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The article presents information on the publication of a book "Applied Statistics, Algorithms," relevant to statistics, by the Royal Statistical Society in cooperation with the Science Research Council's Working Party on Statistical Computing. A policy statement describing the editorial policy appears in "Applied Statistics," Vol. 1. No. 1 (1968). A support paper describing the expected contents of the external specification and making recommendation for the layout of algorithms and for programming strategy will appear in the following issue.

This paper investigates the problem of factor prime factorizations for n-D polynomial matrices and presents a criterion for the existence of factor prime factorizations for an important class of n-D polynomial matrices. As a by-product, we also obtain an algebraic algorithm to check n-D factor primeness in some important cases which partially solves the long-standing open problem of recognizing n-D factor prime matrices. Some problems related to the factorization methods are also studied. Several exam- pies are given to illustrate the results. The results presented in this paper are true over any coefficient field. [ABSTRACT FROM AUTHOR]

The Association for Computing Machinery (ACM) Press is pleased to announce that the Collected Algorithms from ACM (CALGO) is now available on acm.org. as of February 1997. Originally established in 1960 as the Algorithms Department in CACM, and then transfered to Transactions on Mathematical Software in 1975, CALGO is a collection of heavily used algorithms, either in original form or translated into other languages. Planned enhancements include a cumulative SHAR classification index and the full CALGO library in CD-ROM. Contact address for any information regarding CALGO has been provided.

This paper addresses the robust gradient learning (RGL) problem. Gradient learning models aim at learning the gradient vector of some target functions in supervised learning problems, which can be further used to applications, such as variable selection, coordinate covariance estimation, and supervised dimension reduction. However, existing GL models are not robust to outliers or heavy-tailed noise. This paper provides an RGL framework to address this problem in both regression and classification. This is achieved by introducing a robust regression loss function and proposing a robust classification loss. Moreover, our RGL algorithm works in an instance-based kernelized dictionary instead of some fixed reproducing kernel Hilbert space, which may provide more flexibility. To solve the proposed nonconvex model, a simple computational algorithm based on gradient descent is provided and the convergence of the proposed method is also analyzed. We then apply the proposed RGL model to applications, such as nonlinear variable selection and coordinate covariance estimation. The efficiency of our proposed model is verified on both synthetic and real data sets. [ABSTRACT FROM AUTHOR]

The article focuses on technological innovations that are resulting from research into origami. It states that origami has been described mathematically and modeled with computers, allowing engineers to create technologies that can be folded into a compact shape for transport. It mentions that each folded flap in origami uses a circular portion which allows engineers plan creases that will provide a desired shape. It comments that the folding algorithms are used in technological applications.

This paper presents a new approach to blind source extraction from convolutive mixtures in multi-input multi-output (MIMO) channels. Two ill-conditioned cases are considered: the number of sensors is less than the number of sources and the number of sensors is greater than or equal to the number of sources but the system is noninvertible. Although there exist several works related to ill-conditioned dynamic MIMO channels, especially on blind channel identification, how to obtain a true source Only from observable convolutive mixtures is still an open problem. In this paper, beginning with introducing two blind ex- traction models for blind deconvolution in ill-conditioned MIMO channels, we discuss the extractability issue. Results from our extractability analysis (a necessary and sufficient condition) show that it is possible to extract individual sources from the outputs. Furthermore, all potentially separable sources (at most equal to the number of sensors) can be extracted sequentially based on these extraction models. A cost function based on cross cumulant is discussed along with the Gauss-Newton algorithm. Finally, a simulation example is presented for illustration. [ABSTRACT FROM AUTHOR]

The article presents the discussion on digital rights management (DRM). Topics include other form of rights management impeding their ability for pacifying the children; protecting content licensors' rights while giving purchasers, renters, and subscribers flexible and fair options for watching content; and containing content encryption and license generation.

In this paper, a power-area efficient geometry engine (GE) using a low-complexity three-level subdivision algorithm is presented. The proposed subdivision algorithm and architecture is capable of providing low complexity, high power-area efficiency, scalable and near-Phong shading quality. The forward difference, edge function recovery, dual space subdivision, triangle filtering, and triangle setup coefficient sharing schemes are employed to alleviate the redundant computation for the proposed algorithm. According to the low-complexity subdivision algorithm, one reconfigurable datapath is proposed to save the area since the same set of processing elements (PE) is reused for different operations of GE. Compared with the conventional subdivision algorithm, the proposed subdivision algorithm reduces the number of memory/register accesses for subdivision by 40% and 60.32% for level-1 and level-2 subdivision, respectively. In terms of the number of multiplications for transforms, the reduction can be attained by 27.5% and 60.27% for level-1 and level-2 subdivision, respectively. From the implementation results, the proposed GE can achieve the power-area efficiency of 518.8 Kvertices/(s\bulletmW\bulletmm^2) for level-1 subdivision. [ABSTRACT FROM PUBLISHER]

This article discusses a quicker method to multiply two whole numbers, devised by David Harvey of the University of New South Wales in Australia and Joris van der Hoeven at the Ecole Polytechnique in France. The author examines the impact of this method on computing algorithms and in the field of computational complexity theory.

Network utility maximization (NUM) problem formulations provide an important approach to conduct network resource allocation and to view layering as optimization decomposition. In the existing literature, distributed implementations are typically achieved by means of the so-called dual decomposition technique. However, the span of decomposition possibilities includes many other elements that, thus far, have not been fully exploited, such as the use of the primal decomposition technique, the versatile introduction of auxiliary variables, and the potential of multilevel decompositions. This paper presents a systematic framework to exploit alternative decomposition structures as a way to obtain different distributed algorithms, each with a different tradeoff among convergence speed, message passing amount and asymmetry, and distributed computation architecture. Several specific applications are considered to illustrate the proposed framework, including resource-constrained and direct-control rate allocation, and rate allocation among Q0S classes with multipath routing. For each of these applications, the associated generalized NUM formulation is first presented, followed by the development of novel alternative decompositions and numerical experiments on the resulting new distributed algorithms. A systematic enumeration and comparison of alternative vertical decompositions in the future will help complete a mathematical theory of network architectures. [ABSTRACT FROM AUTHOR]

In this paper, a novel optimization technique is proposed to optimize filter coefficients of linear phase finite-impulse response (FIR) filter to share common subexpressions within and among coefficients. Existing approaches of common subexpression elimination optimize digital filters in two stages: first, an FIR filter is designed in a discrete space such as finite wordlength space or signed power-of-two (SPT) space to meet a given specification; in the second stage, an optimization algorithm is applied on the discrete coefficients to find and eliminate the common subexpressions. Such a two-stage optimization technique suffers from the problem that the search space in the second stage is limited by the finite wordlength or SPT coefficients obtained in the first stage optimization. The new proposed algorithm overcomes this problem by optimizing the filter coefficients directly in subexpression space for a given specification. Numerical examples of benchmark filters show that the required number of adders obtained using the proposed algorithm is much less than those obtained using two-stage optimization approaches. [ABSTRACT FROM AUTHOR]

In this paper, a new spilt-radix fast Hartley transform (FHT) algorithm is proposed for computing the discrete Hartley transform (DHT) of an arbitrary length N = q * 2m, where q is an odd integer. The basic idea behind the proposed FHT algorithm is that a mixture of radix-2 and radix-S index maps is used in the decomposition of the DHT. This idea and the use of an efficient in- dexing process lead to a new decomposition different from that of the existing split-radix FHT algorithms, since the existing ones are all based on the use of a mixture of radix-2 and radix-4 index maps. The proposed algorithm reduces substantially the operations such as data transfer, address generation, and twiddle factor evaluation or access to the lookup table, which contribute significantly to the execution time of FHT algorithms. it is shown that the arithmetic complexity (multiplications+additions) of the proposed algorithm is, in almost all cases, the same as that of the existing split-radix FHT algorithm for length- q * 2m DHTs. Since the proposed algorithm is expressed in a simple matrix form, it facilitates an easy implementation of the algorithm, and allows for an extension to the multidimensional case. [ABSTRACT FROM AUTHOR]

In this paper, we present an efficient algorithm to compute singular points and singularity-induced bifurcation points of differential-algebraic equations for a multimachine power-system model Power systems are often modeled as a set of differential-algebraic equations (DAE) whose algebraic part brings singularity issues into dynamic stability assessment of power systems. Roughly speaking, the singular points are points that satisfy the algebraic equations, but at which the vector field is not defined. In terms of power-system dynamics, around singular points, the generator angles (the natural states variables) are not defined as a graph of the load bus variables (the algebraic variables). Thus, the causal requirement of the DAE model breaks down and it cannot predict system behavior. Singular points constitute important organizing elements of power-system DAE models. This paper proposes an iterative method to compute singular points at any given parameter value. With a lemma presented in this paper, we are also able to locate singularity induced bifurcation points upon identifying the singular points. The proposed method is implemented into voltage stability toolbox and simulations results are presented for a 5-bus and IEEE 118-bus systems. [ABSTRACT FROM AUTHOR]

A recent study conducted at the University of California Riverside has developed an algorithm for searching optimal variance component estimators in linear mixed models. The study focuses on the estimation of variance components, which is crucial in data analysis based on a linear mixed model. The algorithm aims to derive strictly positive unbiased estimators with minimum variance by modifying the method-of-moments estimator using a class of square non-singular regularization matrices. The proposed method allows for the convenient study of the theoretical and numerical properties of the estimator, even in small samples. The research concludes by illustrating the use of the algorithm in two illustrative examples. [Extracted from the article]

Purpose Ordinary differential equations (ODEs) are widely used in the engineering curriculum. They model a spectrum of interesting physical problems that arise in engineering disciplines. Studies of different types of ODEs are determined by engineering applications. Various techniques are used to solve practical differential equations problems. This paper aims to present a computational tool or a computer-assisted technique aimed at tackling ODEs. This method is usually not taught and/or not accessible to undergraduate students. The aim of this strategy is to help the readers to develop an effective and relatively novel problem-solving skill. Because of the drudgery of hand computations involved, the method requires the need to use computers packages. In this work, the successive differentiation method (SDM) for solving linear and nonlinear and homogeneous or non-homogeneous ODEs is presented. The algorithm uses the successive differentiation of any given ODE to determine the values of the function’s derivatives at a single point, mostly x = 0. The obtained values are used to construct the Taylor series of the solution of the examined ODE. The algorithm does not require any new assumption, hence handles the problem in a direct manner. The power of the method is emphasized by testing a variety of models with distinct orders, with constant and variable coefficients. Most of the symbolic and numerical computations can be carried out using computer algebra systems.Design/methodology/approach This study presents a computational tool or a computer-assisted technique aimed at tackling ODEs. This method is usually not taught and/or not accessible to undergraduate students. The aim of this strategy is to help the readers to develop an effective and relatively novel problem-solving skill. Because of the drudgery of hand computations involved, the method requires the need to use computers packages.Findings This method is applied to a variety of well-known equations, such as the Bernoulli equation, the Riccati equation, the Abel equation and the second-order Euler equation, some with constant and variable coefficients. SDM handles linear and nonlinear and homogeneous or nonhomogeneous ODEs in a direct manner without any need to restrictive conditions. The method works effectively to the Volterra integral equations, as will be discussed in a coming work.Originality/value The method can be extended to a wide range of engineering problems that are modeled by differential equations. The method is simple and novel and highly accurate. [ABSTRACT FROM AUTHOR]

The article reports on finding all subgraphs of an undirected graph [H]. A maximal complete subgraph is also called clique which refers to a complete subgraph that is not included in any other complete subgraph. According to the authors, a research paper was released wherein descriptions of techniques to find maximal complete subgraphs are provided. The authors discussed two algorithms using a branch-and-bound technique so that there will be no clique. The first algorithm produces cliques in lexicographic order while the second is derived from the first algorithm.

Keywords: Beijing; People's Republic of China; Asia; Mathematics; Algorithms; Bone Research; Health and Medicine EN Beijing People's Republic of China Asia Mathematics Algorithms Bone Research Health and Medicine 2296 2296 1 08/07/23 20230811 NES 230811 2023 AUG 11 (NewsRx) -- By a News Reporter-Staff News Editor at Health & Medicine Week -- Researchers detail new data in Mathematics. Beijing, People's Republic of China, Asia, Mathematics, Algorithms, Bone Research, Health and Medicine. [Extracted from the article]

Neely has discussed computational error generated by some algorithms used to compute various statistics. In the present paper methods are described which are error-free, simple in concept, and usually less costly in machine time than those mentioned by Neely. [ABSTRACT FROM AUTHOR]

A recent study conducted at COMSATS University in Islamabad, Pakistan, has focused on the importance of selecting the right medical device manufacturer in healthcare systems. The researchers developed a decision-making algorithm based on fuzzy theory to assist in choosing the most suitable worldwide medical device manufacturer. They utilized complex q-rung orthopair fuzzy Yager aggregation operators and tested their efficacy in multi-criteria decision-making. The results demonstrated the adaptability and efficiency of the proposed algorithm and aggregation operators. The research has been peer-reviewed and confirmed to produce precise and accurate outcomes. [Extracted from the article]

A recent study conducted in Dongguan, People's Republic of China, focused on the application of sequential databases in various fields such as market basket analysis, medical prediction, and sign language recognition. The study highlighted the limitations of previous research that assumed each event occurred instantaneously and proposed the integration of duration with temporal patterns in interval-based sequential databases. The researchers developed two algorithms, FTDPMiner-EP and FTDPMiner-TM, to mine frequent temporal duration-based patterns (TDPs). The experiments conducted on real and synthetic databases demonstrated the good performance of the algorithms. This research has been peer-reviewed and provides valuable insights into the field of mathematics. [Extracted from the article]

Chongqing, People's Republic of China, Asia, Mathematics, Algorithms, Brain, Central Nervous System, Cerebrum, Health and Medicine, Telencephalon Keywords: Chongqing; People's Republic of China; Asia; Mathematics; Algorithms; Brain; Central Nervous System; Cerebrum; Health and Medicine; Telencephalon EN Chongqing People's Republic of China Asia Mathematics Algorithms Brain Central Nervous System Cerebrum Health and Medicine Telencephalon 1137 1137 1 04/10/23 20230414 NES 230414 2023 APR 14 (NewsRx) -- By a News Reporter-Staff News Editor at Health & Medicine Week -- Investigators publish new report on Mathematics. [Extracted from the article]

Purpose – The purpose of this paper is to present a weighted algorithm based on the homotopy perturbation method for solving the heat transfer equation in the cast-mould heterogeneous domain. Design/methodology/approach – A weighted algorithm based on the homotopy perturbation method is used to minimize the volume of computations. The authors show that this technique yields the analytical solution of the desired problem in the form of a rapidly convergent series with easily computable components. Findings – The authors illustrate that the proposed method produces satisfactory results with respect to Adomian decomposition method and standard homotopy perturbation method. The reliability of the method and the reduction in the size of computational domain give this method a wider applicability. Originality/value – This research presents, for the first time, a new modification of the proposed technique, for aforementioned problems and some interesting results are obtained. [ABSTRACT FROM AUTHOR]

Cascaded Diophantine Frequency Synthesis' (CDFS) is an approach to high-resolution frequency synthesis based on the mathematical properties of integer numbers and Diophantine equations. CDFS can be implemented using two or more phase- locked loops (PLLs) and frequency mixing stages in a cascade topology. CDFS achieves frequency resolution arbitrarily finer than that of the constituent PLLs while maintaining their loop bandwidths and frequency hopping agility. CDFS results in inter- mediate signals with minimal frequency ranges in all frequency mixing stages, allowing for improved spectral purity and lower design complexity compared to the parallel form of its predecessor, Diophantine Frequency Synthesis (DFS). CDFS architectures are modularly structured and expandable. The paper introduces CDFS focusing on the mathematical and algorithmic aspects. [ABSTRACT FROM AUTHOR]

This paper introduces a tightly coupled topographic sensor-processor and digital signal processor (DSP) architecture for real-time visual multitarget tracking (MTT) applications. We define real-time visual MTT as the task of tracking targets contained in an input image flow at a sampling-rate that is higher than the speed of the fastest maneuvers that the targets make. We utilize a sensor-processor based on the cellular neural network universal machine architecture that permits the offloading of the main image processing tasks from the DSP and introduces opportunities for sensor adaptation based on the tracking performance feedback from the DSP. To achieve robustness, the image processing algorithms running on the sensor borrow ideas from biological systems: the input is processed in different parallel channels (spatial, spatio-temporal and temporal) and the interaction of these channels generates the measurements for the digital tracking algorithms. These algorithms (running on the DSP) are responsible for distance calculation, state estimation, data association and track maintenance. The performance of the proposed system is studied using actual hardware for different video flows containing rapidly moving maneuvering targets. [ABSTRACT FROM AUTHOR]

This paper presents a new technique for the passivity enforcement of linear time-invariant multiport systems in state- space form. This technique is based on a study of the spectral properties of related Hamiltonian matrices. The formulation is applicable in case the system input-output transfer function is in admittance, impedance, hybrid, or scattering form. A standard test for passivity is first performed by checking the existence of imaginary eigenvalues of the associated Hamiltonian matrix. In the presence of imaginary eigenvalues the system is not passive. In such a case, a new result based on first-order perturbation theory is presented for the precise characterization of the frequency bands where passivity violations occur. This characterization is then used for the design of an iterative perturbation scheme of the state matrices, aimed at the displacement of the imaginary eigenvalues of the Hamiltonian matrix. The result is an effective algorithm leading to the compensation of the passivity violations. This procedure is very efficient when the passivity violations are small, so that first-order perturbation is applicable. Several examples illustrate and validate the procedure. [ABSTRACT FROM AUTHOR]

In order to solve the problem that previous relation researches in operational task-resource matching are hard to flexible computing for generating a new matching scheme from the existing scheme under the condition of operational tasks or resources adjusted in uncertainty cases, role-based approaches to operational task-resource flexible matching model and algorithm are proposed in the paper for flexible matching operational tasks with resources. Firstly, through introducing the concept of roles, the role-based calculation framework of operational task-resource flexible matching is constructed. Secondly, two aspect indexes about resource utilization ratio (RUR) and time utilization ratio (TUR) are given to reflect operational task-resource matching quality (TRMQ), which can be regarded as the objective function for modeling role-based operational task-resource flexible matching mathematical formulation. On the basis of this, the role-based artificial bee colony (RABC) algorithm, including five specific calculating operators, is put forward for solving the flexible matching problem with double encoding on operational tasks and resources by roles. Finally, via comparing with the previous methods in application cases, it can be validated that role-based model and proposed algorithm are more effective, which can be used to obtain a new incremental scheme from the existing matching scheme for adopting the operational tasks or resources adjustment. Moreover, there are flexible computation advantages of the approaches proposed in this paper to solve the problem about operational task-resource matching in large-scale. [ABSTRACT FROM AUTHOR]

A recent report from Universiti Malaya discusses research on cancer treatment using optimal control supported by swarm intelligence. The study aims to develop hybrid techniques that combine optimal control theory with evolutionary algorithms and multi-objective swarm algorithms to reduce cancerous cells while minimizing the use of chemotherapy medications and toxicity. Two hybrid techniques were proposed and evaluated, with MOEA/D emerging as the most effective algorithm in reducing tumor size and cancer drug concentration. The study highlights the importance of integrating optimal control theory and evolutionary algorithms for optimizing cancer chemotherapy treatment. [Extracted from the article]

This paper describes an alternate method for summing a set of floating-point numbers. Comparison of the error bound for this method with that of the standard summation method shows that it is considerably less sensitive to propagation of round-off error. [ABSTRACT FROM AUTHOR]

Abstract The study of properties of gradual evaluation methods in argumentation has received increasing attention in recent years, with studies devoted to various classes of frameworks/ methods leading to conceptually similar but formally distinct properties in different contexts. In this paper we provide a novel systematic analysis for this research landscape by making three main contributions. First, we identify groups of conceptually related properties in the literature, which can be regarded as based on common patterns and, using these patterns, we evidence that many further novel properties can be considered. Then, we provide a simplifying and unifying perspective for these groups of properties by showing that they are all implied by novel parametric principles of (either strict or non-strict) balance and monotonicity. Finally, we show that (instances of) these principles (and thus the group, literature and novel properties that they imply) are satisfied by several quantitative argumentation formalisms in the literature, thus confirming the principles' general validity and utility to support a compact, yet comprehensive, analysis of properties of gradual argumentation. [ABSTRACT FROM AUTHOR]

Investigates the efficacy of algorithm for the assignment of instruction addresses and formats. Conditions for the presentation of algorithm; Suitability of the algorithm for arbitrary program structure; Existence of optimality criterion implying preferential choices subjects to the addressing constraints.

In this paper, we propose a fast algorithm for sign- extraction of a number given in the Residue Number System (2n - 1, 2n, 2n + 1). The algorithm can be implemented using three n-bit wide additions, two of which can be done in parallel. It can be used in a wide variety of problems, i.e., in algorithms for dividing numbers in the RNS, or in evaluating the sign of determinant in computational geometry, etc. [ABSTRACT FROM AUTHOR]

Purpose - The paper seeks to provide an adaptive fuzzy logic controller for permanent magnet synchronous motor (PMSM) under direct torque control (DTC) algorithm to minimize the torque ripple. Design/methodology/approach - The design methodology is based on vector control analysis. MATLAB simulations supported with experimental study under C++ are used to execute the proposed work. Findings - The results show that considerable torque ripple reduction as well as considerable current ripple reduction can be achieved by utilizing adaptive fuzzy switching algorithm to fire the inverter supplying the PMSM. Research limitations/implications - This research is limited to PMSM, however the research can be extended to include other AC motors as well. In addition, the following points can be studied, the effects of harmonics in control signals on the torque ripple. Digital and active filters as solution to these harmonics can be also addressed. The actual mathematical relation between the torque ripple and flux ripple can be studied to set the flux and torque bands width in reasonable value. Practical implications - Based on existence DTC control system, it is only required to change the software-switching algorithm, to provide smooth torque, given that the switching frequency of the inverter module is more than or equal to 15?kHz and the system is supplied with timers. In addition, a relatively higher DC voltage may be required to achieve higher speed compared with the traditional DTC. Originality/value - In this paper, the stator flux position, and errors due to deviations from reference values of the torque and stator flux are used to select two active vectors while at the same time the absolute value of the torque error and the stator flux position are fuzzified to adapt the switching of the inverter in order to control the applied average voltage level in such a way as to minimize the torque ripple, so instead of fixed time table structure, a fuzzy logic is used to calculate the switching time for the selected vectors and no PI controller is used as the case in the traditional-space vector modulation. This work is directed to motor drive system designers who seek highly smooth torque performance with fast response. [ABSTRACT FROM AUTHOR]

Gambling has provided centuries of inspiration to probabilists and statisticians. The process continues. There also exist fundamental links between betting and a newer subject, Information Theory, which began with Claude Shannon and his ground-breaking 1948 paper A Mathematical Theory of Communication. It is a result which arises very naturally. A successful gambler and a successful data compression algorithm must both accurately estimate probability distributions. There are practical results as well as theoretical: Shannon and colleagues, including the legendary gambler and mathematician Edward Thorp, actually attempted to apply results from information theory in Las Vegas casinos and stock market transactions. Oliver Johnson examines the connections. [ABSTRACT FROM AUTHOR]

Keywords: Algorithms; Bone Research; Health and Medicine; Mathematics EN Algorithms Bone Research Health and Medicine Mathematics 6668 6668 1 08/14/23 20230818 NES 230818 2023 AUG 18 (NewsRx) -- By a News Reporter-Staff News Editor at Health & Medicine Week -- Investigators publish new report on mathematics. Algorithms, Bone Research, Health and Medicine, Mathematics. [Extracted from the article]

This paper studies the rendezvous strategy for a group of unicycle systems with connectivity preservation and collision avoidance. Based on the method of potential functions, a novel distributed control algorithm is proposed for all unicycles. By tuning the design parameters, the unicycles finally aggregate so that the average of the distances is bounded by a pre-specified positive number. It is proved that the connectivity of a minimum spanning tree in the initial topology is guaranteed. The result is then extended to multiple unicycles with heterogenous input disturbances. Potential function is further modified to handle the disturbances. Illustrative example is presented to show the improvements and effectiveness of the proposed controller. [ABSTRACT FROM AUTHOR]

Our news reporters obtained a quote from the research from University of Vigo: "As a consequence, it is necessary to shorten the time spent in locating and reconstructing the atheroma plaque that can be developed in an artery. Keywords: Algorithms; Angiology; Health and Medicine; Intravascular; Mathematics EN Algorithms Angiology Health and Medicine Intravascular Mathematics 6249 6249 1 03/23/23 20230303 NES 230303 2023 MAR 3 (NewsRx) -- By a News Reporter-Staff News Editor at Health & Medicine Week -- Investigators discuss new findings in mathematics. [Extracted from the article]

In this paper, we focus on optimal H 2 model reduction methods for bilinear systems. The optimal H 2 model reduction problem can be viewed as a minimization problem on Grassmann manifold. By utilizing the geometry of Grassmann manifold, a gradient descent model reduction algorithm and a conjugate gradient model reduction algorithm based on Grassmann manifold are given. These two algorithms can simulate well the behavior of the original system and the order-reduced systems generated by our algorithms can satisfy the minimal stability requirement. Numerical examples are given to illustrate the effectiveness of our methods. [ABSTRACT FROM AUTHOR]

A study conducted by Chongqing Medical University in China has developed a new algorithm for detecting hip dysplasia. The algorithm, called Cba-yolov5s, is based on the YOLOv5s model and incorporates angle consistency and bi-level routing attention. By expanding the local neighborhood size and filtering out irrelevant regions, the algorithm improves the accuracy of hip joint keypoint detection and positioning. The algorithm was tested on a clinical dataset and outperformed existing algorithms in terms of error reduction. The researchers believe that this algorithm could provide a possibility for automatic diagnosis of hip dysplasia. [Extracted from the article]

The article presents new research from Shenyang University on a gastrointestinal image classification method using an improved Adam algorithm, AdamW_AGC, which enhances classification accuracy and training stability. Topics include the challenges in medical image classification, the proposed AdamW_AGC algorithm, and experimental results demonstrating its effectiveness on various datasets.

A recent study conducted at Silesian University of Technology in Gliwice, Poland, has developed an algorithm called RuleKit-CS that allows for the robust mining of contrast sets in classification, regression, and survival data. Contrast set mining is an important knowledge discovery problem used in various fields such as medicine, industry, and economics. The algorithm was found to be a useful tool for discovering differences between defined groups, with higher support and precision than popular competitors. The algorithm has been implemented as part of the RuleKit suite. [Extracted from the article]

Researchers from Universidade Nove de Julho in Sao Paulo, Brazil, have published a report exploring the application of complex network models and genetic algorithms in epidemiological modeling. The study aims to replicate the dynamics of disease spread in urban environments by accurately mapping individual contacts and social networks. Using a genetic algorithm, the researchers estimate the input parameters for network construction and simulate disease transmission within these networks. The results demonstrate the networks' resemblance to real social interactions and highlight the potential of complex network models and genetic algorithms in predicting and managing public health crises. [Extracted from the article]

A researcher from Shandong Youth University of Political Science has developed a breast ultrasound image classification algorithm based on a combination of convolutional neural network (CNN) and Transformer models. The algorithm aims to improve the interpretability and accuracy of computer-aided diagnosis (CAD) systems for breast cancer detection. By leveraging tumor boundaries and extracting both local and global features, the proposed model achieved state-of-the-art performance with an accuracy of 0.9870 and an F1 score of 0.9872. The research highlights the potential of deep learning models in enhancing the interpretation of medical images and reducing the workload of doctors. [Extracted from the article]

Researchers at the University of Southampton in the United Kingdom have developed a new method for automatically identifying the inspiratory and expiratory breathing phases in lung sound recordings. This is important for monitoring and diagnosing diseases, as adventitious lung sounds can indicate the presence of a disease. The algorithm uses a filter to estimate the second derivative of the lung sound signal and then calculates its normalized absolute value to identify the breathing phases. The research has been peer-reviewed and published in the journal Biomedical Signal Processing and Control. [Extracted from the article]

A research report from the Centro Federal de Educacao Tecnologica de Minas Gerais discusses a novel approach to controlling the Aedes aegypti mosquito, which is the main vector for diseases such as dengue, yellow fever, Zika, and chikungunya. The study proposes a two-dimensional diffusion-reaction model that describes the interaction between aquatic and adult female stages of the mosquito, taking into account parameters dependent on rainfall and temperature. The researchers used optimization techniques and genetic algorithms to find optimal solutions for minimizing the mosquito population. Numerical results showed a significant reduction in the Aedes aegypti population. [Extracted from the article]

A study conducted by researchers at Beijing University of Chemical Technology explores the implementation of data analysis and information management for elderly nursing care. The study focuses on caregiver activity recognition and the use of wearable devices to improve the inspection of caregivers' work. The researchers used the XGBoost model, along with other algorithms, to analyze the characteristics of caregivers' activities and optimize recognition performance. The study concludes that the application of information technology and artificial intelligence can effectively promote the digitalization and intelligent development of the elderly nursing care industry. [Extracted from the article]

A report from the School of Mathematics and Statistics in Changsha, People's Republic of China, discusses the use of a novel automatic detection and classification algorithm for elderly cognitive impairment using Convolutional Support Vector Machine (CSVM). The study focuses on Alzheimer's disease (AD) and the importance of early diagnosis in clinical practice. The research utilizes survey data from elderly residents in Changsha to construct a cognitive impairment dataset and evaluates the performance of the CSVM algorithm in identifying cognitive impairment. The study concludes that accurate differentiation of normal cognition, mild cognitive impairment (MCI), and AD can aid in timely intervention and adjuvant treatment for potential patients. [Extracted from the article]