to determine if a web-based algorithm designed to support the decision-making process of cancer care providers (CCPs) differentially impacted their self-reported self-efficacy and practices for providing smoking prevention and cessation services in Peru and Colombia.MethodsA simple decision-making tree algorithm was built in REDCap using information from an extensive review of the currently available smoking prevention and cessation resources. We employed a pre-post study design with a mixed-methods approach among 53 CCPs in Peru and Colombia for pilot-testing the web-based algorithm during a 3-month period. Wilcoxon signed-rank test was used to compare the CCPs’ self-efficacy and practices before and after using the web-based algorithm. The usability of the web-based algorithm was quantitatively measured with the system usability scale (SUS), as well as qualitatively through the analysis of four focus groups conducted among the participating CCPs.ResultsThe pre-post assessments indicated that the CCPs significantly improved their self-efficacy and practices toward smoking prevention and cessation services after using the web-based algorithm. The overall average SUS score obtained among study participants was 82.9 (± 9.33) [Peru 81.5; Colombia 84.1]. After completing the qualitative analysis of the focus groups transcripts, four themes emerged: limited resources currently available for smoking prevention and cessation in oncology settings, merits of the web-based algorithm, challenges with the web-based algorithm, and suggestions for improving this web-based decision-making tool.ConclusionThe web-based algorithm showed high usability and was well-received by the CCPs in Colombia and Peru, promoting a preliminary improvement in their smoking prevention and cessation self-efficacy and practices.

Composite continuum robots: Accurate modeling and model reduction

Models of continuum robots often trade off accuracy and speed. The constant curvature assumption model can perform fast calculations but with poor accuracy. Static models can obtain good calculation accuracy but with slower computation speed. In this paper, a precise and efficient method for establishing a non-constant curvature kinematic model for composite continuum robots is proposed. First, an algorithm based on the Beam Constraint Model is proposed to establish the static model of the continuum robot. The situation in which friction changes gradually in continuum robots is considered in the static model. Then, the Kepler elliptic curve is used to simplify the static model to build a non-constant curvature kinematic model of the continuum robot. Then, complex inverse kinematics solutions are transformed into explicit sets of equations by mathematical transformation. Finally, simulations and experiments are designed to demonstrate the algorithm proposed in this paper. The simulation results show that the proposed algorithm is 1572 times faster than the Levenberg–Marquardt algorithm. The experimental results show that the average error of the static model is 0.065 mm, accounting for 0.13% of its length. The maximum error is 0.309 mm, accounting for 0.618% of its length. The positioning accuracy of the non-constant curvature model proposed in this paper is 2.02 times that of the constant curvature model. The results show that the simplified kinematic model algorithm based on the static model has high accuracy and computational efficiency. This research is crucial for the practical application of continuum robots in engineering.

A novel metaheuristic based on object-oriented programming concepts for engineering optimization

This paper presents a novel, robust, efficient, and simple optimization algorithm called the Object-Oriented Programming Optimization Algorithm (OOPOA) for tackling constrained and unconstrained optimization problems. The algorithm is inspired by the inheritance concept of Object-Oriented programming languages, where the features of a class are classified into three types according to inheritance probability: public, private, and protected. The object-oriented programming inheritance concept is implemented in the algorithm to update the population for the next generations. The proposed algorithm ensures exploitation by selecting the solution with the highest fitness to be inherited in each iteration. It ensures exploration by applying a mutation process that helps explore wide regions in the search space. The performance of this technique is demonstrated by solving 34 different optimization tasks, including 20 standard benchmark problems, ten IEEE Congress of Evolutionary Computation benchmark test functions, and four constrained real-world engineering design problems.

A Simple and Fast Algorithm for Generating Correlation Matrices with a Known Average Correlation Coefficient

This article describes a simple and fast algorithm for generating correlation matrices ( R ) with a known average correlation. The algorithm should be useful for researchers desiring plausible R matrices for substantive domains in which average correlations are known (at least approximately). The method is non iterative and it can solve relatively large problems (e.g., generate a 500 × 500 R matrix) in less than a second on a personal computer. It also has didactic value for introducing students to the convex set of feasible R matrices of a fixed dimension. This Euclidean body is called an elliptope. The proposed method exploits the geometry of elliptopes to efficiently generate realistic R matrices with a desired average correlation coefficient. R code for implementing the algorithm (and for reproducing all of the results of this article) is reported in an online supplement.

The hidden burden of melioidosis in Nepal: A paradigm for the urgent need to implement a simple laboratory algorithm to detect melioidosis in low-resource endemic areas

Melioidosis, an emerging infectious disease caused by the gram-negative bacillus Burkholderia pseudomallei, is massively underdiagnosed in many low- and middle-income countries. The disease is clinically extremely variable, has a high case fatality rate and assumed to be highly endemic in South Asian countries, including Nepal. The reasons for underdiagnosis include lack of awareness among clinicians and laboratory staff and limited microbiological capacities. Since costly laboratory equipment and consumables are likely to remain a significant challenge in many melioidosis-endemic countries in the near future it will be necessary to make optimum use of available tools and promote their stringent implementation. Therefore, we suggest that health facilities in resource-poor countries such as Nepal introduce a simple and low-cost diagnostic laboratory algorithm for the identification of B. pseudomallei cultures. This screening algorithm should be applied specifically to samples from patients with fever of unknown origin and risk factors for melioidosis such as diabetes. Additionally, there could also be a role of low-cost novel promising serological point-of-care tests, which are currently under research and development.

A novel simplified buck power system control algorithm: Application to the emulation of photovoltaic solar panels

This paper proposes an innovative simplified two-stage algorithm for precise and durable regulation of the buck power systems. A critically damped of response is captured and synthesized in the first stage via a second order model. In the second stage, the desired robust response of the system is enforced and stirred by a new parameterless controller. The main feature of this controller is simplicity, which is facilitated by its independence from tunable control parameters. Practical numerical simulations that take into account the impact of plant uncertainties and noise measurements with varying variances are used to thoroughly assess the feasibility of the proposed controller. To highlight the main contribution of this paper, the devised control algorithm is juxtaposed with established controllers, namely the PSO-tuned versions of the sliding mode, backstepping, and PID controllers, alongside other cut cutting-edge controllers, revealing its prowess performance superiority and heightened structural simplicity. Finally, the suggested structure is integrated in a standalone photovoltaic system for appraisal of PV emulation potency. It is found to preserved a superior performance in the context of PV emulation as compared to existing emulators, achieving a dynamic efficiency of 97.85 % in the specific case of MPPT.

Visualization of the rolling motion of spheres connected with a rubber band using an image processing technique

The traditional physics laboratory has adopted a photogate and polarized light to measure rotation motion in a fixed system, but they are not applicable to rolling objects. Computer vision has played an increasingly important role in image analysis. The popularization of mobile phones, cameras and computers makes it possible to measure the rotation of an object in a simple but nonintrusive way in a physics laboratory. A ‘tracker’ has been used to analyze the rotation motion of large objects, such as vehicle wheels, by recognizing the position of a marker. However, it is still challenging to precisely recognize the marker in a small object via simple algorithms in a physics laboratory. In this paper, we introduce a facile image processing technique to visualize the rotation and spin motion of spheres by marking it with two red and green semi-spheres. A basic formula of projection was derived to analyze the expression of spin angles with the projection area of the semi-sphere. The precision and suitability of the image processing technique was proven to be effective through comparison with the photogate measurement technique. The image processing technique has also been used to analyze the rotation and spin motion of two spheres bonded with a rubber band. It provides not only the trajectory of sphere centers, but the evolution of spin angles, orbit diameter and orbit angles of spheres. By analyzing the relationship between spin angles and orbit diameter, it is clear that the rubber band experienced typical transformations between three different phases (twist, coil and supercoil) until the energy was exhausted. The method offers valuable insights into rotational dynamics, showcasing its potential for practical applications in the physics laboratory and in educational contexts.

Extension of Negative-Sequence Current Compensation Range Based on Negative- and Zero-Sequence Voltage Injection for Hybrid Cascaded STATCOM

Negative sequence voltage (NSV) injection is an effective cluster balancing control for CHB STATCOM, which has a higher capability in eliminating unbalanced active powers than zero sequence voltage (ZSV) injection. Unfortunately, NSV is employed for negative sequence current control under unbalanced current compensation applications, and only ZSV injection is used for cluster balancing, thereby seriously limiting negative sequence current compensation range (NCCR). To extend NCCR, the converter with a common DC link, called power exchange unit (PEU), is inserted into CHB to form a hybrid cascaded structure, which can freely exchange the unbalanced active powers via the common DC link. However, only ZSV injection method fails to take the advantage of this hybrid cascaded converter (HCC) to extend NCCR. In this paper, the NSV injection with a simple algorithm in dq frame is proposed for the HCC STATCOM with negative sequence current compensation. Owing to the PEU, the NSV of CHB for cluster balancing is counteracted by superposing an opposite NSV into PEU, thus transferring unbalanced active power from CHB to PEU and not affecting the negative sequence current control. Due to the limit of PEU capacity, the ZSV injection is also employed, and thus a novel cluster balancing control based on NSV and ZSV injection is proposed, based on which the NCCR is greatly extended. Finally, the proposed control is verified by the experimental results on a 400V / 7.5kvar HCC STATCOM.

Rapid standoff spectroscopic characterization of plastic waste using quartz tuning fork

Standoff molecular identification of chemicals finds immense applications in homeland security, forensic investigation and plastic recycling industries. Although, standoff detection using mid-infrared radiation offers excellent molecular selectivity, sensitive detection of mid-IR radiation using inexpensive detectors is a challenge. In the present work, we show commercially available inexpensive Quartz Tuning Fork (QTF) can be effectively used for rapid standoff detection of solid samples using mid-IR radiation. In this method, a plastic sample placed 40 cm away was excited with tunable infrared (IR) radiation pulsed at the resonance frequency of the QTF. The IR radiation scattered off the plastic sample was used for exciting the QTF into resonance. Plotting the QTF resonant amplitude as a function of irradiating IR wavelength represents the unique IR spectrum of the plastic sample under study. The resolution of spectra recorded using QTF was found to be superior to those collected with ATR-FTIR and the technique based on QTF was 103 times faster than microcantilever-based photothermal deflection techniques. By combining simple machine learning algorithms with QTF standoff resonance IR spectra, various plastic samples can be effectively classified with 100% accuracy. Also, this technique was found to be capable of identifying black plastics without any further sample preparation requirements.