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Stochastic Machine Learning Models for Mutation Rate Analysis of Malignant Cancer Cells in Patients with Acute Lymphoblastic Leukemia 用于分析急性淋巴细胞白血病患者恶性肿瘤细胞突变率的随机机器学习模型
Q4 Engineering Pub Date : 2024-07-05 DOI: 10.46300/9106.2024.18.1
Martsenyuk Vasyl, Abubakar Umar Sadiq, Sverstiuk Andriy, Dimitrov Georgi, Gancarczyk Tomasz
Acute lymphoblastic leukemia, a pervasive form of the carcinogenic disease, is a lethal ailment subjecting numerous pediatric patients globally to terminal conditions. is a rapidly progressive condition, that exposes patients to conditions including Tumor Lysis Syndrome which often occurs early after the induction chemotherapy, contemporary research focuses primarily on the development of techniques for the early diagnosis of Acute Lymphoblastic Leukemia (ALL), leaving a gap within the literature. This study examines the application of machine learning techniques for the prognosis the mutation rate of cancer cells in pediatric patients with Acute Lymphoblastic Leukemia using clinical data from patients with ALL, who have undergone tests using Next Generation Sequencing (NGS) technology. An overview of the clinical data utilized is provided in this study, with a comprehensive workflow encompassing, data analysis, dimensionality reduction, classification and regression tree algorithm (CART), and neural networks. Results here demonstrate the efficiency with which these methods are able to target and decipher cancer cell proliferation in pediatric patients suffering from acute lymphoblastic leukemia. Valuable insights into relationships between key factors and conversion rates were also derived through data mining. However, tree classification and regression algorithms and neural networks used herein indicate the flexibility and the power of machine learning models in predicting the recurrence of cancer cells accurately. This study’s results affirm previous findings thus giving clinical proof for mutational drivers among pediatric patients having Acute Lymphoblastic Leukemia. This adds value to results by providing an applicable utility in medical practice. Principally, this study denotes a substantial advancement in leveraging machine learning workflows for mutation rate analysis of cancer cells. By appraising clinical corroboration, emphasizing the explain ability and interpretability, and building upon these findings, future research can contribute to improving patient care and results in the field of Leukaemia.
急性淋巴细胞白血病是一种普遍存在的致癌疾病,是一种致命的疾病,使全球众多儿科患者面临绝症。急性淋巴细胞白血病是一种进展迅速的疾病,使患者面临包括肿瘤溶解综合征在内的各种情况,而肿瘤溶解综合征往往发生在诱导化疗后的早期。本研究利用使用下一代测序(NGS)技术进行检测的急性淋巴细胞白血病(ALL)患者的临床数据,研究了机器学习技术在预测急性淋巴细胞白血病儿科患者癌细胞突变率方面的应用。本研究概述了所使用的临床数据,其全面的工作流程包括数据分析、降维、分类和回归树算法(CART)以及神经网络。研究结果表明,这些方法能够高效地锁定和解读急性淋巴细胞白血病儿科患者的癌细胞增殖。通过数据挖掘,还对关键因素与转化率之间的关系有了宝贵的见解。不过,这里使用的树状分类和回归算法以及神经网络表明,机器学习模型在准确预测癌细胞复发方面具有灵活性和强大的功能。这项研究的结果肯定了之前的发现,从而为急性淋巴细胞白血病儿科患者的突变驱动因素提供了临床证明。这为医疗实践提供了适用的实用性,从而增加了研究结果的价值。主要而言,这项研究表明,利用机器学习工作流程进行癌细胞突变率分析取得了重大进展。通过评估临床佐证,强调解释能力和可解释性,并以这些发现为基础,未来的研究将有助于改善白血病领域的患者护理和结果。
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引用次数: 0
Detecting Small Objects Using a Smartphone and Neon Camera 使用智能手机和霓虹灯相机检测小物体
Q4 Engineering Pub Date : 2023-06-01 DOI: 10.18178/ijsps.11.2.7-10
Lianly Rompis, Julie Rante
—In daily life, humans often encounter difficulties when performing activities such as working or learning, particularly when handling small components such as needles, screws, clips, coin batteries and electronic components. These objects are frequently dropped and finding them can consume extra time and energy. Additionally, they pose a danger to babies and children while they are playing around. Given that smartphones have become essential devices for communication and are highly versatile, easily used both at work and at home, the research team from the Faculty of Engineering was motivated to study how to optimize the use of smartphones for detecting small objects. The research methodology included a literature review, observation, and analysis using a smartphone and neon camera application. This application was selected due to its unique characteristics to produce a perfect black background and color image frame. Five small components were chosen as samples for the research: needles, screws, clips, coin batteries, and transparent Light Emitting Diodes (LEDs). The results provide a fundamental understanding for further development of using neon cameras to detect small objects. 
在日常生活中,人类在进行工作或学习等活动时经常遇到困难,特别是在处理针、螺丝、夹子、硬币电池和电子元件等小部件时。这些物品经常掉落,寻找它们会消耗额外的时间和精力。此外,它们在玩耍时对婴儿和儿童构成危险。鉴于智能手机已经成为必不可少的通信设备,而且用途广泛,在工作和家庭中都很容易使用,来自工程学院的研究团队受到激励,研究如何优化智能手机用于检测小物体的使用。研究方法包括文献回顾、观察和分析,使用智能手机和霓虹灯相机应用程序。这个应用程序被选中,因为它的独特特点,以产生一个完美的黑色背景和彩色图像框架。研究中选择了五个小部件作为样本:针、螺丝、夹子、硬币电池和透明发光二极管(led)。研究结果为进一步发展利用霓虹灯相机探测小物体提供了基础认识。
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引用次数: 0
Optimization of New Energy Vehicle Road Noise Problem Based on Finite Element Analysis Method 基于有限元分析方法的新能源汽车道路噪声问题优化
Q4 Engineering Pub Date : 2023-04-04 DOI: 10.46300/9106.2023.17.22
Fu Mao
In the use of new energy vehicles, user experience has always been the key project of major manufacturers. At present, the research on user experience focuses on the posture performance of the vehicle itself, and less attention is paid to road noise. Therefore, this study takes the road noise problem of new energy vehicles as the object. The finite element analysis method is chosen for modeling. And the research on the optimization of road noise is carried out. After modeling, the correctness of the model was tested, and all four modes were controlled within the modal error range of 5%. When the new energy vehicle based on this model ran at 80 km/h, the peak road noise was reduced by about 11 dB(A). In addition, after optimizing the tire, the peak value decreased by 4 dB(A). After optimizing the transverse stinger of the rear suspension, the Z-bending mode was increased by 22.3 Hz. Compared with the previous basic scheme, the optimization effect was obvious. When the optimized new energy vehicle ran at a speed of 60 km/h, the peak value is reduced by about 5 dB(A) on the rough road with a frequency of 65 Hz. The results showed that, under the proposed method, the road noise problem was improved, the peak value of the problem was eliminated, and the expected acceptable range was reached.
在新能源汽车的使用中,用户体验一直是各大厂商的重点项目。目前对用户体验的研究主要集中在车辆本身的姿态性能上,而对道路噪声的关注较少。因此,本研究以新能源汽车道路噪声问题为研究对象。采用有限元分析方法进行建模。并对道路噪声的优化进行了研究。建模完成后,验证了模型的正确性,将四种模态误差控制在5%的模态误差范围内。当基于该模型的新能源汽车以80 km/h行驶时,道路峰值噪声降低约11 dB(A)。此外,优化轮胎后,峰值降低了4 dB(A)。优化后悬架横向推力杆后,z -弯曲模态提高22.3 Hz。与之前的基本方案相比,优化效果明显。当优化后的新能源汽车以60 km/h的速度行驶时,在频率为65 Hz的粗糙路面上,峰值降低约5 dB(a)。结果表明,在该方法下,道路噪声问题得到了改善,消除了问题的峰值,达到了预期的可接受范围。
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引用次数: 0
Base Elements for Artificial Neural Network: Structure Modeling, Production, Properties 人工神经网络的基本元素:结构建模,生产,性质
Q4 Engineering Pub Date : 2023-04-03 DOI: 10.46300/9106.2023.17.21
A. Sidorenko, N. Klenov, I. Soloviev, S. Bakurskiy, V. Boian, R. Morari, Yu. B. Savva, A. Lomakin, Ludmila Sidorenko, Svetlana Sidorenko, Irina Sidorenko, O. Severyukhina, Aleksey Fedotov, Anastasia Salamatina, A. Vakhrushev
A radical reduction in power consumption is becoming an important task in the development of supercomputers. Artificial neural networks (ANNs) based on superconducting elements of spintronics seem to be the most promising solution. A superconducting ANN needs to develop two basic elements - a nonlinear (neuron) and a linear connecting element (synapse). The theoretical and experimental results of this complex and interdisciplinary problem are presented in this paper. The results of our theoretical and experimental study of the proximity effect in a stacked superconductor/ferromagnet (S/F) superlattice with Co-ferromagnetic layers of various thicknesses and coercive fields and Nb-superconducting layers of constant thickness equal to the coherence length of niobium and some studies using computer simulation of the formation of such multilayer nanostructures and their magnetic properties are presented in this article.
大幅降低功耗正成为超级计算机发展中的一项重要任务。基于自旋电子学超导元件的人工神经网络(ann)似乎是最有希望的解决方案。超导人工神经网络需要发展两个基本元素——非线性(神经元)和线性连接元素(突触)。本文介绍了这一复杂的跨学科问题的理论和实验结果。本文介绍了具有不同厚度和矫顽力场的共铁磁层和等于铌相干长度等厚度的铌-超导层的叠加超导体/铁磁(S/F)超晶格中邻近效应的理论和实验研究结果,以及利用计算机模拟这种多层纳米结构的形成及其磁性能的一些研究结果。
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引用次数: 0
Underwater Acoustic Positioning for Close Sources Using Time Division and Code Division Multiplexing 基于时分和码分复用的近源水声定位
Q4 Engineering Pub Date : 2023-03-29 DOI: 10.46300/9106.2023.17.20
S. Yoshizawa, Atsushi Wada, Hideki Sugimoto
Underwater acoustic positioning system (UAPS) is used to know the positions of underwater robots and underwater structures. In ultra-short baseline (USBL) acoustic positioning systems, the three-dimensional position is determined by measuring the time difference of arrival (TDOA). In this paper, we investigate the acoustic positioning system targeting multiple sound sources and propose a simultaneous multi-point measurement method using time division and code division multiplexing (TD-CDM). TD-CDM provides higher position accuracy than code division multiplexing (CDM) and has a much shorter positioning time than time division and multiplexing (TDM). The effectiveness of TD-CDM has been proven by the results of the water tank experiment and simulation.
水声定位系统(UAPS)用于了解水下机器人和水下结构的位置。在超短基线(USBL)声定位系统中,通过测量到达时间差(TDOA)来确定三维位置。本文研究了针对多声源的声定位系统,提出了一种采用时分和码分复用(TD-CDM)的多点同步测量方法。TD-CDM具有比码分复用(CDM)更高的定位精度和比时分复用(TDM)更短的定位时间。水箱试验和仿真结果验证了TD-CDM的有效性。
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引用次数: 0
Distributed Generation Hosting Capacity Evaluation for Distribution Networks Considering Uncertainty 考虑不确定性的配电网分布式发电承载能力评估
Q4 Engineering Pub Date : 2023-03-29 DOI: 10.46300/9106.2023.17.19
Mohammad Ali Ashna, Dong Liang
The use of grid systems for distributing and managing resources such as computing power and data storage has become increasingly widespread in recent years. However, as the demand for these resources continues to grow, the capacity of traditional grid systems to meet this demand has become a concern. When dealing with the constantly expanding system scale and its many uncertainties, traditional model-based techniques are becoming unsuitable. A better alternative to these techniques involves considering data-driven control (DDC) methodologies. In this paper, we begin by reviewing the current state of the art in DDC usage in grid systems in monitoring, improving, error detection, etc. with a particular focus on improving host capacity. We then describe our proposed approach, which involves improving the host capacity of grid systems using historical data. Finally, we present experimental results demonstrating the effectiveness of our approach and discuss its potential impact and future directions.
近年来,网格系统在分配和管理资源(如计算能力和数据存储)方面的应用越来越广泛。然而,随着对这些资源的需求不断增长,传统电网系统满足这一需求的能力已成为一个问题。在处理不断扩大的系统规模及其众多的不确定性时,传统的基于模型的技术变得越来越不适应。这些技术的一个更好的替代方案涉及到考虑数据驱动控制(DDC)方法。在本文中,我们首先回顾了DDC在电网系统中使用的现状,包括监控、改进、错误检测等,并特别关注提高主机容量。然后,我们描述了我们提出的方法,该方法涉及使用历史数据提高网格系统的主机容量。最后,我们给出了实验结果,证明了我们的方法的有效性,并讨论了其潜在的影响和未来的方向。
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引用次数: 0
DTC-SVM οf Sensorless Five-phase Induction Machine Using Extended Kalman Filter 基于扩展卡尔曼滤波的无传感器五相感应电机DTC-SVM ο
Q4 Engineering Pub Date : 2023-03-13 DOI: 10.46300/9106.2023.17.17
E. Benyoussef, S. Barkat
This work relates to the study of direct torque control based on space vector modulation applied on five-phase induction machine. It is well established that the conventional direct torque control using hysteresis comparators suffers from high torque ripples and variable switching frequency. The most common solution to those problems is the use of space vector modulation. In the other hand, this paper aims also to design an extended Kalman filter observer for speed/flux estimation, which improves not only the control performances by using a sensorless algorithm but also can lower the cost and increase the reliability of the system. Both theoretical principle and simulation results of the sensorless control method of multiphase drive will be conducted to verify the effectiveness of the proposed control approach.
本文研究了基于空间矢量调制的直接转矩控制在五相感应电机上的应用。传统的磁滞比较器直接转矩控制存在转矩波动大和开关频率可变的问题。这些问题最常见的解决方案是使用空间矢量调制。另一方面,本文还设计了一种扩展的卡尔曼滤波观测器用于速度/通量估计,该观测器不仅可以提高无传感器算法的控制性能,还可以降低系统的成本和提高系统的可靠性。通过多相驱动无传感器控制方法的理论原理和仿真结果验证了所提控制方法的有效性。
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引用次数: 0
Optimization of Lai Estimation Method Based on Smartphones with Fisheye Lens 基于鱼眼镜头智能手机的Lai估计方法优化
Q4 Engineering Pub Date : 2023-03-13 DOI: 10.46300/9106.2023.17.14
Lichen Zhu, Peng Guan, Weiping Liu, Y. Zheng
Leaf area index (LAI) is an important biological factor reflecting vegetation growth and forest ecosystem. LAI can be used to obtain plant health status, carbon cycle, and surrounding ecological environment effectively. In this study, the smartphone was equipped with a fisheye lens, and the optimization method was used to estimate LAI, which was compared with digital hemispherical photography (DHP) to investigate the possibility of the new method for LAI estimation. The hemispherical image was divided into blocks, and the optimized Otsu method was used for algorithm segmentation, which can effectively distinguish vegetation from the sky. Concurrently, when the gap fraction inversion LAI was performed, the linear inversion algorithm was improved based on single-angle inversion, and the LAI was obtained by inversion through the linear fitting of the mul-tiangle gap fraction. The experimental sample was located in Olympic National Forest Park in Beijing. Three coniferous mixed forests and three broadleaved forests were selected from the experimental sample. LAI measurements from smartphones were compared with those from DHP. In the samples for mixed coniferous forests, the values for coefficients of determination R^2 were 0.835, 0.802, and 0.809, and root mean square errors (REMS) were 0.137, 0.120, and 0.147. For the broadleaf forest samples, the values for R² were 0.629, 0.679, and 0.758, and REMS were 0.144, 0.135, and 0.137. The R^2 and RMES for the overall data was 0.810 and 0.134, respectively, and a good agreement between the LAI measurements from the proposed method and those from the DHP supports an accurate estimation. The results show that the use of a fisheye lens on a smartphone can effectively and accurately obtain tree canopy LAI. This provides a fast and effective new method to measure LAI of forest vegetation near the ground, which is of great significance for studying the interaction between plant growth status, ecological environment, and phenological changes.
叶面积指数(LAI)是反映植被生长和森林生态系统的重要生物因子。LAI可以有效地获取植物健康状况、碳循环和周围生态环境。本研究在智能手机上配置鱼眼镜头,采用优化方法估算LAI,并与数字半球摄影(DHP)进行比较,探讨新方法估算LAI的可能性。将半球形图像进行分块,采用优化后的Otsu方法进行算法分割,能够有效区分植被和天空。同时,在进行间隙分数反演LAI时,在单角度反演的基础上改进了线性反演算法,通过多三角形间隙分数的线性拟合进行反演得到LAI。实验样本位于北京奥林匹克国家森林公园。从实验样本中选取3个针叶混交林和3个阔叶林。智能手机的LAI测量值与DHP测量值进行了比较。混交林样品的决定系数R^2分别为0.835、0.802和0.809,均方根误差(REMS)分别为0.137、0.120和0.147。阔叶林样本的R²分别为0.629、0.679和0.758,REMS分别为0.144、0.135和0.137。总体数据的R^2和RMES分别为0.810和0.134,所提出方法的LAI测量值与DHP测量值之间的良好一致性支持了准确的估计。结果表明,在智能手机上使用鱼眼镜头可以有效准确地获取树冠LAI。这为近地森林植被LAI的测量提供了一种快速有效的新方法,对研究植物生长状况、生态环境和物候变化之间的相互作用具有重要意义。
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引用次数: 0
Phytochemical Screening and Evaluation of Heavy Metals in a Medicinal Plant Marrubium Vulgare L 药用植物凡夫兰重金属的植物化学筛选与评价
Q4 Engineering Pub Date : 2023-03-13 DOI: 10.46300/9106.2023.17.13
Ado-Baba Ahmed, Tahar Kebi
Our research is part of the enhancement of our plant heritage that we deemed necessary to exploit it, our choice fell on a medicinal plant Marrubium vulgare L and this by the phytochemical characterization (of leaves, stems and roots) followed by the study of the xerophytic character, by determining the content of five heavy metals (Zinc, Copper, Cadmium, Lead and Chromium)in the different organs and by analysis with atomic absorption spectrometry (AAS). The results of the phytochemical tests showed the richness in secondary compounds, namely: flavonoids, tannins, saponosides, coumarins and reducing compounds. heavy metal analyzes showed that Marrubium vulgare L was found to have a high capacity to accumulate heavy metals, especially chromium and copper. The levels of its heavy metals are within the toxic threshold of plants.
我们的研究是加强我们的植物遗产的一部分,我们认为有必要开发它,我们选择了药用植物Marrubium vulgare L,这是通过植物化学特性(叶,茎和根)的研究,然后是旱生特性的研究,通过测定不同器官中五种重金属(锌,铜,镉,铅和铬)的含量,并通过原子吸收光谱(AAS)分析。植物化学试验结果表明,黄酮类化合物、单宁类化合物、皂苷类化合物、香豆素类化合物和还原性化合物丰富。重金属分析结果表明,普通Marrubium vulgare L具有较高的重金属积累能力,特别是铬和铜。它的重金属含量在植物的有毒阈值之内。
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引用次数: 1
An Enhanced SLC Scheme for Cooperative Spectrum Sensing System in Cognitive Radio 认知无线电协同频谱感知系统中一种改进的SLC方案
Q4 Engineering Pub Date : 2023-03-13 DOI: 10.46300/9106.2023.17.18
Younes Bouzegag, Djamal Teguig, A. Maali
The hidden-nodes and noise uncertainty have a negative impact on the spectrum sensing results in cognitive radio. Accordingly, cooperative spectrum sensing is proposed to effectively increase detection reliability by dealing with different soft and hard patterns in the fusion center. In the present work, we analyzed various soft and hard fusion rules. Improved Square Law Combining (SLC) rules are proposed to provide better detection performance than the conventional scheme. To validate the introduced rule, MATLAB simulations were conducted revealing the out-performance of the proposed schemes over the conventional one even in a critical wireless environment with a low signal-to-noise ratio. The proposed approach is then more advantageous because it minimizes the trade-off between detection performance and computational complexity.
在认知无线电中,隐藏节点和噪声不确定性对频谱感知结果有负面影响。为此,提出协同频谱感知,通过处理融合中心不同的软、硬模式,有效提高检测可靠性。在本工作中,我们分析了各种软、硬融合规律。提出了改进的平方律组合(SLC)规则,以提供比传统方案更好的检测性能。为了验证所引入的规则,进行了MATLAB仿真,揭示了即使在低信噪比的关键无线环境中,所提出的方案也优于传统方案。因此,所提出的方法更有利,因为它最大限度地减少了检测性能和计算复杂性之间的权衡。
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引用次数: 0
期刊
International Journal of Circuits, Systems and Signal Processing
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