Mathematical Biosciences and Engineering最新文献_第5页

Optimal vaccine allocation strategy: Theory and application to the early stage of COVID-19 in Japan. 最佳疫苗分配策略：日本 COVID-19 早期阶段的理论与应用。

IF 2.6 4区工程技术

Mathematical Biosciences and Engineering Pub Date : 2024-06-19 DOI: 10.3934/mbe.2024277

Toshikazu Kuniya, Taisuke Nakata, Daisuke Fujii

引用次数: 0

Research on MEC computing offload strategy for joint optimization of delay and energy consumption. 联合优化延迟和能耗的 MEC 计算卸载策略研究。

IF 2.6 4区工程技术

Mathematical Biosciences and Engineering Pub Date : 2024-06-17 DOI: 10.3934/mbe.2024276

Mingchang Ni, Guo Zhang, Qi Yang, Liqiong Yin

{"title":"Research on MEC computing offload strategy for joint optimization of delay and energy consumption.","authors":"Mingchang Ni, Guo Zhang, Qi Yang, Liqiong Yin","doi":"10.3934/mbe.2024276","DOIUrl":"https://doi.org/10.3934/mbe.2024276","url":null,"abstract":"The decision-making process for computational offloading is a critical aspect of mobile edge computing, and various offloading decision strategies are strongly linked to the calculated latency and energy consumption of the mobile edge computing system. This paper proposes an offloading scheme based on an enhanced sine-cosine optimization algorithm (SCAGA) designed for the \"edge-end\" architecture scenario within edge computing. The research presented in this paper covers the following aspects: (1) Establishment of computational resource allocation models and computational cost models for edge computing scenarios; (2) Introduction of an enhanced sine and cosine optimization algorithm built upon the principles of Levy flight strategy sine and cosine optimization algorithms, incorporating concepts from roulette wheel selection and gene mutation commonly found in genetic algorithms; (3) Execution of simulation experiments to evaluate the SCAGA-based offloading scheme, demonstrating its ability to effectively reduce system latency and optimize offloading utility. Comparative experiments also highlight improvements in system latency, mobile user energy consumption, and offloading utility when compared to alternative offloading schemes.","PeriodicalId":49870,"journal":{"name":"Mathematical Biosciences and Engineering","volume":null,"pages":null},"PeriodicalIF":2.6,"publicationDate":"2024-06-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142037552","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Hyperparameter optimization: Classics, acceleration, online, multi-objective, and tools. 超参数优化：经典、加速、在线、多目标和工具。

IF 2.6 4区工程技术

Mathematical Biosciences and Engineering Pub Date : 2024-06-14 DOI: 10.3934/mbe.2024275

Jia Mian Tan, Haoran Liao, Wei Liu, Changjun Fan, Jincai Huang, Zhong Liu, Junchi Yan

{"title":"Hyperparameter optimization: Classics, acceleration, online, multi-objective, and tools.","authors":"Jia Mian Tan, Haoran Liao, Wei Liu, Changjun Fan, Jincai Huang, Zhong Liu, Junchi Yan","doi":"10.3934/mbe.2024275","DOIUrl":"https://doi.org/10.3934/mbe.2024275","url":null,"abstract":"Hyperparameter optimization (HPO) has been well-developed and evolved into a well-established research topic over the decades. With the success and wide application of deep learning, HPO has garnered increased attention, particularly within the realm of machine learning model training and inference. The primary objective is to mitigate the challenges associated with manual hyperparameter tuning, which can be ad-hoc, reliant on human expertise, and consequently hinders reproducibility while inflating deployment costs. Recognizing the growing significance of HPO, this paper surveyed classical HPO methods, approaches for accelerating the optimization process, HPO in an online setting (dynamic algorithm configuration, DAC), and when there is more than one objective to optimize (multi-objective HPO). Acceleration strategies were categorized into multi-fidelity, bandit-based, and early stopping; DAC algorithms encompassed gradient-based, population-based, and reinforcement learning-based methods; multi-objective HPO can be approached via scalarization, metaheuristics, and model-based algorithms tailored for multi-objective situation. A tabulated overview of popular frameworks and tools for HPO was provided, catering to the interests of practitioners.","PeriodicalId":49870,"journal":{"name":"Mathematical Biosciences and Engineering","volume":null,"pages":null},"PeriodicalIF":2.6,"publicationDate":"2024-06-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142037544","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Analytic delay distributions for a family of gene transcription models. 基因转录模型系列的分析延迟分布。

IF 2.6 4区工程技术

Mathematical Biosciences and Engineering Pub Date : 2024-06-13 DOI: 10.3934/mbe.2024273

S Hossein Hosseini, Marc R Roussel

{"title":"Analytic delay distributions for a family of gene transcription models.","authors":"S Hossein Hosseini, Marc R Roussel","doi":"10.3934/mbe.2024273","DOIUrl":"https://doi.org/10.3934/mbe.2024273","url":null,"abstract":"Models intended to describe the time evolution of a gene network must somehow include transcription, the DNA-templated synthesis of RNA, and translation, the RNA-templated synthesis of proteins. In eukaryotes, the DNA template for transcription can be very long, often consisting of tens of thousands of nucleotides, and lengthy pauses may punctuate this process. Accordingly, transcription can last for many minutes, in some cases hours. There is a long history of introducing delays in gene expression models to take the transcription and translation times into account. Here we study a family of detailed transcription models that includes initiation, elongation, and termination reactions. We establish a framework for computing the distribution of transcription times, and work out these distributions for some typical cases. For elongation, a fixed delay is a good model provided elongation is fast compared to initiation and termination, and there are no sites where long pauses occur. The initiation and termination phases of the model then generate a nontrivial delay distribution, and elongation shifts this distribution by an amount corresponding to the elongation delay. When initiation and termination are relatively fast, the distribution of elongation times can be approximated by a Gaussian. A convolution of this Gaussian with the initiation and termination time distributions gives another analytic approximation to the transcription time distribution. If there are long pauses during elongation, because of the modularity of the family of models considered, the elongation phase can be partitioned into reactions generating a simple delay (elongation through regions where there are no long pauses), and reactions whose distribution of waiting times must be considered explicitly (initiation, termination, and motion through regions where long pauses are likely). In these cases, the distribution of transcription times again involves a nontrivial part and a shift due to fast elongation processes.","PeriodicalId":49870,"journal":{"name":"Mathematical Biosciences and Engineering","volume":null,"pages":null},"PeriodicalIF":2.6,"publicationDate":"2024-06-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142037542","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Feedback stabilization and observer design for sterile insect technique models. 昆虫不育技术模型的反馈稳定和观测器设计

IF 2.6 4区工程技术

Mathematical Biosciences and Engineering Pub Date : 2024-06-13 DOI: 10.3934/mbe.2024274

Kala Agbo Bidi

引用次数: 0

Image data augmentation techniques based on deep learning: A survey. 基于深度学习的图像数据增强技术：调查。

IF 2.6 4区工程技术

Mathematical Biosciences and Engineering Pub Date : 2024-06-12 DOI: 10.3934/mbe.2024272

Wu Zeng

{"title":"Image data augmentation techniques based on deep learning: A survey.","authors":"Wu Zeng","doi":"10.3934/mbe.2024272","DOIUrl":"https://doi.org/10.3934/mbe.2024272","url":null,"abstract":"In recent years, deep learning (DL) techniques have achieved remarkable success in various fields of computer vision. This progress was attributed to the vast amounts of data utilized to train these models, as they facilitated the learning of more intricate and detailed feature information about target objects, leading to improved model performance. However, in most real-world tasks, it was challenging to gather sufficient data for model training. Insufficient datasets often resulted in models prone to overfitting. To address this issue and enhance model performance, generalization ability, and mitigate overfitting in data-limited scenarios, image data augmentation methods have been proposed. These methods generated synthetic samples to augment the original dataset, emerging as a preferred strategy to boost model performance when data was scarce. This review first introduced commonly used and highly effective image data augmentation techniques, along with a detailed analysis of their advantages and disadvantages. Second, this review presented several datasets frequently employed for evaluating the performance of image data augmentation methods and examined how advanced augmentation techniques can enhance model performance. Third, this review discussed the applications and performance of data augmentation techniques in various computer vision domains. Finally, this review provided an outlook on potential future research directions for image data augmentation methods.","PeriodicalId":49870,"journal":{"name":"Mathematical Biosciences and Engineering","volume":null,"pages":null},"PeriodicalIF":2.6,"publicationDate":"2024-06-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142037545","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

An anti-impersonation attack electronic health record sharing scheme based on proxy re-encryption and blockchain. 基于代理重加密和区块链的防冒名攻击电子健康记录共享方案。

IF 2.6 4区工程技术

Mathematical Biosciences and Engineering Pub Date : 2024-06-03 DOI: 10.3934/mbe.2024271

Jiayuan Zhang, Rongxin Guo, Yifan Shi, Wanting Tang

{"title":"An anti-impersonation attack electronic health record sharing scheme based on proxy re-encryption and blockchain.","authors":"Jiayuan Zhang, Rongxin Guo, Yifan Shi, Wanting Tang","doi":"10.3934/mbe.2024271","DOIUrl":"https://doi.org/10.3934/mbe.2024271","url":null,"abstract":"Many current electronic medical record (EMR) sharing schemes that use proxy re-encryption and blockchain do not fully consider the potential threat of malicious node impersonation attacks. This oversight could lead to data leakage as attackers masquerade as legitimate users or proxy nodes during the sharing process. To deal with this problem, we propose an EMR sharing scheme based on proxy re-encryption and blockchain to protect against impersonation attacks. First, we prevent the potential threat of impersonation attacks by generating a shared temporary key and assigning tasks to multiple proxy nodes. Second, we use a random function to ensure that the selection of encrypted proxy nodes is fair. Third, we use a combination of blockchain and the InterPlanetary File System to solve the problem of insufficient storage capacity of shared processes and ensure the storage security of EMRs. Through the security proof, our scheme guarantees anti-impersonation, anti-collusion, and anti-chosen plaintext attack capability in the sharing process of EMRs. Additionally, experiments on the blockchain platform, namely Chain33, show that our scheme significantly increases efficiency.","PeriodicalId":49870,"journal":{"name":"Mathematical Biosciences and Engineering","volume":null,"pages":null},"PeriodicalIF":2.6,"publicationDate":"2024-06-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142037541","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Predicting the transmission trends of COVID-19: an interpretable machine learning approach based on daily, death, and imported cases. 预测 COVID-19 的传播趋势：基于日常病例、死亡病例和输入病例的可解释机器学习方法。

IF 2.6 4区工程技术

Mathematical Biosciences and Engineering Pub Date : 2024-06-03 DOI: 10.3934/mbe.2024270

Hyeonjeong Ahn, Hyojung Lee

{"title":"Predicting the transmission trends of COVID-19: an interpretable machine learning approach based on daily, death, and imported cases.","authors":"Hyeonjeong Ahn, Hyojung Lee","doi":"10.3934/mbe.2024270","DOIUrl":"https://doi.org/10.3934/mbe.2024270","url":null,"abstract":"COVID-19 is caused by the SARS-CoV-2 virus, which has produced variants and increasing concerns about a potential resurgence since the pandemic outbreak in 2019. Predicting infectious disease outbreaks is crucial for effective prevention and control. This study aims to predict the transmission patterns of COVID-19 using machine learning, such as support vector machine, random forest, and XGBoost, using confirmed cases, death cases, and imported cases, respectively. The study categorizes the transmission trends into the three groups: L0 (decrease), L1 (maintain), and L2 (increase). We develop the risk index function to quantify changes in the transmission trends, which is applied to the classification of machine learning. A high accuracy is achieved when estimating the transmission trends for the confirmed cases (91.5-95.5%), death cases (85.6-91.8%), and imported cases (77.7-89.4%). Notably, the confirmed cases exhibit a higher level of accuracy compared to the data on the deaths and imported cases. L2 predictions outperformed L0 and L1 in all cases. Predicting L2 is important because it can lead to new outbreaks. Thus, this robust L2 prediction is crucial for the timely implementation of control policies for the management of transmission dynamics.","PeriodicalId":49870,"journal":{"name":"Mathematical Biosciences and Engineering","volume":null,"pages":null},"PeriodicalIF":2.6,"publicationDate":"2024-06-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141318840","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

The switch point algorithm applied to a harvesting problem. 转换点算法应用于收割问题。

IF 2.6 4区工程技术

Mathematical Biosciences and Engineering Pub Date : 2024-05-30 DOI: 10.3934/mbe.2024269

Summer Atkins, William W Hager, Maia Martcheva

{"title":"The switch point algorithm applied to a harvesting problem.","authors":"Summer Atkins, William W Hager, Maia Martcheva","doi":"10.3934/mbe.2024269","DOIUrl":"https://doi.org/10.3934/mbe.2024269","url":null,"abstract":"In this paper, we investigate an optimal harvesting problem of a spatially explicit fishery model that was previously analyzed. On the surface, this problem looks innocent, but if parameters are set to where a singular arc occurs, two complex questions arise. The first question pertains to Fuller's phenomenon (or chattering), a phenomenon in which the optimal control possesses a singular arc that cannot be concatenated with the bang-bang arcs without prompting infinite oscillations over a finite region. 1) How do we numerically assess whether or not a problem chatters in cases when we cannot analytically prove such a phenomenon? The second question focuses on implementation of an optimal control. 2) When an optimal control has regions that are difficult to implement, how can we find alternative strategies that are both suboptimal and realistic to use? Although the former question does not apply to all optimal harvesting problems, most fishery managers should be concerned about the latter. Interestingly, for this specific problem, our techniques for answering the first question results in an answer to the the second. Our methods involve using an extended version of the switch point algorithm (SPA), which handles control problems having initial and terminal conditions on the states. In our numerical experiments, we obtain strong empirical evidence that the harvesting problem chatters, and we find three alternative harvesting strategies with fewer switches that are realistic to implement and near optimal.","PeriodicalId":49870,"journal":{"name":"Mathematical Biosciences and Engineering","volume":null,"pages":null},"PeriodicalIF":2.6,"publicationDate":"2024-05-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141318843","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Finite-time passivity of neutral-type complex-valued neural networks with time-varying delays. 具有时变延迟的中性复值神经网络的有限时间被动性。

IF 2.6 4区工程技术

Mathematical Biosciences and Engineering Pub Date : 2024-05-28 DOI: 10.3934/mbe.2024268

Haydar Akca, Chaouki Aouiti, Farid Touati, Changjin Xu

引用次数: 0