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EfficientNet Ensemble Learning: Identifying Ethiopian Medicinal Plant Species and Traditional Uses by Integrating Modern Technology with Ethnobotanical Wisdom 高效网络集合学习:通过现代技术与人种植物学智慧的结合识别埃塞俄比亚药用植物物种和传统用途
Pub Date : 2024-01-29 DOI: 10.3390/computers13020038
Mulugeta Adibaru Kiflie, D. Sharma, Mesfin Abebe Haile, Ramasamy Srinivasagan
Ethiopia is renowned for its rich biodiversity, supporting a diverse variety of medicinal plants with significant potential for therapeutic applications. In regions where modern healthcare facilities are scarce, traditional medicine emerges as a cost-effective and culturally aligned primary healthcare solution in developing countries. In Ethiopia, the majority of the population, around 80%, and for a significant proportion of their livestock, approximately 90% continue to prefer traditional medicine as their primary healthcare option. Nevertheless, the precise identification of specific plant parts and their associated uses has posed a formidable challenge due to the intricate nature of traditional healing practices. To address this challenge, we employed a majority based ensemble deep learning approach to identify medicinal plant parts and uses of Ethiopian indigenous medicinal plant species. The primary objective of this research is to achieve the precise identification of the parts and uses of Ethiopian medicinal plant species. To design our proposed model, EfficientNetB0, EfficientNetB2, and EfficientNetB4 were used as benchmark models and applied as a majority vote-based ensemble technique. This research underscores the potential of ensemble deep learning and transfer learning methodologies to accurately identify the parts and uses of Ethiopian indigenous medicinal plant species. Notably, our proposed EfficientNet-based ensemble deep learning approach demonstrated remarkable accuracy, achieving a significant test and validation accuracy of 99.96%. Future endeavors will prioritize expanding the dataset, refining feature-extraction techniques, and creating user-friendly interfaces to overcome current dataset limitations.
埃塞俄比亚以其丰富的生物多样性而闻名于世,这里的药用植物种类繁多,具有巨大的治疗潜力。在现代医疗设施匮乏的地区,传统医学成为发展中国家一种具有成本效益且符合当地文化的初级医疗解决方案。在埃塞俄比亚,约 80% 的人口以及约 90% 的牲畜仍然选择传统医药作为主要的医疗保健手段。然而,由于传统疗法的复杂性,精确识别特定植物成分及其相关用途一直是一项艰巨的挑战。为了应对这一挑战,我们采用了一种基于多数的集合深度学习方法来识别埃塞俄比亚本土药用植物的药用部位和用途。本研究的主要目标是精确识别埃塞俄比亚药用植物物种的部位和用途。为了设计我们提出的模型,我们使用了 EfficientNetB0、EfficientNetB2 和 EfficientNetB4 作为基准模型,并应用了基于多数票的集合技术。这项研究强调了集合深度学习和迁移学习方法在准确识别埃塞俄比亚本土药用植物物种的部位和用途方面的潜力。值得注意的是,我们提出的基于 EfficientNet 的集合深度学习方法表现出了卓越的准确性,测试和验证准确率高达 99.96%。未来的工作将优先考虑扩大数据集、完善特征提取技术和创建用户友好界面,以克服当前数据集的局限性。
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引用次数: 0
Improved Recognition of Kurdish Sign Language Using Modified CNN 使用改进型 CNN 提高库尔德手语识别率
Pub Date : 2024-01-28 DOI: 10.3390/computers13020037
Karwan M. Hama Rawf, A. O. Abdulrahman, A. Mohammed
The deaf society supports Sign Language Recognition (SLR) since it is used to educate individuals in communication, education, and socialization. In this study, the results of using the modified Convolutional Neural Network (CNN) technique to develop a model for real-time Kurdish sign recognition are presented. Recognizing the Kurdish alphabet is the primary focus of this investigation. Using a variety of activation functions over several iterations, the model was trained and then used to make predictions on the KuSL2023 dataset. There are a total of 71,400 pictures in the dataset, drawn from two separate sources, representing the 34 sign languages and alphabets used by the Kurds. A large collection of real user images is used to evaluate the accuracy of the suggested strategy. A novel Kurdish Sign Language (KuSL) model for classification is presented in this research. Furthermore, the hand region must be identified in a picture with a complex backdrop, including lighting, ambience, and image color changes of varying intensities. Using a genuine public dataset, real-time classification, and personal independence while maintaining high classification accuracy, the proposed technique is an improvement over previous research on KuSL detection. The collected findings demonstrate that the performance of the proposed system offers improvements, with an average training accuracy of 99.05% for both classification and prediction models. Compared to earlier research on KuSL, these outcomes indicate very strong performance.
聋人社会支持手语识别(SLR),因为它可用于个人交流、教育和社交教育。本研究介绍了使用改进的卷积神经网络(CNN)技术开发库尔德手语实时识别模型的结果。识别库尔德字母是本研究的主要重点。通过多次迭代使用各种激活函数对模型进行了训练,然后用于对 KuSL2023 数据集进行预测。该数据集中共有 7.14 万张图片,分别来自两个不同的来源,代表了库尔德人使用的 34 种手语和字母。大量真实用户图片被用来评估所建议策略的准确性。本研究提出了一种用于分类的新型库尔德手语(KuSL)模型。此外,手部区域必须在背景复杂的图片中进行识别,包括光线、环境和不同强度的图片颜色变化。通过使用真实的公共数据集、实时分类和个人独立性,同时保持较高的分类准确性,所提出的技术比以往的 KuSL 检测研究有所改进。收集到的研究结果表明,拟议系统的性能有所提高,分类和预测模型的平均训练准确率达到 99.05%。与之前对 KuSL 的研究相比,这些结果表明系统性能非常强大。
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引用次数: 0
Forest Defender Fusion System for Early Detection of Forest Fires 森林卫士森林火灾早期探测融合系统
Pub Date : 2024-01-28 DOI: 10.3390/computers13020036
Manar Khalid Ibraheem Ibraheem, M. Mohamed, Ahmed Fakhfakh
In the past ten years, rates of forest fires around the world have increased significantly. Forest fires greatly affect the ecosystem by damaging vegetation. Forest fires are caused by several causes, including both human and natural causes. Human causes lie in intentional and irregular burning operations. Global warming is a major natural cause of forest fires. The early detection of forest fires reduces the rate of their spread to larger areas by speeding up their extinguishing with the help of equipment and materials for early detection. In this research, an early detection system for forest fires is proposed called Forest Defender Fusion. This system achieved high accuracy and long-term monitoring of the site by using the Intermediate Fusion VGG16 model and Enhanced Consumed Energy-Leach protocol (ECP-LEACH). The Intermediate Fusion VGG16 model receives RGB (red, green, blue) and IR (infrared) images from drones to detect forest fires. The Forest Defender Fusion System provides regulation of energy consumption in drones and achieves high detection accuracy so that forest fires are detected early. The detection model was trained on the FLAME 2 dataset and obtained an accuracy of 99.86%, superior to the rest of the models that track the input of RGB and IR images together. A simulation using the Python language to demonstrate the system in real time was performed.
在过去十年中,世界各地的森林火灾率大幅上升。森林火灾破坏植被,对生态系统造成极大影响。森林火灾由多种原因引起,包括人为原因和自然原因。人为原因在于故意和不规则的燃烧作业。全球变暖是森林火灾的主要自然原因。森林火灾的早期发现可以借助早期发现设备和材料加快灭火速度,从而降低火灾向更大范围蔓延的速度。本研究提出了一种名为 "森林卫士融合 "的森林火灾早期探测系统。该系统通过使用中间融合 VGG16 模型和增强型耗能浸出协议(ECP-LEACH),实现了对现场的高精度和长期监控。Intermediate Fusion VGG16 模型接收来自无人机的 RGB(红、绿、蓝)和 IR(红外)图像,以探测森林火灾。森林卫士融合系统可调节无人机的能耗,并实现高探测精度,从而及早发现森林火灾。该检测模型在 FLAME 2 数据集上进行了训练,准确率达到 99.86%,优于其他同时跟踪 RGB 和红外图像输入的模型。我们使用 Python 语言进行了模拟,以实时演示该系统。
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引用次数: 1
The Role of Situatedness in Immersive Dam Visualization: Comparing Proxied with Immediate Approaches 情境性在沉浸式水坝可视化中的作用:代用法与直接法的比较
Pub Date : 2024-01-27 DOI: 10.3390/computers13020035
Nuno Verdelho Trindade, Pedro Leitão, Daniel Gonçalves, Sérgio Oliveira, Alfredo Ferreira
Dam safety control is a multifaceted activity that requires analysis, monitoring, and structural behavior prediction. It entails interpreting vast amounts of data from sensor networks integrated into dam structures. The application of extended reality technologies for situated immersive analysis allows data to be contextualized directly over the physical referent. Such types of visual contextualization have been known to improve analytical reasoning and decision making. This study presents DamVR, a virtual reality tool for off-site, proxied situated structural sensor data visualization. In addition to describing the tool’s features, it evaluates usability and usefulness with a group of 22 domain experts. It also compares its performance with an existing augmented reality tool for the on-site, immediate situated visualization of structural data. Participant responses to a survey reflect a positive assessment of the proxied situated approach’s usability and usefulness. This approach shows a decrease in performance (task completion time and errors) for more complex tasks but no significant differences in user experience scores when compared to the immediate situated approach. The findings indicate that while results may depend strongly on factors such as the realism of the virtual environment, the immediate physical referent offered some advantages over the proxied one in the contextualization of data.
大坝安全控制是一项多方面的活动,需要分析、监测和结构行为预测。它需要解释来自集成到大坝结构中的传感器网络的大量数据。将扩展现实技术应用于情景沉浸式分析,可以直接将数据与物理参照物联系起来。众所周知,这种类型的视觉情境化可以改善分析推理和决策制定。本研究介绍了一种虚拟现实工具 DamVR,该工具用于非现场、代理情景结构传感器数据可视化。除了介绍该工具的功能外,它还与 22 位领域专家一起评估了工具的可用性和实用性。报告还将该工具的性能与现有的增强现实工具进行了比较,后者用于现场结构数据的即时情景可视化。参与者对调查的反馈反映出,他们对代理情景方法的可用性和实用性给予了积极评价。与即时情景式方法相比,这种方法在更复杂的任务中的表现(任务完成时间和错误)有所下降,但在用户体验评分方面没有显著差异。研究结果表明,虽然结果在很大程度上取决于虚拟环境的逼真度等因素,但在数据情境化方面,直接物理参照物比代理参照物更具优势。
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引用次数: 0
Approximating Kolmogorov complexity 近似科尔莫哥洛夫复杂性
Pub Date : 2023-09-21 DOI: 10.3233/com-200302
Ruslan Ishkuvatov, D. Musatov, Alexander Shen
It is well known that the Kolmogorov complexity function (the minimal length of a program producing a given string, when an optimal programming language is used) is not computable and, moreover, does not have computable lower bounds. In this paper we investigate a more general question: can this function be approximated? By approximation we mean two things: firstly, some (small) difference between the values of the complexity function and its approximation is allowed; secondly, at some (rare) points the values of the approximating function may be arbitrary. For some values of the parameters such approximation is trivial (e.g., the length function is an approximation with error d except for a O ( 2 − d ) fraction of inputs). However, if we require a significantly better approximation, the approximation problem becomes hard, and we prove it in several settings. Firstly, we show that a finite table that provides good approximations for Kolmogorov complexities of n-bit strings, necessarily has high complexity. Secondly, we show that there is no good computable approximation for Kolmogorov complexity of all strings. In particular, Kolmogorov complexity function is neither generically nor coarsely computable, as well as its approximations, and the time-bounded Kolmogorov complexity (for any computable time bound) deviates significantly from the unbounded complexity function. We also prove hardness of Kolmogorov complexity approximation in another setting: the mass problem whose solutions are good approximations for Kolmogorov complexity function is above the halting problem in the Medvedev lattice. Finally, we mention some proof-theoretic counterparts of these results. A preliminary version of this paper was presented at CiE 2019 conference (In Computing with Foresight and Industry – 15th Conference on Computability in Europe, CiE 2019, Durham, UK, July 15–19, 2019, Proceedings (2019) 230–239 Springer).
众所周知,柯尔莫哥洛夫复杂度函数(在使用最优编程语言的情况下,产生给定字符串的程序的最小长度)是不可计算的,而且没有可计算的下限。在本文中,我们将研究一个更普遍的问题:这个函数能否被逼近?我们所说的近似有两层含义:首先,复杂度函数的值与其近似值之间允许存在一些(很小的)差异;其次,在某些(罕见的)点上,近似函数的值可以是任意的。对于某些参数值,这种近似是微不足道的(例如,长度函数是误差为 d 的近似值,只有 O ( 2 - d ) 部分输入除外)。然而,如果我们需要一个明显更好的近似值,近似问题就会变得困难,我们将在几种情况下证明这一点。首先,我们证明了能很好地近似 n 位字符串的柯尔莫哥洛夫复杂度的有限表必然具有很高的复杂度。其次,我们证明不存在所有字符串的柯尔莫哥洛夫复杂度的可计算近似值。特别是,科尔莫哥罗夫复杂度函数及其近似值既不是一般可计算的,也不是粗略可计算的,有时间限制的科尔莫哥罗夫复杂度(对于任何可计算的时间限制)与无时间限制的复杂度函数有很大偏差。我们还在另一个环境中证明了柯尔莫哥洛夫复杂性近似的硬度:解是柯尔莫哥洛夫复杂性函数良好近似的质量问题高于梅德韦杰夫晶格中的停止问题。最后,我们提到了这些结果的一些证明论对应物。本文的初步版本已在 CiE 2019 会议上发表(In Computing with Foresight and Industry - 15th Conference on Computability in Europe, CiE 2019, Durham, UK, July 15-19, 2019, Proceedings (2019) 230-239 Springer)。
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引用次数: 0
A Parametric Family of Triangular Norms and Conorms with an Additive Generator in the Form of an Arctangent of a Linear Fractional Function 线性分数阶函数的反正切形式的一个加性生成器的三角形范数及其参数族
Pub Date : 2023-08-08 DOI: 10.3390/computation11080155
T. Ledeneva
At present, fuzzy modeling has established itself as an effective tool for designing and developing systems for various purposes that are used to solve problems of control, diagnostics, forecasting, and decision making. One of the most important problems is the choice and justification of an appropriate functional representation of the main fuzzy operations. It is known that, in the class of rational functions, such operations can be represented by additive generators in the form of a linear fractional function, a logarithm of a linear fractional function, and an arctangent of a linear fractional function. The paper is devoted to the latter case. Restrictions on the parameters, under which the arctangent of a linear fractional function is an increasing or decreasing generator, are defined. For each case, a corresponding fuzzy operation (a triangular norm or a conorm) is constructed. The theoretical significance of the research results lies in the fact that the obtained parametric families enrich the theory of Archimedean triangular norms and conorms and provide additional opportunities for the functional representation of fuzzy operations in the framework of fuzzy modeling. In addition, in fact, we formed a scheme for study functions that can be considered additive generators and constructed the corresponding fuzzy operations.
目前,模糊建模已经成为设计和开发各种目的的系统的有效工具,用于解决控制,诊断,预测和决策问题。其中一个最重要的问题是选择和证明一个适当的函数表示的主要模糊操作。我们知道,在有理函数类中,这样的运算可以用加性生成器以线性分数函数、线性分数函数的对数和线性分数函数的反正切的形式来表示。这篇论文专门讨论后一种情况。定义了分数阶线性函数的反正切函数是递增或递减生成函数的参数限制条件。对于每种情况,构造相应的模糊运算(三角范数或保形)。研究结果的理论意义在于,所获得的参数族丰富了阿基米德三角规范理论,为模糊建模框架下模糊运算的函数表示提供了额外的机会。此外,实际上我们形成了一种可视为加性生成器的学习函数方案,并构造了相应的模糊运算。
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引用次数: 0
Revealing the Genetic Code Symmetries through Computations Involving Fibonacci-like Sequences and Their Properties 通过类斐波那契序列及其性质的计算揭示遗传密码的对称性
Pub Date : 2023-08-07 DOI: 10.3390/computation11080154
T. Négadi
In this work, we present a new way of studying the mathematical structure of the genetic code. This study relies on the use of mathematical computations involving five Fibonacci-like sequences; a few of their “seeds” or “initial conditions” are chosen according to the chemical and physical data of the three amino acids serine, arginine and leucine, playing a prominent role in a recent symmetry classification scheme of the genetic code. It appears that these mathematical sequences, of the same kind as the famous Fibonacci series, apart from their usual recurrence relations, are highly intertwined by many useful linear relationships. Using these sequences and also various sums or linear combinations of them, we derive several physical and chemical quantities of interest, such as the number of total coding codons, 61, obeying various degeneracy patterns, the detailed number of H/CNOS atoms and the integer molecular mass (or nucleon number), in the side chains of the coded amino acids and also in various degeneracy patterns, in agreement with those described in the literature. We also discover, as a by-product, an accurate description of the very chemical structure of the four ribonucleotides uridine monophosphate (UMP), cytidine monophosphate (CMP), adenosine monophosphate (AMP) and guanosine monophosphate (GMP), the building blocks of RNA whose groupings, in three units, constitute the triplet codons. In summary, we find a full mathematical and chemical connection with the “ideal sextet’s classification scheme”, which we alluded to above, as well as with others—notably, the Findley–Findley–McGlynn and Rumer’s symmetrical classifications.
在这项工作中,我们提出了一种研究遗传密码数学结构的新方法。这项研究依赖于使用涉及五个类斐波那契序列的数学计算;它们的一些“种子”或“初始条件”是根据三种氨基酸(丝氨酸、精氨酸和亮氨酸)的化学和物理数据来选择的,这三种氨基酸在最近的遗传密码对称分类方案中起着重要作用。这些数学数列,就像著名的斐波那契数列一样,除了它们通常的递归关系外,似乎还被许多有用的线性关系紧密地交织在一起。利用这些序列以及它们的各种总和或线性组合,我们得出了一些感兴趣的物理和化学量,如编码密码子的总数61,服从各种简并模式,H/CNOS原子的详细数量和整数分子质量(或核子数),在编码氨基酸的侧链和各种简并模式中,与文献中描述的一致。我们还发现,作为一个副产品,准确描述了四种核糖核苷酸的化学结构,即单磷酸尿苷(UMP)、单磷酸胞苷(CMP)、单磷酸腺苷(AMP)和单磷酸鸟苷(GMP),它们是RNA的组成部分,以三个单位分组,构成三重密码子。总之,我们发现了一个完整的数学和化学联系与“理想六联体的分类方案”,我们提到了上面,以及与其他-特别是,芬德利-芬德利-麦格林和鲁默的对称分类。
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引用次数: 1
Uncoupling Techniques for Multispecies Diffusion-Reaction Model 多组分扩散-反应模型的解耦技术
Pub Date : 2023-08-04 DOI: 10.3390/computation11080153
M. Vasilyeva, S. Stepanov, Alexey L. Sadovski, Stephen Henry
We consider the multispecies model described by a coupled system of diffusion–reaction equations, where the coupling and nonlinearity are given in the reaction part. We construct a semi-discrete form using a finite volume approximation by space. The fully implicit scheme is used for approximation by time, which leads to solving the coupled nonlinear system of equations at each time step. This paper presents two uncoupling techniques based on the explicit–implicit scheme and the operator-splitting method. In the explicit–implicit scheme, we take the concentration of one species in coupling term from the previous time layer to obtain a linear uncoupled system of equations. The second approach is based on the operator-splitting technique, where we first solve uncoupled equations with the diffusion operator and then solve the equations with the local reaction operator. The stability estimates are derived for both proposed uncoupling schemes. We present a numerical investigation for the uncoupling techniques with varying time step sizes and different scales of the diffusion coefficient.
我们考虑由扩散-反应方程耦合系统描述的多物种模型,其中反应部分给出了耦合和非线性。我们利用空间的有限体积近似构造一个半离散形式。采用全隐式格式进行时间逼近,从而在每个时间步上求解耦合非线性方程组。本文提出了基于显隐格式和算子分裂方法的两种解耦技术。在显隐格式中,我们从前一时间层中取耦合项中一种的浓度,得到一个线性解耦方程组。第二种方法是基于算子分裂技术,首先用扩散算子求解解耦方程,然后用局部反应算子求解解耦方程。给出了两种解耦方案的稳定性估计。本文对不同时间步长和不同扩散系数尺度下的解耦技术进行了数值研究。
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引用次数: 0
Joining Federated Learning to Blockchain for Digital Forensics in IoT 加入联邦学习区块链用于物联网中的数字取证
Pub Date : 2023-08-03 DOI: 10.3390/computers12080157
Wejdan Almutairi, T. Moulahi
In present times, the Internet of Things (IoT) is becoming the new era in technology by including smart devices in every aspect of our lives. Smart devices in IoT environments are increasing and storing large amounts of sensitive data, which attracts a lot of cybersecurity threats. With these attacks, digital forensics is needed to conduct investigations to identify when and where the attacks happened and acquire information to identify the persons responsible for the attacks. However, digital forensics in an IoT environment is a challenging area of research due to the multiple locations that contain data, traceability of the collected evidence, ensuring integrity, difficulty accessing data from multiple sources, and transparency in the process of collecting evidence. For this reason, we proposed combining two promising technologies to provide a sufficient solution. We used federated learning to train models locally based on data stored on the IoT devices using a dataset designed to represent attacks on the IoT environment. Afterward, we performed aggregation via blockchain by collecting the parameters from the IoT gateway to make the blockchain lightweight. The results of our framework are promising in terms of consumed gas in the blockchain and an accuracy of over 98% using MLP in the federated learning phase.
当今时代,物联网(IoT)正在成为一个新时代的技术,包括智能设备在我们生活的方方面面。物联网环境下的智能设备不断增加,存储着大量敏感数据,这也吸引了大量的网络安全威胁。对于这些攻击,需要数字取证来进行调查,以确定攻击发生的时间和地点,并获取信息以确定攻击的责任人。然而,物联网环境中的数字取证是一个具有挑战性的研究领域,因为包含数据的多个位置,收集证据的可追溯性,确保完整性,难以从多个来源访问数据,以及收集证据过程的透明度。因此,我们建议将两种有前途的技术结合起来,以提供一个充分的解决方案。我们使用联邦学习来训练本地模型,该模型基于存储在物联网设备上的数据,使用旨在表示对物联网环境的攻击的数据集。之后,我们通过区块链进行聚合,从物联网网关收集参数,使区块链轻量级。我们的框架的结果在区块链中消耗的gas和在联邦学习阶段使用MLP的准确率超过98%方面是有希望的。
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引用次数: 0
Enhancing the Hardware Pipelining Optimization Technique of the SHA-3 via FPGA 基于FPGA的SHA-3硬件流水线优化技术
Pub Date : 2023-08-03 DOI: 10.3390/computation11080152
Argyrios Sideris, M. Dasygenis
Information is transmitted between multiple insecure routing hops in text, image, video, and audio. Thus, this multi-hop digital data transfer makes secure transmission with confidentiality and integrity imperative. This protection of the transmitted data can be achieved via hashing algorithms. Furthermore, data integrity must be ensured, which is feasible using hashing algorithms. The advanced cryptographic Secure Hashing Algorithm 3 (SHA-3) is not sensitive to a cryptanalysis attack and is widely preferred due to its long-term security in various applications. However, due to the ever-increasing size of the data to be transmitted, an effective improvement is required to fulfill real-time computations with multiple types of optimization. The use of FPGAs is the ideal mechanism to improve algorithm performance and other metrics, such as throughput (Gbps), frequency (MHz), efficiency (Mbps/slices), reduction of area (slices), and power consumption. Providing upgraded computer architectures for SHA-3 is an active area of research, with continuous performance improvements. In this article, we have focused on enhancing the hardware performance metrics of throughput and efficiency by reducing the area cost of the SHA-3 for all output size lengths (224, 256, 384, and 512 bits). Our approach introduces a novel architectural design based on pipelining, which is combined with a simplified format for the round constant (RC) generator in the Iota (ι) step only consisting of 7 bits rather than the standard 64 bits. By reducing hardware resource utilization in the area and minimizing the amount of computation required at the Iota (ι) step, our design achieves the highest levels of throughput and efficiency. Through extensive experimentation, we have demonstrated the remarkable performance of our approach. Our results showcase an impressive throughput rate of 22.94 Gbps and an efficiency rate of 19.95 Mbps/slices. Our work contributes to advancing computer architectures tailored for SHA-3, therefore unlocking new possibilities for secure and high-performance data transmission.
信息在文本、图像、视频和音频的多个不安全路由跳之间传输。因此,这种多跳数字数据传输使得具有机密性和完整性的安全传输势在必行。这种对传输数据的保护可以通过散列算法来实现。此外,必须确保数据的完整性,这是可行的使用哈希算法。高级加密安全散列算法3 (SHA-3)对密码分析攻击不敏感,由于其长期安全性在各种应用中被广泛采用。然而,由于要传输的数据量不断增加,需要通过多种类型的优化来实现实时计算的有效改进。使用fpga是提高算法性能和其他指标的理想机制,例如吞吐量(Gbps)、频率(MHz)、效率(Mbps/片)、面积减少(片)和功耗。为SHA-3提供升级的计算机架构是一个活跃的研究领域,性能也在不断改进。在本文中,我们主要关注通过降低SHA-3在所有输出大小长度(224、256、384和512位)下的面积成本来增强吞吐量和效率的硬件性能指标。我们的方法引入了一种基于流水线的新架构设计,它与Iota (ι)步骤中仅由7位而不是标准64位组成的圆形常数(RC)生成器的简化格式相结合。通过减少该区域的硬件资源利用率并最大限度地减少Iota (ι)步骤所需的计算量,我们的设计实现了最高水平的吞吐量和效率。通过广泛的实验,我们已经证明了我们的方法的卓越性能。我们的结果显示了22.94 Gbps的吞吐量和19.95 Mbps/片的效率。我们的工作有助于推进为SHA-3量身定制的计算机架构,从而为安全和高性能数据传输解锁新的可能性。
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引用次数: 0
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