- Wenzhou Wu;Zhi Liu;Jun Zheng;Yuhua Zuo;Buwen Cheng;
A novel lateral Ge/Si avalanche photodiode without a charge region is investigated herein using device physical simulation. High field is provided by the band-gap barrier and build-in field at the Ge/Si interface in the vertical direction. Modulating the Si mesa thickness(0-0.4 μm) and impurity concentration of the intrinsic Si substrate(1×10~(16)-4×10~(16)cm~(-3)) strengthens the electric field confinement in the substrate region and provides a high avalanche multiplication in the Si region. When the Si mesa thickness is 0.3 μm, and the impurity concentration of the Si substrate is 2×10~(16) cm~(-3), the Lateral Avalanche PhotoDiode(LAPD) exhibits a peak gain of 246 under 1.55 μm incident light power of -22.2 dBm, which increases with decreasing light intensity.
2019年01期 v.24 1-8页 [查看摘要][在线阅读][下载 1069K] [下载次数：34 ] |[网刊下载次数：0 ] |[引用频次：5 ] |[阅读次数：0 ] - Dawid Po?ap;Marcin Wozniak;
The amount of digital data is increasing every day. At every step of our daily lives, we deal with technologies in which our data are stored(e.g., mobile phones and laptops), and this is one of the main reasons for the design of various types of encryption and user identity verification algorithms. These algorithms are meant not only to fulfill the desire of protecting data but also to address the possibility of granting access of specific digital data to selected individuals. This process brings with it the problem of identity verification. This paper discusses the problem of voice verification and presents a voice verification method based on artificial intelligence methods.Numerous tests are performed herein to demonstrate the effectiveness of the presented solution. The research results are shown and discussed in terms of the advantages and disadvantages of the solution.
2019年01期 v.24 9-17页 [查看摘要][在线阅读][下载 1117K] [下载次数：59 ] |[网刊下载次数：0 ] |[引用频次：8 ] |[阅读次数：0 ] - Yadong Huang;Yueting Chai;Yi Liu;Jianping Shen;
E-commerce, driven by computer and internet technology, has experienced a significant growth in almost all fields during the past two decades. E-commerce has significantly changed the rules of business. Numerous research institutions and enterprises have made e-commerce more intelligent and convenient. Here, we propose a novel prototype of next-generation e-commerce platform with an architecture framework and theoretical models.Each subject, including the individual, enterprise, and administrative department, has his/her personalized portal to complete the subject information synchronization, supply release, demand satisfaction, and social contact. By using the personalized portal, instead of the traditional trading platform, the consumers and suppliers can complete intelligent matching transactions without intermediate traders. Moreover, the overall transaction process can be reviewed, making the transaction safer, more transparent, and more interesting. Moreover, the interconnected personalized portals solve the isolated islands of information, and the counterparts support parallel processing.Thus, this may improve the operating efficiency of the entire society.
2019年01期 v.24 18-29页 [查看摘要][在线阅读][下载 828K] [下载次数：125 ] |[网刊下载次数：0 ] |[引用频次：8 ] |[阅读次数：0 ] - Hongli Zhang;Cong Wang;Wenhui Fan;
Dynamic Reactive Power Optimization(DRPO) is a large-scale, multi-period, and strongly coupled nonlinear mixed-integer programming problem that is difficult to solve directly. First, to handle discrete variables and switching operation constraints, DRPO is formulated as a nonlinear constrained two-objective optimization problem in this paper. The first objective is to minimize the real power loss and the Total Voltage Deviations(TVDs), and the second objective is to minimize incremental system loss. Then a Filter Collaborative State Transition Algorithm(FCSTA) is presented for solving DRPO problems. Two populations corresponding to two different objectives are employed. Moreover, the filter technique is utilized to deal with constraints. Finally, the effectiveness of the proposed method is demonstrated through the results obtained for a 24-hour test on Ward & Hale 6 bus, IEEE 14 bus, and IEEE 30 bus test power systems. To substantiate the effectiveness of the proposed algorithms, the obtained results are compared with different approaches in the literature.
2019年01期 v.24 30-43页 [查看摘要][在线阅读][下载 2393K] [下载次数：64 ] |[网刊下载次数：0 ] |[引用频次：8 ] |[阅读次数：0 ] - Xiangyu Meng;Gaochao Xu;Tingting Guo;Yongjian Yang;Wenxu Shen;Kuo Zhao;
The lack of continuous connectivity and a complete path from source to destination makes node communication quite difficult in Delay-Tolerant Networks(DTNs). Most studies focus on routing problems in idealized network environments without considering social properties. Communication devices are carried by individuals in many DTNs; therefore, DTNs are unique social networks to some extent. To design efficient routing protocols for DTNs, it is important to analyze their social properties. In this paper, a more accurate and comprehensive metric for detecting the quality of the relationships between nodes is proposed, by considering the contact time, contact frequency, and contact regularity. An overlapping hierarchical community detection method is designed based on this new metric, and a tree structure is built. Furthermore, we exploit the overlapping community structure and the tree structure to provide message-forwarding paths from the source node to the destination node.The simulation results show that our Routing method based on Overlapping hierarchical Community Detection(ROCD) achieves better delivery rate than SimBet and Bubble Rap, the classic routing protocols, without affecting the average delay.
2019年01期 v.24 44-51页 [查看摘要][在线阅读][下载 793K] [下载次数：32 ] |[网刊下载次数：0 ] |[引用频次：7 ] |[阅读次数：0 ] - Weiwei Jiang;Lin Zhang;
Traffic forecasting has been an active research field in recent decades, and with the development of deeplearning technologies, researchers are trying to utilize deep learning to achieve tremendous improvements in traffic forecasting, as it has been seen in other research areas, such as speech recognition and image classification. In this study, we summarize recent works in which deep-learning methods were applied for geospatial data-based traffic forecasting problems. Based on the insights from previous works, we further propose a deep-learning framework,which transforms geospatial data to images, and then utilizes the state-of-the-art deep-learning methodologies such as Convolutional Neural Network(CNN) and residual networks. To demonstrate the simplicity and effectiveness of our framework, we present a formulation of the New York taxi pick-up/drop-off forecasting problem, and show that our framework significantly outperforms traditional methods, including Historical Average(HA) and AutoRegressive Integrated Moving Average(ARIMA).
2019年01期 v.24 52-64页 [查看摘要][在线阅读][下载 2091K] [下载次数：149 ] |[网刊下载次数：0 ] |[引用频次：42 ] |[阅读次数：0 ] - Yuzhu Cheng;Weiping Wang;Jianxin Wang;Haodong Wang;
Firewalls are crucial elements that enhance network security by examining the field values of every packet and deciding whether to accept or discard a packet according to the firewall policies. With the development of networks, the number of rules in firewalls has rapidly increased, consequently degrading network performance.In addition, because most real-life firewalls have been plagued with policy conflicts, malicious traffics can be allowed or legitimate traffics can be blocked. Moreover, because of the complexity of the firewall policies, it is very important to reduce the number of rules in a firewall while keeping the rule semantics unchanged and the target firewall rules conflict-free. In this study, we make three major contributions. First, we present a new approach in which a geometric model, multidimensional rectilinear polygon, is constructed for the firewall rules compression problem.Second, we propose a new scheme, Firewall Policies Compression(FPC), to compress the multidimensional firewall rules based on this geometric model. Third, we conducted extensive experiments to evaluate the performance of the proposed method. The experimental results demonstrate that the FPC method outperforms the existing approaches, in terms of compression ratio and efficiency while maintaining conflict-free firewall rules.
2019年01期 v.24 65-76页 [查看摘要][在线阅读][下载 1481K] [下载次数：53 ] |[网刊下载次数：0 ] |[引用频次：1 ] |[阅读次数：0 ] - Yu Liu;Shuting Dong;Mingming Lu;Jianxin Wang;
Reserve allocation is a significant problem faced by commercial banking businesses every day. To satisfy the cash requirement of customers and abate the vault cash pressure, commercial banks need to appropriately allocate reserves for each bank outlet. Excessive reserve would impact the revenue of bank outlets. Low reserves cannot guarantee the successful operation of bank outlets. Considering the reserve requirement is effected by the past cash balance, we deal the reserve allocation problem as a time series prediction problem, and the Long Short Time Memory(LSTM) network is adapted to solve it. In addition, the proposed LSTM prediction model regards date property, which can affect the cash balance, as a primary factor. The experiment results show that our method outperforms some existing traditional methods.
2019年01期 v.24 77-85页 [查看摘要][在线阅读][下载 3806K] [下载次数：211 ] |[网刊下载次数：0 ] |[引用频次：30 ] |[阅读次数：0 ] - Guorui Li;Sancheng Peng;Cong Wang;Jianwei Niu;Ying Yuan;
As one of the key operations in Wireless Sensor Networks(WSNs), the energy-efficient data collection schemes have been actively explored in the literature. However, the transform basis for sparsifing the sensed data is usually chosen empirically, and the transformed results are not always the sparsest. In this paper, we propose a Data Collection scheme based on Denoising Autoencoder(DCDA) to solve the above problem. In the data training phase, a Denoising AutoEncoder(DAE) is trained to compute the data measurement matrix and the data reconstruction matrix using the historical sensed data. Then, in the data collection phase, the sensed data of whole network are collected along a data collection tree. The data measurement matrix is utilized to compress the sensed data in each sensor node, and the data reconstruction matrix is utilized to reconstruct the original data in the sink.Finally, the data communication performance and data reconstruction performance of the proposed scheme are evaluated and compared with those of existing schemes using real-world sensed data. The experimental results show that compared to its counterparts, the proposed scheme results in a higher data compression rate, lower energy consumption, more accurate data reconstruction, and faster data reconstruction speed.
2019年01期 v.24 86-96页 [查看摘要][在线阅读][下载 3343K] [下载次数：60 ] |[网刊下载次数：0 ] |[引用频次：26 ] |[阅读次数：0 ] - Dingyuan Li;Fu Liu;Junfei Qiao;Rong Li;
Echo State Network(ESN) is a recurrent neural network with a large, randomly generated recurrent part called the dynamic reservoir. Only the output weights are modified during training. However, proper balancing of the trade-off between the structure and performance for ESN remains a difficult task. In this paper, a structure optimized method for ESN based on contribution is proposed to simplify its network structure and improve its performance.First, we evaluate the contribution of reservoir neurons. Second, we present a pruning mechanism to remove the unimportant connection weights of reservoir neurons with low contribution. Finally, the new output weights are learned with the pseudo inverse method. The novel optimized ESN, named C-ESN, is tested on a Lorenz chaotic time-series prediction and an actual municipal sewage treatment system. The simulation results show that the C-ESN can have better prediction and generalization performance than ESN.
2019年01期 v.24 97-105页 [查看摘要][在线阅读][下载 1593K] [下载次数：51 ] |[网刊下载次数：0 ] |[引用频次：12 ] |[阅读次数：0 ] - Xingshen Song;Yuexiang Yang;Yu Jiang;
Inverted indexes are widely adopted in the vast majority of information systems. Growing requirements for efficient query processing have motivated the development of various compression techniques with different spacetime characteristics. Although a single encoder yields a relatively stable point in the space-time tradeoff curve,flexibly transforming its characteristic along the curve to fit different information retrieval tasks can be a better way to prepare the index. Recent research comes out with an idea of integrating different encoders within the same index,namely, exploiting access skewness by compressing frequently accessed regions with faster encoders and rarely accessed regions with succinct encoders, thereby improving the efficiency while minimizing the compressed size.However, these methods are either inefficient or result in coarse granularity. To address these issues, we introduce the concept of bicriteria compression, which aims to formalize the problem of optimally trading the compressed size and query processing time for inverted index. We also adopt a Lagrangian relaxation algorithm to solve this problem by reducing it to a knapsack-type problem, which works in O(n log n)time and O(n)space, with a negligible additive approximation. Furthermore, this algorithm can be extended via dynamic programming pursuing improved query efficiency. We perform an extensive experiment to show that, given a bounded time/space budget, our method can optimally trade one for another with more efficient indexing and query performance.
2019年01期 v.24 106-122页 [查看摘要][在线阅读][下载 861K] [下载次数：19 ] |[网刊下载次数：0 ] |[引用频次：1 ] |[阅读次数：0 ] <正>Tsinghua Science and Technology (Tsinghua Sci Technol), an academic journal sponsored by Tsinghua University,is publish,ed bimonthly. This journal aims at presenting the up-to-date scientific achievements with high creativity and great significance in computer and electronic engineering. Contributions all over the world are welcome.Tsinghua Sci Technol is indexed by SCI, Engineering index (Ei, USA), INSPEC, SA, Cambridge Abstract, and other abstracting indexes.Manuscripts are selected for publication according to the editorial assessment of their suitability and evaluation
2019年01期 v.24 123页 [查看摘要][在线阅读][下载 528K] [下载次数：11 ] |[网刊下载次数：0 ] |[引用频次：0 ] |[阅读次数：0 ]