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Comparison Between Milstein and Exact Coupling Methods using MATLAB for a Particular Two-Dimensional Stochastic Differential Equation 特定二维随机微分方程Milstein与精确耦合方法的MATLAB比较
IF 1.1 4区 计算机科学 Q2 Social Sciences Pub Date : 2020-11-01 DOI: 10.6688/JISE.202011_36(6).0006
Yousef Alnafisah
We compare Milstein and exact coupling methods for the strong approximation of solutions to stochastic differential equations (SDE), which are driven by Brownian motion. Both of these methods attain an order one convergence under the nondegeneracy assumption of the diffusion term for the exact coupling method. We also compare their implementation using MATLAB. A particular two-dimensional SDE is used in the implementation for comparing their results. Moreover, the performance of both methods and the amount of time required to obtain the result are also analyzed. It is interesting to mention that this comparison is very important in several areas, such as stochastic analysis, financial mathematics and some physical applications.
我们比较了米尔斯坦和精确耦合方法对布朗运动驱动的随机微分方程(SDE)强逼近解的求解。在精确耦合方法的扩散项不退化的假设下,这两种方法都达到了一阶收敛。我们还比较了它们在MATLAB中的实现。在实现中使用一个特定的二维SDE来比较它们的结果。此外,还分析了两种方法的性能和获得结果所需的时间。有趣的是,这种比较在一些领域是非常重要的,比如随机分析、金融数学和一些物理应用。
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引用次数: 0
Convolutional and Fully Connected Layer in DFN DFN中的卷积和全连通层
IF 1.1 4区 计算机科学 Q2 Social Sciences Pub Date : 2020-09-01 DOI: 10.6688/JISE.202009_36(5).0009
Mian Mian Lau, K. Lim
Deep feedforward network (DFN) is the general structure of many well-known deep neural networks (DNN) for image classification. The recent research emphasizes on going deeper and wider network architecture to achieve higher accuracy and lower misclassification rate. This paper provides a study and investigation on stacking three basic operation of neural layers, i.e. convolutional layer, pooling layer and fully connected layer. As a result, a new framework of convolutional deep feedforward network (C-DFN) is proposed in this paper. C-DFN performed significantly better than deep feedforward network (DFN), deep belief network (DBN), and convolutional deep belief network (C-DBN) in MNIST dataset, INRIA pedestrian dataset and Daimler pedestrian dataset. The convolutional layer acts as a trainable feature extractor improving the network performance significantly. Moreover, it reduced 14% of the trainable parameters in DFN. With the use of trainable activation function such as PReLU in the C-DFN, it achieves an average misclassification rate of 9.22% of the three benchmark datasets.
深度前馈网络(Deep feedforward network, DFN)是目前已知的用于图像分类的深度神经网络(Deep neural network, DNN)的一般结构。近年来的研究重点是深入和广泛的网络架构,以达到更高的准确率和更低的误分类率。本文对卷积层、池化层和全连接层这三种神经层的基本操作进行了研究和探讨。为此,本文提出了一种新的卷积深度前馈网络(C-DFN)框架。C-DFN在MNIST数据集、INRIA行人数据集和Daimler行人数据集上的表现明显优于深度前馈网络(DFN)、深度信念网络(DBN)和卷积深度信念网络(C-DBN)。卷积层作为可训练的特征提取器,显著提高了网络性能。此外,它减少了DFN中14%的可训练参数。在C-DFN中使用PReLU等可训练激活函数,实现了三个基准数据集的平均误分类率为9.22%。
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引用次数: 1
A Risk Assessment Approach of Hypertension Based on Mobile Crowd Sensing 基于移动人群感知的高血压风险评估方法
IF 1.1 4区 计算机科学 Q2 Social Sciences Pub Date : 2020-09-01 DOI: 10.6688/JISE.202009_36(5).0012
Huanhuan Zhao, Zuchang Ma, Yining Sun
Mobile crowd sensing (MCS) makes full use of the sensing and wireless communication capabilities of smart mobile devices to collect real-time information effectively. It makes it possible to monitor people's health condition in real time. Our health information collected through MCS can be used to improve healthcare service. Hypertension is a widespread chronic disease, and preventing hypertension can effectively reduce the incidence of cardiovascular disease. In this paper, we propose a hypertension risk assessment approach based on mobile crowd sensing, which allows for real time health monitoring and warning. In order to stimulate the enthusiasm of MCS volunteers, optimized communication model is used to reduce the communication cost of non-data-users. Additionally, the current hypertension risk status of patients will be feed back to them in real time. In our approach, binary logistic regression is used to select risk factors of hypertension, and then the risk factors are used as the inputs of BP neural network to construct the risk prediction model. Furthermore, the hypertension risk is further divided into low risk, medium risk and high risk through cumulative distribution function. 4498 samples from a community health service center in Hefei area were used to evaluate the performance of the proposed approach. The experimental results show that the proposed approach can provide real-time, effective monitoring and dynamic feedback of the hypertension risk, offering a novel clinical tool for the early warning of hypertension. The proposed approach also provides a general framework for risk assessment of other chronic diseases.
移动人群感知(MCS)充分利用智能移动设备的感知和无线通信能力,有效地收集实时信息。它使实时监测人们的健康状况成为可能。我们通过MCS收集的健康信息可用于改善医疗服务。高血压是一种广泛存在的慢性病,预防高血压可以有效降低心血管疾病的发生率。在本文中,我们提出了一种基于移动人群感知的高血压风险评估方法,该方法允许实时健康监测和警告。为了激发MCS志愿者的积极性,采用优化的通信模型来降低非数据用户的通信成本。此外,患者当前的高血压风险状况将实时反馈给他们。在我们的方法中,使用二元逻辑回归来选择高血压的危险因素,然后将这些危险因素作为BP神经网络的输入来构建风险预测模型。此外,通过累积分布函数将高血压风险进一步分为低风险、中风险和高风险。采用合肥地区某社区卫生服务中心的4498份样本对该方法的性能进行了评价。实验结果表明,该方法可以对高血压风险进行实时、有效的监测和动态反馈,为高血压早期预警提供了一种新的临床工具。拟议的方法还为其他慢性病的风险评估提供了一个总体框架。
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引用次数: 1
Rule Based Conversion of L A T E X Math Equations into Content MathML (CMML) 基于规则的L - T - X数学方程到内容MathML (cml)的转换
IF 1.1 4区 计算机科学 Q2 Social Sciences Pub Date : 2020-09-01 DOI: 10.6688/JISE.202009_36(5).0006
Sharaf Hussain, Samita Bai, S. Khoja
This paper discusses the formation of math grammar rules for LATEX math equations. These rules are used to generate Abstract Syntax Tree (AST) which extracts structural information from mathematical expressions given in LATEX format. Later AST is used to generate XML structure of mathematical expressions that make mathematical expressions machine-readable in heterogeneous environments. A rule-based algorithm is also proposed that converts LATEX math expressions into Content MathML (CMML), which produces semantic enrichment in web documents. The rules for writing LATEX math equations are formulated and implemented as LATEX Math Grammar (LMG), which are used for generating AST. Further, AST is converted into XML structure which is used to generate CMML encoding. Initially, the conversion algorithm is tested on 20 equations used in an NTCIR-12 math competition, then the algorithm is tested on NTCIR-12 Wikipedia-MathIR and ArXiv data sets. The results show that our algorithm is capable of converting LATEX complex equations into CMML extensively as compared to the existing ones as well as its time efficiency is better than contemporary systems.
本文讨论了LATEX数学方程数学语法规则的形成。这些规则用于生成抽象语法树(AST), AST从以LATEX格式给出的数学表达式中提取结构信息。后来使用AST生成数学表达式的XML结构,使数学表达式在异构环境中具有机器可读性。提出了一种基于规则的算法,将LATEX数学表达式转换为内容MathML (Content MathML),从而在web文档中产生语义丰富。LATEX数学公式的编写规则被表述为LATEX数学语法(LATEX math Grammar, LMG),用于生成AST,并将AST转换为XML结构,用于生成cml编码。首先,在ntcirr -12数学竞赛中使用的20个方程上测试了转换算法,然后在ntcirr -12 Wikipedia-MathIR和ArXiv数据集上测试了该算法。结果表明,与现有算法相比,该算法能够将LATEX复杂方程广泛地转换为cml,并且时间效率优于现有系统。
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引用次数: 1
Modelling of Charging Control Scheme for QZSI with Battery Topology 基于电池拓扑的QZSI充电控制方案建模
IF 1.1 4区 计算机科学 Q2 Social Sciences Pub Date : 2020-09-01 DOI: 10.6688/JISE.202009_36(5).0002
K. H. Law
Quasi Z-source inverter (qZSI) has been proven to be reliable for inverting DC electricity to AC. When compared with conventional two stage DC-AC boost inverter topology, qZSI is a single stage topology which can be simply constructed via connecting a quasi Z-source (qZS) impedance network in series with an H-bridge inverter. This resulted an attractive topology without needing any switching element and resistor in the DC-link. In this paper, the investigation of qZSI with battery topology is extended to regulate its output voltage from a fluctuating DC input source. Through extensive mathematic derivation, a control scheme which comprised of battery current controller, battery management algorithm, and electronic circuit breaker (ECB) algorithm, is proposed to achieve the aforementioned outcome plus ensuring the effectiveness of battery charging and discharging capability as well as prevention of over-charging and over-discharging of the battery according to the DC input voltage level. All theoretical findings are validated with simulation results using Matlab / Simulink software package.
准z源逆变器(qZSI)已被证明可以可靠地将直流电转换为交流电。与传统的两级直流-交流升压逆变器拓扑结构相比,qZSI是一种单级拓扑结构,可以通过将准z源(qZS)阻抗网络串联到h桥逆变器来简单地构建。这产生了一个有吸引力的拓扑结构,而不需要在直流链路中使用任何开关元件和电阻。本文将电池拓扑qZSI的研究扩展到从波动的直流输入源调节其输出电压。通过广泛的数学推导,提出了一种由电池电流控制器、电池管理算法和电子断路器(ECB)算法组成的控制方案,以实现上述结果,同时保证电池充放电能力的有效性,并根据直流输入电压水平防止电池过充过放。利用Matlab / Simulink软件包对所有理论结果进行了仿真验证。
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引用次数: 4
Vanishing Gradient Analysis in Stochastic Diagonal Approximate Greatest Descent Optimization 随机对角近似最大下降优化中的消失梯度分析
IF 1.1 4区 计算机科学 Q2 Social Sciences Pub Date : 2020-09-01 DOI: 10.6688/JISE.202009_36(5).0005
H. Tan, K. Lim
Deep learning neural network is often associated with high complexity classification problems by stacking multiple hidden layers between input and output. The measured error is backpropagated layer-by-layer in a network with gradual vanishing gradient value due to the differentiation of activation function. In this paper, Stochastic Diagonal Approximate Greatest Descent (SDAGD) is proposed to tackle the issue of vanishing gradient in the deep learning neural network using the adaptive step length derived based on the second-order derivatives information. The proposed SDAGD optimizer trajectory is demonstrated using three-dimensional error surfaces, i:e: (a) a hilly error surface with two local minima and one global minimum; (b) a deep Gaussian trench to simulate drastic gradient changes experienced with ravine topography and (c) small initial gradient to simulate a plateau terrain. As a result, SDAGD is able to converge at the fastest rate to the global minimum without the interference of vanishing gradient issue as compared to other benchmark optimizers such as Gradient Descent (GD), AdaGrad and AdaDelta. Experiments are tested on saturated and unsaturated activation functions using sequential added hidden layers to evaluate the vanishing gradient mitigation with the proposed optimizer. The experimental results show that SDAGD is able to obtain good performance in the tested deep feedforward networks while stochastic GD obtain worse misclassification error when the network has more than three hidden layers due to the vanishing gradient issue. SDAGD can mitigate the vanishing gradient by adaptively control the step length element in layers using the second-order information. At the constant training iteration setup, SDAGD with ReLU can achieve the lowest misclassification rate of 1.77% as compared to other optimization methods.
深度学习神经网络通常通过在输入和输出之间叠加多个隐藏层来解决高复杂性的分类问题。在梯度值逐渐消失的网络中,由于激活函数的微分,测量误差逐层反向传播。针对深度学习神经网络中梯度消失的问题,提出了基于二阶导数信息的自适应步长随机对角近似最大下降算法(SDAGD)。提出的SDAGD优化器轨迹使用三维误差曲面进行了演示,i:e:(a)一个具有两个局部最小值和一个全局最小值的丘陵误差曲面;(b)深高斯沟,模拟峡谷地形的剧烈梯度变化;(c)小初始梯度,模拟高原地形。因此,与其他基准优化器(如梯度下降(GD)、AdaGrad和AdaDelta)相比,SDAGD能够以最快的速度收敛到全局最小值,而不会受到梯度消失问题的干扰。在饱和和非饱和激活函数上进行了实验,使用顺序添加隐藏层来评估该优化器对消失梯度的缓解效果。实验结果表明,在所测试的深度前馈网络中,SDAGD能够获得较好的性能,而随机GD由于梯度消失问题,当网络隐藏层超过3层时,会产生较差的误分类误差。SDAGD利用二阶信息自适应控制层内的步长元素,减轻了梯度消失的影响。在恒训练迭代设置下,与其他优化方法相比,采用ReLU的SDAGD的误分类率最低,为1.77%。
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引用次数: 0
Transcultural Practices of International Students as Identity Performances in Digital Settings 国际学生的跨文化实践作为数字环境下的身份表演
IF 1.1 4区 计算机科学 Q2 Social Sciences Pub Date : 2020-08-27 DOI: 10.32674/jise.v9i2.2175
Osman Solmaz
Guided by an interdisciplinary approach, this study seeks to illustrate the digital practices of international speakers on social media. The practices of international users are especially valuable due to the presence of various audiences in their networks, some rarely researched. For this purpose, the study examines the social media practices of 16 international graduate students (IGSs), who experience a transnational mobility in the United States. The data is collected through semi-structured interviews with participants and their social media data. The analysis includes quantitative assessment of participants’ social media activities and qualitative analyses of interviews and digital practices. The findings of the study illustrate how individuals with transborder experiences engage in identity work by sharing transcultural content with a multitude of audiences in their networks. The study concludes that digital practices involving the transcultural flow of content present opportunities for IGSs to work and realign various facets of their identities.
在跨学科方法的指导下,本研究试图说明国际演讲者在社交媒体上的数字实践。国际用户的做法尤其有价值,因为他们的网络中有各种受众,其中一些受众很少被研究。为此,本研究调查了16名在美国经历跨国流动的国际研究生的社交媒体实践。数据是通过对参与者及其社交媒体数据的半结构化采访收集的。分析包括对参与者社交媒体活动的定量评估,以及对采访和数字实践的定性分析。这项研究的结果表明,有跨境经历的个人是如何通过在网络中与众多受众分享跨文化内容来从事身份认同工作的。该研究得出结论,涉及跨文化内容流的数字实践为IGS提供了工作和重新调整其身份各个方面的机会。
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引用次数: 0
Forging the ideal educated girl: the production of desirable subjects in Muslim South Asia. 塑造理想的受过教育的女孩:南亚穆斯林理想科目的生产。
IF 1.1 4区 计算机科学 Q2 Social Sciences Pub Date : 2020-08-19 DOI: 10.32674/jise.v9i2.1666
Taiwo Adenuga
This is a book about the history of Muslim girls/women in South Asia and their difficulties in acquiring an education.
这是一本关于南亚穆斯林女孩/妇女的历史和她们在获得教育方面的困难的书。
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引用次数: 1
Mindset, Heartset, and Skillset 心态、心态和技能
IF 1.1 4区 计算机科学 Q2 Social Sciences Pub Date : 2020-08-14 DOI: 10.32674/jise.v9isi.2810
Prince Paa-Kwesi Heto, H. Indangasi
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引用次数: 1
Role of Value Creating Education and Ubuntu Philosophy in Fostering Humanism in Africa 价值创造教育与Ubuntu哲学在非洲人文精神培育中的作用
IF 1.1 4区 计算机科学 Q2 Social Sciences Pub Date : 2020-08-11 DOI: 10.32674/jise.v9is(1).1857
M. Odari
Soka (value creating) education is a Japanese concept propounded by Tsunesaburo Makiguchi and further developed by Josei Toda and Daisaku Ikeda. This educational philosophy aims to foster individuals who can find meaning in their lives and contribute to the well-being of others to better society. Ubuntu, an African philosophy, espouses togetherness and collectivism. Like value creating education, Ubuntu promotes working for the good of all not solely the individual. Examining these two philosophies, this paper explored their role in promoting humanism. Focusing on the education system in Kenya, this paper investigated how the institutionalization of both philosophies can foster global citizens and realize a more humane Kenya. Furthermore, this paper illustrated the importance of educators as agents of change, aiding students to become global citizens who work towards building a more humanistic society. This paper concluded that integrating both value creating education and Ubuntu in the education system can serve as a tool to nurture individuals who will not only improve their quality of life but also contribute positively to promote a more just and prosperous world.
创价教育是日本的一个概念,由牧口宗三郎提出,由户田若成和池田大作进一步发展。这一教育理念旨在培养能够在生活中找到意义的人,并为他人的福祉做出贡献,从而改善社会。Ubuntu是一种非洲哲学,信奉团结和集体主义。就像创造价值的教育一样,Ubuntu提倡为所有人而不仅仅是个人的利益而工作。本文考察了这两种哲学,探讨了它们在促进人文主义方面的作用。本文以肯尼亚的教育系统为中心,探讨了这两种哲学的制度化如何培养全球公民,实现一个更人道的肯尼亚。此外,本文还阐述了教育工作者作为变革推动者的重要性,帮助学生成为致力于建设一个更加人性化社会的全球公民。本文得出的结论是,将创造价值的教育和Ubuntu纳入教育系统,可以作为培养个人的工具,这些人不仅可以提高生活质量,还可以为促进一个更加公正和繁荣的世界做出积极贡献。
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引用次数: 0
期刊
Journal of Information Science and Engineering
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