Journal of Electronic Science and Technology最新文献

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ECC-Based RFID Authentication Protocol 基于ecc的RFID认证协议

Q1 Engineering

Journal of Electronic Science and Technology

Pub Date : 2021-01-01 DOI: 10.11989/JEST.1674-862X.70517019

Xingchun Yang, Chunxiang Xu, C. Li

The radio frequency identification (RFID) technology has been widely used so far in industrial and commercial applications. To develop the RFID tags that support elliptic curve cryptography (ECC), we propose a scalable and mutual authentication protocol based on ECC. We also suggest a tag privacy model that provides adversaries exhibiting strong abilities to attack a tag’s privacy. We prove that the proposed protocol preserves privacy under the privacy model and that it meets general security requirements. Compared with other recent ECC-based RFID authentication protocols, our protocol provides tag privacy and performs the best under comprehensive evaluation of tag privacy, tag computation cost, and communications cost.

射频识别(RFID)技术目前已广泛应用于工业和商业领域。为了开发支持椭圆曲线加密的RFID标签，提出了一种基于椭圆曲线加密的可扩展互认证协议。我们还提出了一种标签隐私模型，该模型为攻击者提供了攻击标签隐私的强大能力。我们证明了所提出的协议在隐私模型下保持了隐私，并且满足一般的安全要求。与目前其他基于ecc的RFID认证协议相比，我们的协议提供了标签保密性，并在标签保密性、标签计算成本和通信成本的综合评估下表现最佳。

引用次数: 0

Smart Meter Development for Cloud-Based Home Electricity Monitor System 基于云的家庭用电监测系统的智能电表开发

Q1 Engineering

Journal of Electronic Science and Technology

Pub Date : 2021-01-01 DOI: 10.11989/JEST.1674-862X.90616103

Y. Chen, S. S. Berutu, Yue Wang

Α cloud-based home electricity data-monitoring system, which is based on an Arduino Mega controller, is proposed for monitoring the electricity consumption (electrical power) and power quality (PQ) in home. This system is also capable of monitoring the fundamental frequency and supply-voltage transients to ensure that the appliances operate in a safe operation range. The measured data (voltage and current) are transmitted through a WiFi device between the Arduino controller and server. The transmission control protocol (TCP) server is set up to acquire the high-data transmission rate. The server system immediately displays the calculated parameters and the waveform of the acquired signal. A comparison with a standard measurement device shows that the proposed system, which can be built at a low cost, exhibits the same functions as a factory product.

提出了一种基于Arduino Mega控制器的基于云的家庭用电数据监测系统Α，用于监测家庭的用电量(电能)和电能质量(PQ)。该系统还能够监测基频和电源电压瞬变，以确保设备在安全运行范围内运行。测量的数据(电压和电流)通过WiFi设备在Arduino控制器和服务器之间传输。建立传输控制协议(TCP)服务器以获得高数据传输速率。服务器系统立即显示计算出的参数和采集到的信号波形。与标准测量装置的比较表明，该系统可以以低成本构建，具有与工厂产品相同的功能。

引用次数: 2

Comparative Study of 10-MW High-Temperature Superconductor Wind Generator with Overlapped Field Coil Arrangement 重叠场线圈布置的10mw高温超导风力发电机的比较研究

Q1 Engineering

Journal of Electronic Science and Technology

Pub Date : 2021-01-01 DOI: 10.11989/JEST.1674-862X.6110117

Z. Jiang, Jiangping Hu

The electromagnetic characteristics and iron loss of a high-temperature superconductor wind generator (HWG) equipped with an overlapped field coil arrangement (OFCA) are studied by comparing with the one equipped with the conventional field coil arrangement (CFCA). Through a quantitative analysis, it was found that HWG with OFCA exhibits better electromagnetic characteristics than HWG with CFCA and can reduce the iron loss by eliminating the magnetic flux sag caused by the adjacent field coil sides with the same current flow direction. In addition, the OFCA topology can further reduce the volume of the wind generator.

通过与常规场线圈布置(CFCA)的对比，研究了采用重叠场线圈布置(OFCA)的高温超导风力发电机(HWG)的电磁特性和铁损。通过定量分析，发现OFCA的HWG比CFCA的HWG具有更好的电磁特性，并且可以通过消除电流流向相同的相邻场线圈侧引起的磁通垂降来降低铁损耗。此外，OFCA拓扑结构可以进一步减小风力发电机的体积。

引用次数: 0

Characteristic Length of Metallic Nanorods under Physical Vapor Deposition 物理气相沉积下金属纳米棒的特征长度

Q1 Engineering

Journal of Electronic Science and Technology

Pub Date : 2021-01-01 DOI: 10.11989/JEST.1674-862X.90418013

Kai-Feng Jun, Bojun Wang, Haiyuan Chen

By using physical vapor deposition (PVD) to grow metallic nanorods, the characteristic length is controllable, which can be identified by two different growth modes: Mode I and Mode II. In Mode I, the growth of metallic nanorods is dominated by the monolayer surface steps. Whereas in Mode II, the growth mechanism is mainly determined by the multilayer surface steps. In this work, we focused on the analysis of the physical process of Mode I, in which the adatoms diffuse on the monolayer surface at beginning, then diffuse down to the next monolayer surface, and finally result in the metallic nanorods growth. Based on the physical process, both the variations of the characteristic length and the numerical solutions were theoretically proposed. In addition, the two-dimensional (2D) lattice kinetic Monte Carlo simulations were employed to verify the theoretical derivation of the metallic nanorods growth. Our results pay a new way for modifying the performance of metallic nanorods-based applications and devices.

利用物理气相沉积(PVD)生长金属纳米棒，特征长度是可控的，可以通过模式I和模式II两种不同的生长模式来识别。在模式1中，金属纳米棒的生长主要由单层表面台阶控制。而在模式II中，生长机制主要由多层表面台阶决定。在这项工作中，我们重点分析了模式一的物理过程，即附着原子开始在单层表面扩散，然后向下扩散到下一个单层表面，最终导致金属纳米棒的生长。从物理过程出发，从理论上提出了特征长度的变化规律和数值解。此外，利用二维晶格动力学蒙特卡罗模拟验证了金属纳米棒生长的理论推导。我们的研究结果为改进基于金属纳米棒的应用和器件的性能提供了一条新的途径。

引用次数: 0

Computational Intelligence Prediction Model Integrating Empirical Mode Decomposition, Principal Component Analysis, and Weighted k -Nearest Neighbor 结合经验模态分解、主成分分析和加权k近邻的计算智能预测模型

Q1 Engineering

Journal of Electronic Science and Technology

Pub Date : 2020-12-25 DOI: 10.11989/JEST.1674-862X.80124016

Lillian H. Tang, Heping Pan, Yiyong Yao

On the basis of machine leaning, suitable algorithms can make advanced time series analysis. This paper proposes a complex k-nearest neighbor (KNN) model for predicting financial time series. This model uses a complex feature extraction process integrating a forward rolling empirical mode decomposition (EMD) for financial time series signal analysis and principal component analysis (PCA) for the dimension reduction. The information-rich features are extracted then input to a weighted KNN classifier where the features are weighted with PCA loading. Finally, prediction is generated via regression on the selected nearest neighbors. The structure of the model as a whole is original. The test results on real historical data sets confirm the effectiveness of the models for predicting the Chinese stock index, an individual stock, and the EUR/USD exchange rate.

在机器学习的基础上，适当的算法可以进行高级的时间序列分析。本文提出了一种用于预测金融时间序列的复杂k近邻（KNN）模型。该模型使用复杂特征提取过程，该过程集成了用于金融时间序列信号分析的前向滚动经验模式分解（EMD）和用于降维的主成分分析（PCA）。提取信息丰富的特征，然后将其输入到加权KNN分类器，在该分类器中利用PCA加载对特征进行加权。最后，通过对所选择的最近邻居的回归来生成预测。整个模型的结构是独创的。对真实历史数据集的测试结果证实了模型预测中国股指、个股和欧元/美元汇率的有效性。

引用次数: 2

Data Bucket-Based Fragment Management for Solid State Drive Storage System 基于数据桶的固态硬盘存储系统碎片管理

Q1 Engineering

Journal of Electronic Science and Technology

Pub Date : 2020-12-25 DOI: 10.11989/JEST.1674-862X.80113010

Wei Jiang, Junlong Wang, Jinyu Zhan, Jinghuan Yu, Haibo Hu

The current storage mechanism considered little in data’s keeping characteristics. These can produce fragments of various sizes among data sets. In some cases, these fragments may be serious and harm system performance. In this paper, we manage to modify the current storage mechanism. We introduce an extra storage unit called data bucket into the classical data manage architecture. Next, we modify the data manage mechanism to improve our designs. By keeping data according to their visited information, both the number of fragments and the fragment size are greatly reduced. Considering different data features and storage device conditions, we also improve the solid state drive (SSD) lifetime by keeping data into different spaces. Experiments show that our designs have a positive influence on the SSD storage density and actual service time.

现有的存储机制很少考虑数据的保存特性。这些可以在数据集之间产生不同大小的片段。在某些情况下，这些碎片可能会严重影响系统性能。在本文中，我们设法修改当前的存储机制。我们在经典的数据管理架构中引入了一个称为数据桶的额外存储单元。接下来，我们修改数据管理机制来改进我们的设计。通过按访问信息保存数据，大大减少了分片的数量和分片的大小。考虑到不同的数据特性和存储设备条件，我们还通过将数据保存在不同的空间来提高固态硬盘(SSD)的使用寿命。实验表明，我们的设计对SSD的存储密度和实际使用时间有积极的影响。

引用次数: 0

Review on dynamic bandwidth allocation of GPON and EPON GPON和EPON的动态带宽分配研究进展

Q1 Engineering

Journal of Electronic Science and Technology

Pub Date : 2020-12-01 DOI: 10.1016/j.jnlest.2020.100044

Theresal Thangappan , Brintha Therese , Adi Suvarnamma , Gadda Sai Swapna

The passive optical network (PON) technology has been drastically improved in recent years. In spite of using the optical technology, the utilization of the entire bandwidth is a very challenging task. The main categories of PON are the Ethernet passive optical network (EPON) and gigabit passive optical network (GPON). These two networks use the dynamic bandwidth allocation (DBA) algorithm to attain the maximum usage of bandwidth, which is provided in the network dynamically according to the need of the customers with the support of the service level agreement (SLA). This paper will provide a clear review about the DBA algorithm of both technologies as well as the comparison.

无源光网络(PON)技术近年来有了很大的发展。尽管采用了光学技术，但整个带宽的利用是一项非常具有挑战性的任务。PON主要分为以太网无源光网络(EPON)和千兆无源光网络(GPON)。这两种网络都使用动态带宽分配(DBA)算法实现带宽的最大利用，在服务水平协议SLA (service level agreement)的支持下，根据客户的需求动态提供网络中的带宽。本文将对这两种技术的DBA算法进行综述，并进行比较。

引用次数: 15

An Improved Active Islanding Detection Technique for Multi-Inverter Power System 一种改进的多逆变电源系统有源孤岛检测技术

Q1 Engineering

Journal of Electronic Science and Technology

Pub Date : 2020-12-01 DOI: 10.11989/JEST.1674-862X.80831011

Zhang Jie, Yuhua Cheng, Kai Chen, Gen Qiu

Due to the increased penetration of multi-inverter distributed generation systems (DGs), different DGs technologies, inverter control methods, and other inverter functions are challenging the capabilities of islanding detection. In addition, multi-inverter networks connecting the distribution system point of common coupling (PCC) create islanding at paralleling inverters, which adds on to the vulnerability of islanding detection. Furthermore, available islanding detection must overcome more challenges from non-detection zones (NDZs) under reduced power mismatches. Therefore, in this study, a new method called parameter self-adapting active islanding detection was utilized to minimize the dilution effect and reduce the non-detecting zones in multi-inverter power systems. The method utilizes an active frequency drift (AFD) method and applies a positive feedback gain of parameter adaptive, which significantly minimizes the NDZs at parallel inverters. The simulation and experimental outcomes indicate that the proposed method can effectively weaken the dilution effect in multi-inverter networks connecting the distribution system PCC.

由于多逆变器分布式发电系统(dg)的普及，不同的dg技术、逆变器控制方法和其他逆变器功能对孤岛检测能力提出了挑战。此外，连接配电系统共耦合点(PCC)的多逆变器网络在并联逆变器处造成孤岛，增加了孤岛检测的脆弱性。此外，在减少功率失配的情况下，可用的孤岛检测必须克服更多来自非检测区(NDZs)的挑战。因此，本研究采用一种新的参数自适应主动孤岛检测方法来减小多逆变器电力系统的稀释效应，减少无检测区。该方法采用有源频率漂移(AFD)方法，并采用参数自适应的正反馈增益，显著降低了并联逆变器的ndz。仿真和实验结果表明，该方法可以有效地减弱配电系统PCC连接的多逆变器网络中的稀释效应。

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引用次数: 0

Conditional random field tracking model based on a visual long short term memory network 基于视觉长短期记忆网络的条件随机场跟踪模型

Q1 Engineering

Journal of Electronic Science and Technology

Pub Date : 2020-12-01 DOI: 10.1016/j.jnlest.2020.100031

Pei-Xin Liu, Zhao-Sheng Zhu, Xiao-Feng Ye, Xiao-Feng Li

In dense pedestrian tracking, frequent object occlusions and close distances between objects cause difficulty when accurately estimating object trajectories. In this study, a conditional random field tracking model is established by using a visual long short term memory network in the three dimensional space and the motion estimations jointly performed on object trajectory segments. Object visual field information is added to the long short term memory network to improve the accuracy of the motion related object pair selection and motion estimation. To address the uncertainty of the length and interval of trajectory segments, a multimode long short term memory network is proposed for the object motion estimation. The tracking performance is evaluated using the PETS2009 dataset. The experimental results show that the proposed method achieves better performance than the tracking methods based on independent motion estimation.

在密集的行人跟踪中，频繁的物体遮挡和物体之间的近距离会给准确估计物体轨迹带来困难。在本研究中，利用三维空间中的视觉长短期记忆网络和对目标轨迹段进行联合运动估计，建立了条件随机场跟踪模型。在长短期记忆网络中加入目标视野信息，提高运动相关目标对选择和运动估计的准确性。针对运动轨迹段长度和间隔的不确定性，提出了一种多模式长短期记忆网络进行目标运动估计。使用PETS2009数据集评估跟踪性能。实验结果表明，该方法比基于独立运动估计的跟踪方法具有更好的性能。

引用次数: 2

Light-Weight Selective Image Encryption for Privacy Preservation 用于隐私保护的轻量级选择性图像加密

Q1 Engineering

Journal of Electronic Science and Technology

Pub Date : 2020-10-14 DOI: 10.11989/JEST.1674-862X.80327011

Yi-Hui Chen, Eric Jui-Lin Lu, Chu-Fan Wang

To protect personal privacy and confidential preservation, access control is used to authorize legal users for safe browsing the authorized contents on photos. The access control generates an authorization rule according to each permission assignment. However, the general access control is inappropriate to apply in some social services (e.g., photos posted on Flickr and Instagram, personal image management in mobile phone) because of the increasing popularity of digital images being stored and managed. With low maintenance loads, this paper integrates the data hiding technique to propose an access control mechanism for privacy preservation. The proposed scheme changes the partial regions of a given image as random pads (called selective image encryption) and only allows the authorized people to remedy the random pads back to meaningful ones which are with similar visual qualities of original ones.

为了保护个人隐私和保密，通过访问控制对合法用户进行授权，使其能够安全地浏览照片上授权的内容。访问控制根据每次权限分配生成授权规则。但是，由于存储和管理数字图像的日益普及，一般的访问控制不适用于某些社会服务(例如，在Flickr和Instagram上发布的照片，手机中的个人图像管理)。在低维护负荷的情况下，结合数据隐藏技术，提出了一种保护隐私的访问控制机制。该方案将给定图像的部分区域改变为随机填充(称为选择性图像加密)，并且只允许授权人员将随机填充恢复为具有与原始图像相似视觉质量的有意义的填充。

引用次数: 0

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