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2021 5th International Symposium on Multidisciplinary Studies and Innovative Technologies (ISMSIT)最新文献

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Solving IoT Security and Scalability Challenges with Blockchain 用区块链解决物联网安全性和可扩展性挑战
Martin Djonov, Miroslav Galabov, T. Georgieva-Trifonova
Internet of Things (IoT) is one relatively new technology, which aims to make our lives easier by automating our daily processes. This article would aim to deliver an idea how to prevent the IoT technology, delivering maliciously and bad things and how to scale. The intention of this research is to explain how a specific implementation of a Blockchain network, enterprise-grade permissioned distributed ledger framework called Hyperledger Fabric, can be used to resolve the security and scalability issues in an IoT network.
物联网(IoT)是一项相对较新的技术,旨在通过自动化我们的日常流程使我们的生活更轻松。本文旨在提供一个想法,如何防止物联网技术,提供恶意和不好的东西,以及如何扩展。本研究的目的是解释如何使用区块链网络的特定实现,即称为Hyperledger Fabric的企业级许可分布式账本框架来解决物联网网络中的安全性和可扩展性问题。
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引用次数: 2
UTtoKB: a Model for Semantic Relation Extraction from Unstructured Text UTtoKB:非结构化文本语义关系抽取模型
Mustafa Nabeel Salim, Ban Shareef Mustafa
In this paper, a model prototype called UTtoKB has been built. It extracts semantic relationships from an unstructured text based on ontology. The model is a pipeline steps based on natural language processing (NLP) tasks and tools like Coreference Resolution (CR), Named Entity Recognition (NER), Semantic Role Labeling (SRL), and Part of Speech (PoS) Tagging. WordNet is the tool used to measure similarities between entities to convert them into ontology concepts and properties. The model works fine in specific domains, while performance degrades in other domains due to the instability of WordNet performance in finding semantic similarities.
本文建立了一个名为UTtoKB的模型原型。它基于本体从非结构化文本中提取语义关系。该模型是一个基于自然语言处理(NLP)任务和工具的流水线步骤,如共同参考解析(CR)、命名实体识别(NER)、语义角色标记(SRL)和词性标记(PoS)。WordNet是用来度量实体之间的相似性,并将它们转换为本体概念和属性的工具。该模型在特定领域工作良好,而由于WordNet在寻找语义相似性方面的性能不稳定,在其他领域的性能会下降。
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引用次数: 1
Power Converter Topologies for PMSG Based Wind Energy Systems: Packed U Cell Multilevel Inverter Simulation 基于PMSG的风能系统的功率转换器拓扑:封装U单元多电平逆变器仿真
H. Y. Hasirci, A. Vural
One of the results of the development of technology is the development of power electronics and the elements used in power electronics (such as semiconductor circuit elements). When converting DC-AC to conventional inverters, there are problems with lower voltage capacity, high harmonic content at the input and output, and high switching losses. Multilevel inverters (MLIs) have overcome these problems. In this study, The Packed U Cell (PUC) inverter that is a special type of MLIs is investigated. In addition, the PUC7 MLI inverter is designed, simulated, and integrated into the PMSG based variable speed wind energy conversion systems.
技术发展的结果之一是电力电子学和电力电子学中使用的元件(如半导体电路元件)的发展。在将直流-交流转换为常规逆变器时,存在电压容量低、输入输出谐波含量高、开关损耗大等问题。多电平逆变器(mli)克服了这些问题。本文研究了一种特殊类型的MLIs——PUC逆变器。此外,对PUC7 MLI逆变器进行了设计、仿真,并将其集成到基于PMSG的变速风能转换系统中。
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引用次数: 1
Piezoelectric Force Sensor-based Measurement System for Recoil Force Analysis 基于压电力传感器的后坐力分析测量系统
I. Ilter, S. Dilibal, H. Zengin
In this study, a piezoelectric force sensor-based experimental recoil force analysis was performed via examining the formation and effects of recoil forces after overviewing the related experimental studies in the literature. The experimental measurement and the analysis of the recoil forces of the selected shotguns were carried out systematically after selecting the accurate piezoelectric force sensor for the dynamic performance of the recoil mechanism. The experimental setup required for the measurement was built via integrating the selected piezoelectric force sensor, signal conditioner, data acquisation card with a software developed in Visual Basic .NET software language. A developed measuring apparatus was designed to measure the dynamic recoil forces of different shotgun system. The selected piezoelectric force sensor can detect the recoil forces with 36 kHz measurement capacity. All of the data were recorded in real-time. The recorded data were examined, and analyzed comparatively. The collected measurement results are evaluated according to the recoil mechanisms, barrel lengths, weights, and other effective parameters that may affect the recoil forces in the experimental analysis. It was observed that the shotgun that spreads the recoil force over time reduces the peak point and has minimum total recoil energy among the gas cycle, inertia and hybrid shotguns with 71cm barrel length and included 12GA caliber.
本研究在回顾文献相关实验研究的基础上,通过考察后坐力的形成和影响,进行了基于压电力传感器的实验后坐力分析。对所选霰弹枪的后坐力进行了系统的实验测量和分析,选择了精确的压电式力传感器,对所选霰弹枪的后坐力进行了分析。将选定的压电式力传感器、信号调节器、数据采集卡与Visual basic.net开发的软件集成在一起,搭建了测量所需的实验装置。设计了一套测量装置,用于测量不同霰弹枪系统的动态后坐力。所选择的压电式力传感器可以检测后坐力,测量容量为36khz。所有数据都是实时记录的。对记录的数据进行了检查和比较分析。根据实验分析中可能影响后坐力的后坐力机理、枪管长度、重量等有效参数,对收集到的测量结果进行评估。研究发现,在71cm管长、12GA口径的气循环、惯性和混合霰弹枪中,后坐力随时间分散的霰弹枪峰值点减小,总后坐力最小。
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引用次数: 0
Assessment of Slime Mould Algorithm Based Real PID Plus Second-order Derivative Controller for Magnetic Levitation System 基于泥霉菌算法的磁悬浮系统实PID加二阶导数控制器评价
Davut Izci, Serdar Ekinci, Erdal Eker, Ahmet Dündar
This paper aims to demonstrate the success of a recently developed metaheuristic algorithm, named slime mould algorithm (SMA), for efficient operation of a magnetic levitation system. A real proportional-integral-derivative (PID) plus second-order derivative (PIDD2) controller was utilized to demonstrate the implementation. This paper is also the first report on SMA based real PIDD2 controller tuning for control of a magnetic levitation system. The transient response analysis was performed to demonstrate the promise of the proposed approach. Besides, a comparative performance analysis in terms of transient stability was also performed by using other available and good performing approaches. The results have shown the SMA based real PIDD2 controller to be a better choice for efficient operation of a magnetic levitation system.
本文旨在展示最近开发的一种名为黏菌算法(SMA)的元启发式算法的成功,该算法用于磁悬浮系统的有效运行。采用比例-积分-导数(PID)加二阶导数(PIDD2)实数控制器来演示其实现。本文也首次报道了基于SMA的PIDD2控制器实际整定用于磁悬浮系统的控制。进行了瞬态响应分析,以证明所提出的方法的前景。此外,还利用其他可用的性能较好的方法对暂态稳定性进行了性能对比分析。结果表明,基于SMA的实际PIDD2控制器是实现磁悬浮系统高效运行的较好选择。
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引用次数: 3
Discrete-Model Based Analysis of Flyback Converter Circuit 基于离散模型的反激变换器电路分析
Bilal Canol, A. Yildiz
A new model has been proposed for the analysis of Flyback converter with coupled inductance. The model transforms any dynamic circuit into a resistive circuit. The method is based on the discrete equivalent circuit approach. In this way, a fully resistive flyback circuit has been obtained with discrete equivalents of coupled inductor and capacitor. The proposed model makes the analysis easier.
提出了一种分析电感耦合反激变换器的新模型。该模型将任何动态电路转换为电阻电路。该方法基于离散等效电路方法。用这种方法,得到了电感和电容耦合的离散等效的全电阻反激电路。所提出的模型使分析更容易。
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引用次数: 0
Jetson Nano Üzerinde Çift Kameralı Uzaklık Hesaplama Uygulanması
Salih Palamut, Abdullah Elewi, Erdinç Avaroglu
Bu çalışmada merkezler arası uzaklığı 65 mm olan iki kamera, metal plaka yardımıyla sabitlenmiştir. Gömülü sistem olarak iki kamera destekli Jeston Nano tek kart bilgisayarı üzerinde C++ dili ile OpenCv kitaplığı kullanarak çalışma düzlemi kurulmuştur. Bu düzlemde basit kenar bulma algoritması yöntemiyle iki kameradan elde edilen görüntülerin matematiksel hesaplama yöntemleriyle kullanılan kameralar üzerinde piksel hesabıyla görüş alanında bulunan nesnenin uzaklığı hesaplanmış ve analog ölçüm aletiyle hesaplanan değerin sağlaması yapılmıştır. Yapılan çalışmalarda nesnenin 20 cm’den daha yakın konumlanması hesaplanan değerin kenar algoritmasının yetersizliğinden dolayı hata payını arttırdığı 20 cm ve üstü değerler için çevresel etmenlerden dolayı değişken sapmalar olduğu gözlemlenmiştir.In this study, two cameras with 65 mm distance between centers were fixed with the help of metal plate. As an embedded system, a work plane was set up using the C++ language and OpenCv library on a Jeston Nano single board computer with two cameras. In this plane, the distance of the object in the field of view was calculated with the pixel calculation on the cameras used with the mathematical calculation methods of the images obtained from the two cameras by the simple edge detection algorithm method, and the value calculated with the analog measuring instrument was verified. In the studies, it has been observed that there are variable deviations due to environmental factors for values of 20 cm and above, where the calculated value increases the margin of error due to the inadequacy of the edge algorithm.
在这项研究中,两台中心间距为 65 毫米的相机借助金属板固定。作为一个嵌入式系统,在 Jeston Nano 单板计算机上使用 C++ 语言和 OpenCv 库建立了一个由两台相机支持的工作平面。在这个平面上,使用简单的边缘检测算法方法,通过使用数学计算方法对两台摄像机获得的图像进行像素计算,计算出视场中物体的距离,并用模拟测量仪对计算值进行验证。在研究中发现,由于边缘算法的不足,当物体的定位距离超过 20 厘米时,计算值的误差范围会增大,而当计算值超过 20 厘米时,由于环境因素的影响,会出现不同程度的偏差。作为一个嵌入式系统,使用 C++ 语言和 OpenCv 库在 Jeston Nano 单板计算机上建立了一个工作平面,上面有两个摄像头。在这个平面上,使用简单的边缘检测算法方法,通过对两台摄像机获得的图像进行数学计算,利用摄像机上的像素计算来计算视场中物体的距离,并对模拟测量仪计算出的数值进行验证。在研究中发现,由于环境因素的影响,20 厘米及以上的数值会出现不同程度的偏差,由于边缘算法的不足,计算值的误差范围会增大。
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引用次数: 0
Classification of Osmancik and Cammeo Rice Varieties using Deep Neural Networks 基于深度神经网络的水稻品种分类
Umit Ilhan, Ahmet Ilhan, K. Uyar, E. Iseri
Rice is one of the most widely consumed grains in the world. It is globally known that countries in southern Asia are the ones that mostly produce and also consume this particular type of grain. About 800 million tons of rice in many varieties is produced in the world every year. Each variety has its unique characteristics. This study covers research on the classification of Osmancik and Cammeo rice varieties using Deep Neural Networks (DNNs). There are 3810 numerical data of which 2180 belong to Osmancik and 1630 to Cammeo in the University of California Irvine (UCI) Rice (Osmancik and Cammeo) Data Set that is used in this work. The data is subjected to a normalization process which improves the performance of the multilayer neural networks. The performance of this study is measured thru calculating accuracy, sensitivity, specificity, precision, F1-score, NPV, FPR, FDR and, FNR. The overall success rate of this study is found to be 93.04%.
大米是世界上消费最广泛的谷物之一。众所周知,南亚国家是主要生产和消费这种特殊谷物的国家。世界上每年大约生产8亿吨品种繁多的大米。每个品种都有其独特的特点。本研究利用深度神经网络(DNNs)对Osmancik和Cammeo水稻品种进行分类研究。在加州大学欧文分校(UCI) Rice (Osmancik and Cammeo) data Set中有3810个数值数据,其中2180个属于Osmancik, 1630个属于Cammeo。数据经过归一化处理,提高了多层神经网络的性能。通过计算准确性、敏感性、特异性、精密度、f1评分、NPV、FPR、FDR和FNR来衡量本研究的效果。本研究的总体成功率为93.04%。
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引用次数: 1
Comparison of String and Central Inverter for 10MW PV Plant 10MW光伏电站串逆变器与中央逆变器的比较
B. Atasoy, S. S. Tezcan
In Turkey, solar power technology is quickly advancing, and investors are interested in establishing solar power plant. With the support of YEKDEM(Turkish Renewable Energy Resources Support Mechanism) and YEKA(Regulation on Renewable Energy Zones) mechanisms implemented by the state, solar investments have increased with a very serious momentum in recent years. With the recently announced YEKA GES-4 and YEKA GES-5 projects we foresee that the investments in solar power plants in Turkey will increase rapidly in the future. There is a difference in investment operation and maintenance costs, and operation efficiency of grid-tie inverter technology between string and central inverter. In this stud, we will find the optimum inverter selection by performing cost analysis and annual production with string and central inverter in 10 MW solar power plant.
在土耳其,太阳能技术正在迅速发展,投资者对建立太阳能发电厂很感兴趣。在国家实施的YEKDEM(土耳其可再生能源支持机制)和YEKA(可再生能源区监管)机制的支持下,太阳能投资近年来以非常严重的势头增长。随着最近宣布的YEKA GES-4和YEKA GES-5项目,我们预计未来土耳其太阳能发电厂的投资将迅速增加。串式逆变器与集中式逆变器并网逆变器技术在投资、运行维护费用、运行效率等方面存在差异。在本研究中,我们将通过对10 MW太阳能电站的串逆变器和中央逆变器进行成本分析和年生产,找到最佳的逆变器选择。
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引用次数: 3
Mobile Phone Price Class Prediction Using Different Classification Algorithms with Feature Selection and Parameter Optimization 基于特征选择和参数优化的不同分类算法的手机价格分类预测
Mustafa Çetın, Yunus Koç
Machine Learning (ML) algorithms are used in many fields such as finance, education, industry, medicine and e-commerce. ML algorithms show performance differences depending on the dataset and processing steps. Choosing the right algorithm, preprocessing and postprocessing methods has great importance to achieve good results. In this paper, Random Forest Classifier, Logistic Regression Classifier, Decision Tree Classifier, Linear Discriminant Analysis, K-Nearest Neighbor Classifier and SVC methods are compared to predict mobile phone price class. The "Mobile Price Classification" dataset which is taken from Kaggle.com is used to evaluate methods. Firstly, all values at the dataset are checked to verify that there are no missing values. After that, scaling is applied to dataset in order to obtain more relevant data for ML algorithms. Then, feature selection methods which reduce the computational cost by reducing the number of inputs are performed to get meaningful features. Finally, the parameters of classification algorithms are tuned to improve the system accuracy. According to obtained results, it is seen that ANOVA f-test feature selection method is more convenient for this dataset. It gives satisfying accuracy with a minimum number of features. It is also seen that the SVC classifier has the highest test accuracy compared to other models.
机器学习(ML)算法应用于金融、教育、工业、医药和电子商务等诸多领域。机器学习算法根据数据集和处理步骤显示性能差异。选择合适的算法、预处理和后处理方法对获得良好的效果至关重要。本文比较了随机森林分类器、逻辑回归分类器、决策树分类器、线性判别分析、k近邻分类器和SVC方法对手机价格分类的预测效果。从Kaggle.com获取的“移动价格分类”数据集用于评估方法。首先,检查数据集上的所有值,以验证没有缺失值。之后,对数据集进行缩放,以获得更多与ML算法相关的数据。然后,采用特征选择方法,通过减少输入数量来降低计算成本,从而获得有意义的特征。最后,对分类算法的参数进行了调整,以提高系统的准确率。从得到的结果可以看出,方差分析f检验特征选择方法对于该数据集更为方便。它用最少的特征给出了令人满意的精度。还可以看出,与其他模型相比,SVC分类器具有最高的测试精度。
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引用次数: 3
期刊
2021 5th International Symposium on Multidisciplinary Studies and Innovative Technologies (ISMSIT)
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