样式: 排序: IF: - GO 导出 标记为已读
-
A strategy for predicting waste production and planning recycling paths in e-logistics based on improved EMD-LSTM. Math. Biosci. Eng. (IF 2.6) Pub Date : 2023-09-14 Shujuan Liu,Hui Jin,Yanbiao Di
With the rapid development of e-commerce, express delivery has been chosen and accepted by consumers, and a large number of express packages have resulted in serious waste of resources and environmental pollution. Because of the irregularity of online goods purchases by users in real life, logistics parks are unable to accurately judge the recycling needs of various regions. In order to solve this
-
Adaptive rotation attention network for accurate defect detection on magnetic tile surface. Math. Biosci. Eng. (IF 2.6) Pub Date : 2023-09-13 Fang Luo,Yuan Cui,Xu Wang,Zhiliang Zhang,Yong Liao
Defect detection on magnetic tile surfaces is of great significance for the production monitoring of permanent magnet motors. However, it is challenging to detect the surface defects from the magnetic tile due to these issues: 1) Defects appear randomly on the surface of the magnetic tile; 2) the defects are tiny and often overwhelmed by the background. To address such problems, an Adaptive Rotation
-
Extension of probability models of the risk of infections by human enteric viruses. Math. Biosci. Eng. (IF 2.6) Pub Date : 2023-09-13 Costantino Masciopinto
This study presents a novel approach for obtaining reliable models and coefficients to estimate the probability of infection caused by common human enteric viruses. The aim is to provide guidance for public health policies in disease prevention and control, by reducing uncertainty and management costs in health risk assessments. Conventional dose-response (DR) models, based on the theory elaborated
-
Dynamics and optimal control of a stochastic Zika virus model with spatial diffusion. Math. Biosci. Eng. (IF 2.6) Pub Date : 2023-09-13 Minna Shao,Hongyong Zhao
Zika is an infectious disease with multiple transmission routes, which is related to severe congenital disabilities, especially microcephaly, and has attracted worldwide concern. This paper aims to study the dynamic behavior and optimal control of the disease. First, we establish a stochastic reaction-diffusion model (SRDM) for Zika virus, including human-mosquito transmission, human-human sexual transmission
-
Mathematical investigation of normal and abnormal wound healing dynamics: local and non-local models. Math. Biosci. Eng. (IF 2.6) Pub Date : 2023-09-12 O E Adebayo,S Urcun,G Rolin,S P A Bordas,D Trucu,R Eftimie
The movement of cells during (normal and abnormal) wound healing is the result of biomechanical interactions that combine cell responses with growth factors as well as cell-cell and cell-matrix interactions (adhesion and remodelling). It is known that cells can communicate and interact locally and non-locally with other cells inside the tissues through mechanical forces that act locally and at a distance
-
Point of Interest recommendation for social network using the Internet of Things and deep reinforcement learning. Math. Biosci. Eng. (IF 2.6) Pub Date : 2023-09-11 Shuguang Wang
Point of Interest (POI) recommendation is one of the important means for businesses to fully understand user preferences and meet their personalized needs, laying a solid foundation for the development of e-commerce and social networks. However, traditional social network POI recommendation algorithms suffer from various problems such as low accuracy and low recall. Therefore, a social network POI
-
An improved genetic algorithm with dynamic neighborhood search for job shop scheduling problem. Math. Biosci. Eng. (IF 2.6) Pub Date : 2023-09-11 Kongfu Hu,Lei Wang,Jingcao Cai,Long Cheng
The job shop scheduling problem (JSP) has consistently garnered significant attention. This paper introduces an improved genetic algorithm (IGA) with dynamic neighborhood search to tackle job shop scheduling problems with the objective of minimization the makespan. An inserted operation based on idle time is introduced during the decoding phase. An improved POX crossover operator is presented. A novel
-
SDS-Net: A lightweight 3D convolutional neural network with multi-branch attention for multimodal brain tumor accurate segmentation. Math. Biosci. Eng. (IF 2.6) Pub Date : 2023-09-11 Qian Wu,Yuyao Pei,Zihao Cheng,Xiaopeng Hu,Changqing Wang
The accurate and fast segmentation method of tumor regions in brain Magnetic Resonance Imaging (MRI) is significant for clinical diagnosis, treatment and monitoring, given the aggressive and high mortality rate of brain tumors. However, due to the limitation of computational complexity, convolutional neural networks (CNNs) face challenges in being efficiently deployed on resource-limited devices, which
-
A double association-based evolutionary algorithm for many-objective optimization. Math. Biosci. Eng. (IF 2.6) Pub Date : 2023-09-08 Junhua Liu,Wei Zhang,Mengnan Tian,Hong Ji,Baobao Liu
In this paper, a double association-based evolutionary algorithm (denoted as DAEA) is proposed to solve many-objective optimization problems. In the proposed DAEA, a double association strategy is designed to associate solutions with each subspace. Different from the existing association methods, the double association strategy takes the empty subspace into account and associates it with a promising
-
A global optimization generation method of stitching dental panorama with anti-perspective transformation. Math. Biosci. Eng. (IF 2.6) Pub Date : 2023-09-08 Ning He,Hongmei Jin,Hong'an Li,Zhanli Li
To address the limitation of narrow field-of-view in local oral cavity images that fail to capture large-area targets at once, this paper designs a method for generating natural dental panoramas based on oral endoscopic imaging that consists of two main stages: the anti-perspective transformation feature extraction and the coarse-to-fine global optimization matching. In the first stage, we increase
-
Distributed convex optimization of bipartite containment control for high-order nonlinear uncertain multi-agent systems with state constraints. Math. Biosci. Eng. (IF 2.6) Pub Date : 2023-09-07 Yuhang Yao,Jiaxin Yuan,Tao Chen,Xiaole Yang,Hui Yang
This article investigates a penalty-based distributed optimization algorithm of bipartite containment control for high-order nonlinear uncertain multi-agent systems with state constraints. The proposed method addresses the distributed optimization problem by designing a penalty function in the form of a quadratic function, which is the sum of the global objective function and the consensus constraint
-
QSPR/QSAR analysis of some eccentricity based topological descriptors of antiviral drugs used in COVID-19 treatment via $ \mathscr{D}\varepsilon $- polynomials. Math. Biosci. Eng. (IF 2.6) Pub Date : 2023-09-05 Deepalakshmi Sarkarai,Kalyani Desikan
In the field of chemical and medical sciences, topological indices are used to study the chemical, biological, clinical, and therapeutic aspects of pharmaceuticals. The COVID-19 pandemic is largely recognized as the most life-threatening crisis confronting medical advances. Scientists have tested various antiviral drugs and discovered that they help people recover from viral infections like COVID-19
-
A chaos-based adaptive equilibrium optimizer algorithm for solving global optimization problems. Math. Biosci. Eng. (IF 2.6) Pub Date : 2023-09-04 Yuting Liu,Hongwei Ding,Zongshan Wang,Gushen Jin,Bo Li,Zhijun Yang,Gaurav Dhiman
The equilibrium optimizer (EO) algorithm is a newly developed physics-based optimization algorithm, which inspired by a mixed dynamic mass balance equation on a controlled fixed volume. The EO algorithm has a number of strengths, such as simple structure, easy implementation, few parameters and its effectiveness has been demonstrated on numerical optimization problems. However, the canonical EO still
-
Research on multi-strategy improved sparrow search optimization algorithm. Math. Biosci. Eng. (IF 2.6) Pub Date : 2023-09-04 Teng Fei,Hongjun Wang,Lanxue Liu,Liyi Zhang,Kangle Wu,Jianing Guo
To address the issues with inadequate search space, sluggish convergence and easy fall into local optimality during iteration of the sparrow search algorithm (SSA), a multi-strategy improved sparrow search algorithm (ISSA), is developed. First, the population dynamic adjustment strategy is carried out to restrict the amount of sparrow population discoverers and joiners. Second, the update strategy
-
Column storage enables edge computation of biological big data on 5G networks. Math. Biosci. Eng. (IF 2.6) Pub Date : 2023-09-04 Miaoshan Lu,Junjie Tong,Weidong Fang,Jinyin Wang,Shaowei An,Ruimin Wang,Hengxuan Jiang,Changbin Yu
With the continuous improvement of biological detection technology, the scale of biological data is also increasing, which overloads the central-computing server. The use of edge computing in 5G networks can provide higher processing performance for large biological data analysis, reduce bandwidth consumption and improve data security. Appropriate data compression and reading strategy becomes the key
-
Improved graph neural network-based green anaconda optimization for segmenting and classifying the lung cancer. Math. Biosci. Eng. (IF 2.6) Pub Date : 2023-09-04 S Dinesh Krishnan,Danilo Pelusi,A Daniel,V Suresh,Balamurugan Balusamy
Normal lung cells incur genetic damage over time, which causes unchecked cell growth and ultimately leads to lung cancer. Nearly 85% of lung cancer cases are caused by smoking, but there exists factual evidence that beta-carotene supplements and arsenic in water may raise the risk of developing the illness. Asbestos, polycyclic aromatic hydrocarbons, arsenic, radon gas, nickel, chromium and hereditary
-
Nash equilibrium realization of population games based on social learning processes. Math. Biosci. Eng. (IF 2.6) Pub Date : 2023-09-04 Zhiyan Xing,Yanlong Yang,Zuopeng Hu
In the two-population game model, we assume the players have certain imitative learning abilities. To simulate the learning process of the game players, we propose a new swarm intelligence algorithm by combining the particle swarm optimization algorithm, where each player can be considered a particle. We conduct simulations for three typical games: the prisoner's dilemma game (with only one pure-strategy
-
Open interoperability model for Society 5.0's infrastructure and services. Math. Biosci. Eng. (IF 2.6) Pub Date : 2023-08-31 Roman Gumzej,Bojan Rosi
As the Internet of Things (IoT) is considered the foundation of digital transformation in everyday life, the Industrial IoT (IIoT) is considered its business counterpart. Together with the Physical Internet (PhI), they represent the foundation of smart production and logistics as part of the new digitized Society 5.0. Smart grids of different kinds with applications, ranging from power distribution
-
Glucose trend prediction model based on improved wavelet transform and gated recurrent unit. Math. Biosci. Eng. (IF 2.6) Pub Date : 2023-08-29 Tao Yang,Qicheng Yang,Yibo Zhou,Chuanbiao Wen
Glucose trend prediction based on continuous glucose monitoring (CGM) data is a crucial step in the implementation of an artificial pancreas (AP). A glucose trend prediction model with high accuracy in real-time can greatly improve the glycemic control effect of the artificial pancreas and effectively prevent the occurrence of hyperglycemia and hypoglycemia. In this paper, we propose an improved wavelet
-
A convolutional neural network-based decision support system for neonatal quiet sleep detection. Math. Biosci. Eng. (IF 2.6) Pub Date : 2023-08-29 Saadullah Farooq Abbasi,Qammer Hussain Abbasi,Faisal Saeed,Norah Saleh Alghamdi
Sleep plays an important role in neonatal brain and physical development, making its detection and characterization important for assessing early-stage development. In this study, we propose an automatic and computationally efficient algorithm to detect neonatal quiet sleep (QS) using a convolutional neural network (CNN). Our study used 38-hours of electroencephalography (EEG) recordings, collected
-
State-of-the-art survey of in-vehicle protocols and automotive Ethernet security and vulnerabilities. Math. Biosci. Eng. (IF 2.6) Pub Date : 2023-08-29 Aida Ben Chehida Douss,Ryma Abassi,Damien Sauveron
With the help of advanced technology, the automotive industry is in continuous evolution. Modern vehicles are not only comprised of mechanical components but also contain highly complex electronic devices and connections to the outside world. Today's vehicle usually has between 30 and 70 ECUs (Electronic Control Units), which communicate with each other over standard communication protocols. There
-
Dynamics analysis of an SVEIR epidemic model in a patchy environment. Math. Biosci. Eng. (IF 2.6) Pub Date : 2023-08-28 Maoxing Liu,Yuhang Li
In this paper, we propose a multi-patch SVEIR epidemic model that incorporates vaccination of both newborns and susceptible populations. We determine the basic reproduction number $ R_{0} $ and prove that the disease-free equilibrium $ P_{0} $ is locally and globally asymptotically stable if $ R_{0} < 1, $ and it is unstable if $ R_{0} > 1. $ Moreover, we show that the disease is uniformly persistent
-
Finite-time contraction stability of a stochastic reaction-diffusion dengue model with impulse and Markov switching. Math. Biosci. Eng. (IF 2.6) Pub Date : 2023-08-28 Wei You,Jie Ren,Qimin Zhang
From the perspective of prevention and treatment of dengue, it is important to minimize the number of infections within a limited time frame. That is, the study of finite time contraction stability (FTCS) of dengue system is a meaningful topic. This article proposes a dengue epidemic model with reaction-diffusion, impulse and Markov switching. By constructing an equivalent system, the well-posedness
-
Evaluation on sustainable development of fire safety management policies in smart cities based on big data. Math. Biosci. Eng. (IF 2.6) Pub Date : 2023-08-28 Xiaodong Qian
The fire safety management policy is the premise for city managers to master the urban fire safety situation and solve the urban fire safety problems. An excellent fire safety management policy can obtain the basic data of fire safety, analyze the existing problems and potential safety hazards, and provide targeted measures for urban fire safety management. At present, the traditional fire safety management
-
Dynamics study of nonlinear discrete predator-prey system with Michaelis-Menten type harvesting. Math. Biosci. Eng. (IF 2.6) Pub Date : 2023-08-25 Xiaoling Han,Xiongxiong Du
In this paper, we study a discrete predator-prey system with Michaelis-Menten type harvesting. First, the equilibrium points number, local stability and boundedness of the system are discussed. Second, using the bifurcation theory and the center manifold theorem, the bifurcation conditions for the system to go through flip bifurcation and Neimark-Sacker bifurcation at the interior equilibrium point
-
Pedestrian re-identification based on attention mechanism and Multi-scale feature fusion. Math. Biosci. Eng. (IF 2.6) Pub Date : 2023-08-25 Songlin Liu,Shouming Zhang,Zijian Diao,Zhenbin Fang,Zeyu Jiao,Zhenyu Zhong
Existing pedestrian re-identification models generally have low pedestrian retrieval accuracy when encountering factors such as changes in pedestrian posture and occlusion because the network cannot fully express pedestrian feature information. Therefore, this paper proposes a method to address this problem by combining the attention mechanism with multi-scale feature fusion, and combining the proposed
-
Study on the evolutionary strategy of upward patient transfer in the loose medical consortia. Math. Biosci. Eng. (IF 2.6) Pub Date : 2023-08-24 Jialing Li,Guiju Zhu,Xinya Hu,Ruqian Fei,Dan Yu,Dong Wang
Medical institutions in loose medical consortia tend to have poor cooperation due to fragmented interests. We aim to explore any issues associated with patient upward transfer in a loose medical consortium system consisting of two tertiary hospitals with both cooperative and competitive relationships. A two-sided evolutionary game model was constructed to assess the stability of equilibrium strategy
-
Advancing remote consultation through the integration of blockchain and ant colony algorithm. Math. Biosci. Eng. (IF 2.6) Pub Date : 2023-08-24 Xiang Gao,Yipeng Zhang
To guide the more reasonable and fair allocation of medical resources, to solve the problem of fee prices negotiated by various subjects in the medical and health system and patient payment, and to solve the problem of how to ensure the privacy, accuracy, consistency and traceability of data in the process of collecting patient information in each hospital, according to the operation process of a remote
-
Modeling and analyzing an opinion network dynamics considering the environmental factor. Math. Biosci. Eng. (IF 2.6) Pub Date : 2023-08-24 Fulian Yin,Jinxia Wang,Xinyi Jiang,Yanjing Huang,Qianyi Yang,Jianhong Wu
With the development of Internet technology, social media has gradually become an important platform where users can express opinions about hot events. Research on the mechanism of public opinion evolution is beneficial to guide the trend of opinions, making users' opinions change in a positive direction or reach a consensus among controversial crowds. To design effective strategies for public opinion
-
Automated tumor segmentation in thermographic breast images. Math. Biosci. Eng. (IF 2.6) Pub Date : 2023-08-23 Thaweesak Trongtirakul,Sos Agaian,Adel Oulefki
Identifying and delineating suspicious regions in thermal breast images poses significant challenges for radiologists during the examination and interpretation of thermogram images. This paper aims to tackle concerns related to enhancing the differentiation between cancerous regions and the background to achieve uniformity in the intensity of breast cancer's (BC) existence. Furthermore, it aims to
-
Neural-SEIR: A flexible data-driven framework for precise prediction of epidemic disease. Math. Biosci. Eng. (IF 2.6) Pub Date : 2023-08-23 Haoyu Wang,Xihe Qiu,Jinghan Yang,Qiong Li,Xiaoyu Tan,Jingjing Huang
Accurately modeling and predicting epidemic diseases is crucial to prevent disease transmission and reduce mortality. Due to various unpredictable factors, including population migration, vaccination, control efforts, and seasonal fluctuations, traditional epidemic models that rely on prior knowledge of virus transmission mechanisms may not be sufficient to forecast complex epidemics like coronavirus
-
Spatiotemporal retrieval and feature analysis of air pollution episodes. Math. Biosci. Eng. (IF 2.6) Pub Date : 2023-08-23 Peng-Yeng Yin
Air pollution has inevitably come along with the economic development of human society. How to balance economic growth with a sustainable environment has been a global concern. The ambient PM2.5 (particulate matter with aerodynamic diameter ≤ 2.5 μm) is particularly life-threatening because these tiny aerosols could be inhaled into the human respiration system and cause millions of premature deaths
-
UNet segmentation network of COVID-19 CT images with multi-scale attention. Math. Biosci. Eng. (IF 2.6) Pub Date : 2023-08-23 Mingju Chen,Sihang Yi,Mei Yang,Zhiwen Yang,Xingyue Zhang
In recent years, the global outbreak of COVID-19 has posed an extremely serious life-safety risk to humans, and in order to maximize the diagnostic efficiency of physicians, it is extremely valuable to investigate the methods of lesion segmentation in images of COVID-19. Aiming at the problems of existing deep learning models, such as low segmentation accuracy, poor model generalization performance
-
AGMG-Net: Leveraging multiscale and fine-grained features for improved cargo recognition. Math. Biosci. Eng. (IF 2.6) Pub Date : 2023-08-23 Aigou Li,Chen Yang
Security systems place great emphasis on the safety of stored cargo, as any loss or tampering can result in significant economic damage. The cargo identification module within the security system faces the challenge of achieving a 99.99% recognition accuracy. However, current identification methods are limited in accuracy due to the lack of cargo data, insufficient utilization of image features and
-
Visualization design of health detection products based on human-computer interaction experience in intelligent decision support systems. Math. Biosci. Eng. (IF 2.6) Pub Date : 2023-08-22 Yinhua Su
In order to meet the needs of the human-computer interaction experience of health testing products and improve the decision-making efficiency of intelligent decision support systems, we visualized the design of health testing products. We summarized the design methods for the human-computer interaction experience of health testing products, analyzed health testing data visualization requirements in
-
Two-level QR code scheme based on region matrix image secret sharing algorithm. Math. Biosci. Eng. (IF 2.6) Pub Date : 2023-08-21 Li-Na Zhang,Jia-Qi Sun,Xiao-Yu Zhang,Qing-Peng Chen,Jing Zhang
Quick response (QR) codes have become increasingly popular as a medium for quickly and easily accessing information through mobile devices. However, the open-source nature of QR code encoding poses a risk of information leakage and potential attacks, especially with the growing use of QR codes in financial services and authentication applications. To mitigate the risk of information leakage due to
-
Event-triggered integral sliding mode control for uncertain networked linear control systems with quantization. Math. Biosci. Eng. (IF 2.6) Pub Date : 2023-08-21 Xinggui Zhao,Bo Meng,Zhen Wang
In this paper, the integral sliding mode (ISM, SM) controller is designed to address the problem of implementing non-periodic sampled data for a class of networked linear systems with matched and unmatched uncertainties. Due to the redesigned gain of the nominal controller, the feedback control used by the nominal controller guarantees the asymptotic stability of the uncertain networked linear system
-
Dynamical analysis of the effects of circadian clock on the neurotransmitter dopamine. Math. Biosci. Eng. (IF 2.6) Pub Date : 2023-08-21 Ying Li,Zhao Zhao,Yuan-Yuan Tan,Xue Wang
The circadian clock is an autonomous timing system that regulates the physiological and behavioral activities of organisms. Dopamine (DA) is an important neurotransmitter that is associated with many biological activities such as mood and movement. Experimental studies have shown that the circadian clock influences the DA system and disorders in the circadian clock lead to DA-related diseases. However
-
Identification of image genetic biomarkers of Alzheimer's disease by orthogonal structured sparse canonical correlation analysis based on a diagnostic information fusion. Math. Biosci. Eng. (IF 2.6) Pub Date : 2023-08-18 Wei Yin,Tao Yang,GuangYu Wan,Xiong Zhou
Alzheimer's disease (AD) is an irreversible neurodegenerative disease, and its incidence increases yearly. Because AD patients will have cognitive impairment and personality changes, it has caused a heavy burden on the family and society. Image genetics takes the structure and function of the brain as a phenotype and studies the influence of genetic variation on the structure and function of the brain
-
A mathematical model between keystone species: Bears, salmon and vegetation. Math. Biosci. Eng. (IF 2.6) Pub Date : 2023-08-18 Christopher Middlebrook,Xiaoying Wang
We study an ecosystem of three keystone species: salmon, bears and vegetation. Bears consume salmon and vegetation for energy and nutrient intake, but the food quality differs significantly due to the nutritional level difference between salmon and vegetation. We propose a stoichiometric predator-prey model that not only tracks the energy flow from one trophic level to another but also nutrient recycling
-
Investigating difficulties and enhancing understanding in linear algebra: Leveraging SageMath and ChatGPT for (orthogonal) diagonalization and singular value decomposition. Math. Biosci. Eng. (IF 2.6) Pub Date : 2023-08-17 Natanael Karjanto
We explored some common challenges faced by undergraduate students when studying linear algebra, particularly when dealing with algorithmic thinking skills required for topics such as matrix factorization, focusing on (orthogonal) diagonalization and singular value decomposition (SVD). To address these challenges, we introduced SageMath, a Python-based open-source computer algebra system, as a supportive
-
Deep belief improved bidirectional LSTM for multivariate time series forecasting. Math. Biosci. Eng. (IF 2.6) Pub Date : 2023-08-17 Keruo Jiang,Zhen Huang,Xinyan Zhou,Chudong Tong,Minjie Zhu,Heshan Wang
Multivariate time series (MTS) play essential roles in daily life because most real-world time series datasets are multivariate and rich in time-dependent information. Traditional forecasting methods for MTS are time-consuming and filled with complicated limitations. One efficient method being explored within the dynamical systems is the extended short-term memory networks (LSTMs). However, existing
-
FastCAT: A framework for fast routing table calculation incorporating multiple protocols. Math. Biosci. Eng. (IF 2.6) Pub Date : 2023-08-17 Jianfei Cai,Guozheng Yang,Jingju Liu,Yi Xie
Currently, most network outages occur because of manual configuration errors. Therefore, it is essential to verify the correctness of network configurations before deployment. Computing the network control plane is a key technology for network configuration verification. We can verify the correctness of network configurations for fault tolerance by generating routing tables, as well as connectivity
-
Free boundary problem for a nonlocal time-periodic diffusive competition model. Math. Biosci. Eng. (IF 2.6) Pub Date : 2023-08-16 Qiaoling Chen,Fengquan Li,Sanyi Tang,Feng Wang
In this paper we consider a free boundary problem for a nonlocal time-periodic competition model. One species is assumed to adopt nonlocal dispersal, and the other one adopts mixed dispersal, which is a combination of both random dispersal and nonlocal dispersal. We first prove the global well-posedness of solutions to the free boundary problem with more general growth functions, and then discuss the
-
An eco-epidemic model for assessing the application of integrated pest management strategies. Math. Biosci. Eng. (IF 2.6) Pub Date : 2023-08-16 Wenjie Qin,Yue Xia,Yi Yang
Mathematical models have become indispensable tools for analyzing pest control strategies. However, in the realm of pest control studies, the consideration of a plant population being affected by a model that incorporates pests, natural enemies and disease in the pest population has been relatively limited. Therefore, this paper aims to formulate and investigate a hybrid impulsive eco-epidemic model
-
Does supply chain finance business model innovation improve capital allocation efficiency? Evidence from the cost of capital. Math. Biosci. Eng. (IF 2.6) Pub Date : 2023-08-15 Ping Wang,Rui Chen,Qiqing Huang
Based on the sample of China's A-share listed companies from 2008 to 2021 and the text analysis data of supply chain finance, this study examines whether the supply chain finance business model innovation can improve the efficiency of capital allocation. Results showed that: 1) Firms with a supply chain finance business model have a low cost of capital, particularly the cost of equity capital; 2) The
-
Recommendation model based on intention decomposition and heterogeneous information fusion. Math. Biosci. Eng. (IF 2.6) Pub Date : 2023-08-15 Suqi Zhang,Xinxin Wang,Wenfeng Wang,Ningjing Zhang,Yunhao Fang,Jianxin Li
In order to solve the problem of timeliness of user and item interaction intention and the noise caused by heterogeneous information fusion, a recommendation model based on intention decomposition and heterogeneous information fusion (IDHIF) is proposed. First, the intention of the recently interacting items and the users of the recently interacting candidate items is decomposed, and the short feature
-
Design of an automatic landscape design system in smart cities based on vision computing. Math. Biosci. Eng. (IF 2.6) Pub Date : 2023-08-14 Wei Wu,Shicheng Luo,Hongying Wang
In future smart cities, automatic landscape design can be viewed as a promising intelligent application to reduce the reliance on expert labors. As it is a kind of visual sensing activity, it is expected to develop a robust interaction platform with strong ability of visual information fusion. To deal with this issue, this paper integrates vision computing, and designs an automatic landscape design
-
Cell segmentation in fluorescence microscopy images based on multi-scale histogram thresholding. Math. Biosci. Eng. (IF 2.6) Pub Date : 2023-08-14 Yating Fang,Baojiang Zhong
Cell segmentation from fluorescent microscopy images plays an important role in various applications, such as disease mechanism assessment and drug discovery research. Exiting segmentation methods often adopt image binarization as the first step, through which the foreground cell is separated from the background so that the subsequent processing steps can be greatly facilitated. To pursue this goal
-
MUNIX repeatability evaluation method based on FastICA demixing. Math. Biosci. Eng. (IF 2.6) Pub Date : 2023-08-14 Suqi Xue,Farong Gao,Xudong Wu,Qun Xu,Xuecheng Weng,Qizhong Zhang
To enhance the reproducibility of motor unit number index (MUNIX) for evaluating neurological disease progression, this paper proposes a negative entropy-based fast independent component analysis (FastICA) demixing method to assess MUNIX reproducibility in the presence of inter-channel mixing of electromyography (EMG) signals acquired by high-density electrodes. First, composite surface EMG (sEMG)
-
Application of an improved whale optimization algorithm in time-optimal trajectory planning for manipulators. Math. Biosci. Eng. (IF 2.6) Pub Date : 2023-08-14 Juan Du,Jie Hou,Heyang Wang,Zhi Chen
To address the issues of unstable, non-uniform and inefficient motion trajectories in traditional manipulator systems, this paper proposes an improved whale optimization algorithm for time-optimal trajectory planning. First, an inertia weight factor is introduced into the surrounding prey and bubble-net attack formulas of the whale optimization algorithm. The value is controlled using reinforcement
-
SEINN: A deep learning algorithm for the stochastic epidemic model. Math. Biosci. Eng. (IF 2.6) Pub Date : 2023-08-14 Thomas Torku,Abdul Khaliq,Fathalla Rihan
Stochastic modeling predicts various outcomes from stochasticity in the data, parameters and dynamical system. Stochastic models are deemed more appropriate than deterministic models accounting in terms of essential and practical information about a system. The objective of the current investigation is to address the issue above through the development of a novel deep neural network referred to as
-
Research on integrated inventory transportation optimization of inbound logistics via a VMI-TPL model of an existing enterprise. Math. Biosci. Eng. (IF 2.6) Pub Date : 2023-08-14 Kun Zhang,Hanping Hou,Zhiqiang Dong,Ziheng Liu
Third-party logistics companies face a challenging task in minimizing inventory transportation costs due to the complexities of managing numerous suppliers. Effectively optimizing costs becomes a formidable problem for such companies. This empirical research has yielded strategies for minimizing the inventory transportation cost specifically for company D. Through a rigorous optimization process, the
-
Research on robust fuzzy logic sliding mode control of Two-DOF intelligent underwater manipulators. Math. Biosci. Eng. (IF 2.6) Pub Date : 2023-08-14 Kangsen Huang,Zimin Wang
This study investigates the independent motion control of a two-degree-of-freedom (Two-DOF) intelligent underwater manipulator. The dynamics model of two-DOF manipulators in an underwater environment is proposed by combining Lagrange's equation and Morison's empirical formulation. Disturbing factors such as water resistance moments, additional mass force moments and buoyancy forces on the intelligent
-
Developing a Deep Neural Network model for COVID-19 diagnosis based on CT scan images. Math. Biosci. Eng. (IF 2.6) Pub Date : 2023-08-14 Javad Hassannataj Joloudari,Faezeh Azizi,Issa Nodehi,Mohammad Ali Nematollahi,Fateme Kamrannejhad,Edris Hassannatajjeloudari,Roohallah Alizadehsani,Sheikh Mohammed Shariful Islam
COVID-19 is most commonly diagnosed using a testing kit but chest X-rays and computed tomography (CT) scan images have a potential role in COVID-19 diagnosis. Currently, CT diagnosis systems based on Artificial intelligence (AI) models have been used in some countries. Previous research studies used complex neural networks, which led to difficulty in network training and high computation rates. Hence
-
Using Bayesian networks with tabu algorithm to explore factors related to chronic kidney disease with mental illness: A cross-sectional study. Math. Biosci. Eng. (IF 2.6) Pub Date : 2023-08-10 Xiaoli Yuan,Wenzhu Song,Yaheng Li,Qili Wang,Jianbo Qing,Wenqiang Zhi,Huimin Han,Zhiqi Qin,Hao Gong,Guohua Hou,Yafeng Li
While Bayesian networks (BNs) offer a promising approach to discussing factors related to many diseases, little attention has been poured into chronic kidney disease with mental illness (KDMI) using BNs. This study aimed to explore the complex network relationships between KDMI and its related factors and to apply Bayesian reasoning for KDMI, providing a scientific reference for its prevention and
-
The effect of screening on the health burden of chlamydia: An evaluation of compartmental models based on person-days of infection. Math. Biosci. Eng. (IF 2.6) Pub Date : 2023-08-09 Jack Farrell,Owen Spolyar,Scott Greenhalgh
Sexually transmitted diseases (STDs) are detrimental to the health and economic well-being of society. Consequently, predicting outbreaks and identifying effective disease interventions through epidemiological tools, such as compartmental models, is of the utmost importance. Unfortunately, the ordinary differential equation compartmental models attributed to the work of Kermack and McKendrick require
-
Developing trust among players in a vendor-managed inventory model for random demand under environmental impact. Math. Biosci. Eng. (IF 2.6) Pub Date : 2023-08-09 Sharmila Saren,Rekha Guchhait,Ali AlArjani,Biswajit Sarkar
Retailers play a vital role in supply chain management because they deal directly with consumers. Occasionally, retailers may cover the entire system's statistics and not disclose these data to the manufacturer. Therefore, asymmetry is generated in the data throughout the system. The main motive of this research was to prevent unreliability throughout the system using a vendor-managed inventory policy
-
Aerial images object detection method based on cross-scale multi-feature fusion. Math. Biosci. Eng. (IF 2.6) Pub Date : 2023-08-09 Yang Pan,Jinhua Yang,Lei Zhu,Lina Yao,Bo Zhang
Aerial image target detection technology has essential application value in navigation security, traffic control and environmental monitoring. Compared with natural scene images, the background of aerial images is more complex, and there are more small targets, which puts higher requirements on the detection accuracy and real-time performance of the algorithm. To further improve the detection accuracy
-
Synergistic effects of vaccination and virus testing on the transmission of an infectious disease. Math. Biosci. Eng. (IF 2.6) Pub Date : 2023-08-08 Lili Han,Mingfeng He,Xiao He,Qiuhui Pan
Under the background that asymptomatic virus carriers have infectivity for an infectious disease, we establish a difference equations model with vaccination and virus testing in this paper. Assuming that the vaccine is 100% effective for susceptible people but cannot stop the infectivity of asymptomatic virus carriers, we study how to combine vaccination and virus testing at the beginning of an epidemic