歷年獲獎名單

2017人民網獎學金獲獎名單：

鄒立新、張曉麗
2017人民網優秀技術課題獲獎者名單：
一等獎：賈許亞、李亮亮
二等獎：辛雲星
三等獎：李峻峰

優秀論文一等獎（2）

賈許亞

A low overhead flow-holding algorithm in software-defined networks: 　　Software-Defined Networking (SDN) allows flexible and efficient management of networks. However, the limited capacity of flow tables in SDN switches hinders the deployment of SDN. In this paper, we propose a novel routing scheme to improve the efficiency of flow tables in SDNs. To efficiently use the routing scheme, we formulate an optimization problem with the objective to maximize the number of flows in the network, constrained by the limited flow table space in SDN switches. The problem is NP-hard, and we propose the K Similar Greedy Tree (KSGT) algorithm to solve it. We evaluate the performance of KSGT against “traditional” SDN solutions with real-world topologies and traffic. The results show that, compared to the existing solutions, KSGT can reduce about 60% of flow entries when processing the same amount of flows, and improve about 25% of the successful installation and forwarding flows under the same flow table space.; 詳細 >>

李亮亮

The Semantic Extension Analysis Based on Membership-based Model in Fault Detection Task: 　　AbstractAccurate fault prognosis of machine component is important to maintain industry operation system.Faults analysis can be very helpful in fault early warning and reducing maintenance cost. The goal of our work is to design an integrated approach of machine faults analysis. A method widely used is Fuzzy Neural Networks (FNNs), but such method lacks of flexibility. We present a semantic extension with Membershipbased Multi-dimension Hierarchical (MMH) neural network model to jointly include new feature selection approaches and generalized membership operators. MMH model is an adaptive model that employs modified KPCA and Back Propagation algorithm respectively. By introducing optimized KPCA that we can extract more semantic features of higher importance that are appropriate for fault diagnosis. Our prediction model is inspired by the traditional fixed membership. In our approach,an observing value will be segmented into multiple dimensions where each dimension captures deep structural information in the network. The transformation is updated by back propagation.The proposed approach takes advantage of membership thinking and benefits from large learning capacity of deep neural networks (DNNs). This is aiming to take advantage of membership thinking and neural network deep learning abilities. Experimental results on public datasets demonstrate the superiority of our model that has the character of faster convergence, which also improving the accuracy by an average of 5Index TermsFeature Selection;Modified KPCA; Back Propagation; Multi-dimension Hierarchical Neural Network; 詳細 >>

優秀論文二等獎（1）

辛雲星

TeenRead: An Adolescents Reading Recommendation System Towards Online Bibliotherapy: 　　Bibliotherapy has been proved to be an effective way to deal with adolescents psychological stress. Specific reading materials are provided to patients with physical or mental diseases for the purpose of prevention, healing, and rehabilitation. But traditional bibliotherapy requires professional staff with the background of both psychological and library services, which is quite demanding and labor consuming. Moreover, bibliotherapy based on paper books is getting ill-fitted in the present big data era. To address the limitations, this paper proposes an online reading recommendation system called TeenRead to carry out bibliotherapy for adolescents. TeenRead involves the management of users and articles, analysis of users' dynamic reading behaviors, as well as the recommendation based on users' stress categories, stress levels, and reading interests. The results of the user study on 10 volunteers show that, the average decrease of users' stress level is significantly dropped by 22% after a period of reading on TeenRead, which proves that TeenRead performs pretty well as a new method of bibliotherapy.; 詳細 >>

優秀論文三等獎（1）

李峻峰

VR技術及其新聞應用前景研究: 　　本文首先介紹了VR在新聞等各個領域的應用，並介紹了VR目前面臨的主要問題。為了解決這個問題，我們提出了基於自適應FEC編碼的VR傳輸協議MPFEC，可以充分利用多路徑的能力，並根據冗余包恢復丟失的數據包以降低時延，保証更好的VR的沉浸式用戶體驗，使VR在新聞領域廣泛使用成為可能。; 詳細 >>