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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]

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.

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]

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]

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]

A study conducted by researchers at Indiana University School of Medicine has developed a new mathematical model for analyzing recurrent events. The model, called a flexible time-varying coefficient rate model, addresses the limitations of existing rate models by allowing for time-varying covariate effects. The researchers used an efficient algorithm to fit the model and demonstrated its consistency and performance through simulation studies. The model was applied to analyze data from a clinical study on behavioral risk factors for sexually transmitted infections. This research was supported by the NIH National Institute on Alcohol Abuse & Alcoholism. [Extracted from the article]

A research report from Shenyang University in China introduces an improved variant of the Adam optimizer called the BGE-Adam optimization algorithm. This algorithm incorporates three innovative technologies to enhance its adaptability, convergence, and robustness under various training conditions. The BGE-Adam algorithm utilizes a dynamic adjustment mechanism, gradient prediction model, and entropy weighting to improve its performance. Experimental results on different datasets, including medical image gastrointestinal disease tests, demonstrate that the BGE-Adam algorithm achieves higher accuracy and exhibits better convergence and robustness compared to the standard Adam algorithm. This research provides new perspectives for the future development of deep learning optimization algorithms. [Extracted from the article]

Abstract: Credal networks are models that extend Bayesian nets to deal with imprecision in probability, and can actually be regarded as sets of Bayesian nets. Credal nets appear to be powerful means to represent and deal with many important and challenging problems in uncertain reasoning. We give examples to show that some of these problems can only be modeled by credal nets called non-separately specified. These, however, are still missing a graphical representation language and updating algorithms. The situation is quite the opposite with separately specified credal nets, which have been the subject of much study and algorithmic development. This paper gives two major contributions. First, it delivers a new graphical language to formulate any type of credal network, both separately and non-separately specified. Second, it shows that any non-separately specified net represented with the new language can be easily transformed into an equivalent separately specified net, defined over a larger domain. This result opens up a number of new outlooks and concrete outcomes: first of all, it immediately enables the existing algorithms for separately specified credal nets to be applied to non-separately specified ones. We explore this possibility for the 2U algorithm: an algorithm for exact updating of singly connected credal nets, which is extended by our results to a class of non-separately specified models. We also consider the problem of inference on Bayesian networks, when the reason that prevents some of the variables from being observed is unknown. The problem is first reformulated in the new graphical language, and then mapped into an equivalent problem on a separately specified net. This provides a first algorithmic approach to this kind of inference, which is also proved to be NP-hard by similar transformations based on our formalism. [Copyright &y& Elsevier]

Abstract: Non-negative Matrix Factorization (NMF) and Probabilistic Latent Semantic Indexing (PLSI) have been successfully applied to document clustering recently. In this paper, we show that PLSI and NMF (with the I-divergence objective function) optimize the same objective function, although PLSI and NMF are different algorithms as verified by experiments. This provides a theoretical basis for a new hybrid method that runs PLSI and NMF alternatively, each jumping out of the local minima of the other method successively, thus achieving a better final solution. Extensive experiments on five real-life datasets show relations between NMF and PLSI, and indicate that the hybrid method leads to significant improvements over NMF-only or PLSI-only methods. We also show that at first-order approximation, NMF is identical to the -statistic. [Copyright &y& Elsevier]

Abstract: This paper studies generalized rough sets over fuzzy lattices through both the constructive and axiomatic approaches. From the viewpoint of the constructive approach, the basic properties of generalized rough sets over fuzzy lattices are obtained. The matrix representation of the lower and upper approximations is given. According to this matrix view, a simple algorithm is obtained for computing the lower and upper approximations. As for the axiomatic approach, a set of axioms is constructed to characterize the upper approximation of generalized rough sets over fuzzy lattices. [Copyright &y& Elsevier]

Abstract: This paper examines the problem of static output feedback control of a Takagi–Sugeno (TS) fuzzy system. The existence of a static output feedback control law is given in terms of the solvability of bilinear matrix inequalities. An iterative algorithm based on the linear matrix inequality is proposed to compute the static output feedback gain. To reduce the conservatism of the design, the structural information of the membership function of the fuzzy rules is incorporated. Numerical examples are used to illustrate the validity of the methods. [Copyright &y& Elsevier]

This paper investigates the applicability of the stencil-adaptive finite difference method for the simulation of two-dimensional unsteady incompressible viscous flows with curved boundary. The adaptive stencil refinement algorithm has been proven to be able to continuously adapt the stencil resolution according to the gradient of flow parameter of interest [Ding H, Shu C. A stencil adaptive algorithm for finite difference solution of incompressible viscous flows. J Comput Phys 2006;214:397–420], which facilitates the saving of the computational efforts. On the other hand, the capability of the domain-free discretization technique in dealing with the curved boundary provides a great flexibility for the finite difference scheme on the Cartesian grid. Here, we show that their combination makes it possible to simulate the unsteady incompressible flow with curved boundary on a dynamically changed grid. The methods are validated by simulating steady and unsteady incompressible viscous flows over a stationary circular cylinder. [Copyright &y& Elsevier]

Abstract: Hawkins and Yin (Comput. Statist. Data Anal. 40 (2002) 253) describe an algorithm for ridge regression of reduced rank data, i.e.data where , the number of variables, is larger than , the number of observations. Whereas a direct implementation of ridge regression in this setting requires calculations of order , their algorithm uses only calculations of order . In this paper, we describe an alternative algorithm based on a factorization of the (transposed) design matrix. This approach is numerically more stable, further reduces the amount of calculations and needs less memory. In particular, we show that the factorization can be calculated in operations. Once the factorization is obtained, for any value of the ridge parameter the ridge regression estimator can be calculated in operations and the generalized cross-validation score in operations. [Copyright &y& Elsevier]

Abstract: In this paper we address the issue of designing optimal fuzzy interfaces, which are fundamental components of a fuzzy inference system. Due to the different roles of input and output interfaces, optimality conditions are analyzed separately for the two types of interface. We prove that input interfaces are optimal when based on a particular class of fuzzy sets called “bi-monotonic”, provided that mild conditions hold. The class of bi-monotonic fuzzy sets covers a broad range of fuzzy sets shapes, including convex fuzzy sets, so that the provided theoretical results can be applied to several fuzzy models. Such theoretical results are not applicable to output interfaces, for which a different optimality criterion is proposed. Such criterion leads to the definition of an optimality degree that measures the quality of a fuzzy output interface. Illustrative examples are presented to highlight the features of the proposed optimality degree in assessing the quality of output interfaces. [Copyright &y& Elsevier]

The paper presents a generic approach of approximating inference. The method is based on the concept of valuation algebras with its wide range of possible applications in many different domains. We present convenient resource-bounded anytime algorithms, where the maximal time of computation is determined by the user. [Copyright &y& Elsevier]

This paper describes a new approach, HIerarchical DEcision Rules (HIDER), for learning generalizable rules in continuous and discrete domains based on evolutionary algorithms. The main contributions of our approach are the integration of both binary and real evolutionary coding; the use of specific operators; the relaxing coefficient to construct more flexible classifiers by indicating how general, with respect to the errors, decision rules must be; the coverage factor in the fitness function, which makes possible a quick expansion of the rule size; and the implicit hierarchy when rules are being obtained. HIDER is accuracy-aware since it can control the maximum allowed error for each decision rule. We have tested our system on real data from the UCI Repository. The results of a 10-fold cross-validation are compared to C4.5’s and they show a significant improvement with respect to the number of rules and the error rate. [Copyright &y& Elsevier]

In this paper, an iteration algorithm based on interference iteration is proposed and referred to as I-PMF. Derived from the parametric matched filter (PMF), I-PMF has a low computational cost and reveals not only an iteration relationship between the autoregressive (AR) coefficient matrices and interferences in mathematics, but also a mechanism for PMF in suppressing interferences. Then the iteration of I-PMF is utilized in an adaptive method, namely I-PAMF. The average minimum output signal-to-interference-and-noise ratio (SINR) of I-PAMF is analyzed with separated interferences and verified by numerical results. It is shown that the computational cost of the proposed iterative algorithm, i.e. I-PMF, is low and the detection performance of the proposed adaptive iterative algorithm, i.e. I-PAMF, outperforms most of its counterparts with small training size. Although there might be a small loss of detection performance for I-PAMF compared with a few of its counterparts in some cases, I-PAMF still has a much lower computational cost than these counterparts. [ABSTRACT FROM AUTHOR]

A recent study conducted at Anhui University in China has proposed a new algorithm called the adaptive conjugate gradient accelerated evolutionary algorithm (ACG-EA) for optimizing cancer treatment plans in intensity-modulated proton therapy. This technique is considered one of the most advanced cancer treatment methods due to the unique characteristics of proton radiation. The ACG-EA algorithm aims to generate diverse high-quality treatment plans simultaneously, addressing the limitations of existing optimization methods. Experimental results have shown promising performance in six clinical cancer cases. This research has been peer-reviewed and published in the journal Applied Soft Computing. [Extracted from the article]

Researchers at the University of Science and Technology Beijing have developed a lightweight deep learning-based algorithm for segmenting bowel sounds (BS) in gastrointestinal monitoring. The algorithm utilizes one-dimensional convolution layers and bidirectional gate recurrent unit (GRU) layers to enhance feature extraction. A loss function called shape loss is proposed to reduce the sensitivity of the model to thresholds. Experimental results show that the proposed method outperforms other comparison methods in terms of f1-scores and sensitivity to thresholds. This research was supported by the National Natural Science Foundation of China. [Extracted from the article]

A report from the University Francisco of Vitoria in Madrid, Spain discusses the use of artificial intelligence (AI) in enhancing breast cancer diagnosis. The researchers evaluated different approaches using thermographic imaging and found that a hybrid model of convolutional neural networks and evolutionary algorithms achieved an accuracy of nearly 94%. The study highlights the potential benefits of computer vision and AI in medical diagnosis, particularly in the field of breast cancer screening. The research has been peer-reviewed and provides valuable insights into the application of AI in healthcare. [Extracted from the article]

Discusses algorithms for factoring large numbers. Use of computer networks to run algorithms quickly; Arithmetic used in factoring methods; Special-purpose factoring methods; General-purpose factoring methods.

A new algorithm is presented for finding all primes between 2 and n. The algorithm executes in time proportional to n (assuming that multiplication of integers not larger than n can be performed in unit time). The method has the same arithmetic complexity as the algorithm presented by Mairson [6]; however, our version is perhaps simpler and more elegant. It is also easily extended to find the prime factorization of all integers between 2 and n in time proportional to n. [ABSTRACT FROM AUTHOR]