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| 1 | Machine Learning-Based Multi-Modal Information Perception for Soft Robotic Hands显示文摘This paper focuses on multi-modal Information Perception(IP)for Soft Robotic Hands(SRHs)using Machine Learning(ML)algorithms.A flexible Optical Fiber-based Curvature Sensor(OFCS)is fabricated,consisting of a Light-Emitting Diode(LED),photosensitive detector,and optical fiber.Bending the roughened optical fiber generates lower light intensity,which reflecting the curvature of the soft finger.Together with the curvature and pressure information,multi-modal IP is performed to improve the recognition accuracy.Recognitions of gesture,object shape,size,and weight are implemented with multiple ML approaches,including the Supervised Learning Algorithms(SLAs)of K-Nearest Neighbor(KNN),Support Vector Machine(SVM),Logistic Regression(LR),and the unSupervised Learning Algorithm(un-SLA)of K-Means Clustering(KMC).Moreover,Optical Sensor Information(OSI),Pressure Sensor Information(PSI),and Double-Sensor Information(DSI)are adopted to compare the recognition accuracies.The experiment results demonstrate that the proposed sensors and recognition approaches are feasible and effective.The recognition accuracies obtained using the above ML algorithms and three modes of sensor information are higer than 85 percent for almost all combinations.Moreover,DSI is more accurate when compared to single modal sensor information and the KNN algorithm with a DSI outperforms the other combinations in recognition accuracy. | Haiming Huang Junhao Lin Linyuan Wu Bin Fang Zhenkun Wen Fuchun Sun | 2020 | Tsinghua Science and Technology2020，25，2： | 4 |
| 2 | From similarity perspective: a robust collaborative filtering approach for service recommendations显示文摘Collaborative filtering (CF) is a technique commonly used for personalized recommendation and Web service quality-of-service (QoS) prediction. However, CF is vulnerable to shilling attackers who inject fake user profiles into the system. In this paper, we first present the shilling attack problem on CF-based QoS recommender systems for Web services. Then, a robust CF recommendation approach is proposed from a user similarity perspective to enhance the resistance of the recommender systems to the shilling attack. In the approach, the generally used similarity measures are analyzed, and the DegSim (the degree of similarities with top k neighbors) with those measures is selected for grouping and weighting the users. Then, the weights are used to calculate the service similarities/differences and predictions. We analyzed and evaluated our algorithms using WS-DREAM and Movielens datasets. The experimental results demonstrate that shilling attacks influence the prediction of QoS values, and our proposed features and algorithms achieve a higher degree of robustness against shilling attacks than the typical CF algorithms. | Min GAO Bin LING Linda YANG Junhao WEN Qingyu XIONG Shun LI | 2019 | Frontiers of Computer Science2019，13，2： | 2 |
| 3 | A QoS preference-based algorithm for service composition in service-oriented network 显示文摘 | Wei Zhou Junhao Wen Min Gao | 2013 | Optik-International Journal for Light and Electron Optics2013，，3： | 1 |
| 4 | A SOA-based servcie discovery framework in Internet of Things显示文摘 | Li Peng Dong Junping Wen Junhao | 2011 | Journal of Convergence Information Technology2011，6，9： | 1 |
| 5 | Semi-supervised Learning Combining Co-training with ActiveLearning 显示文摘 | ZHANG Yihao WEN Junhao WANG Xibin | 2014 | Expert Systems with Applications2014，41，5： | 1 |
| 6 | Serological AFP/Golgi protein 73 could be a new diagnostic parameter of hepatic diseases显示文摘 | Liyuan Tian Yu Wang Dabin Xu Junhao Gui Xingwang Jia Hongli Tong Xinyu Wen Zhennan Dong Yaping Tian | 2011 | Int J Cancer2011，，8： | 1 |
| 7 | A sort of metric model based on GA显示文摘 | Wen Junhao Zhang Yang Xu Chuanyun | 2006 | Dynamics of Continuous Discrete and Impulsive Systems Series A : Mathematical Analysis China2006，2006，： | 1 |
| 8 | Semi-supervised learning combining co-training with active learning 显示文摘 | Zhang Yihao Wen Junhao Wang Xibin | 2014 | Expert Systems with Applications2014，41，5： | 1 |
| 9 | Real estate price forecasting based on SVM optimized by PS0显示文摘 | Xibin Wang Junhao Wen Yihao Zhang | 2014 | Optik-International Journal for Light and Electron Optics2014，125，3： | 1 |
| 10 | Stimulated emission at 1.54 μm from erbium/oxygen-doped silicon-based light-emitting diodes显示文摘Silicon-based light sources, including light-emitting diodes(LEDs) and laser diodes(LDs) for information transmission, are urgently needed for developing monolithic integrated silicon photonics. Silicon with erbium ions(Er^(3+)) doped by ion implantation is considered a promising approach, but it suffers from an extremely low quantum efficiency. Here we report an electrically pumped superlinear emission at 1.54 μm from Er/O-doped silicon planar LEDs, which are produced by applying a new deep cooling process. Stimulated emission at room temperature is realized with a low threshold current of ~6 mA(~0.8 A∕cm^(2)). Time-resolved photoluminescence and photocurrent results have revealed the complex carrier transfer dynamics by relaxing electrons from the Si conduction band to the Er^(3+) ion. This picture differs from the frequently assumed energy transfer via electron–hole pair recombination of the silicon host. Moreover, the amplified emission from the LEDs is likely due to a quasi-continuous Er/O-related donor band created by the deep cooling technique. This work paves the way for fabricating superluminescent diodes or efficient LEDs at communication wavelengths based on rare-earth-doped silicon. | JIN HONG HUIMIN WEN JIAJING HE JINGQUAN LIU YAPING DAN JENS W.TOMM FANGYU YUE JUNHAO CHU CHUNGANG DUAN | 2021 | Photonics Research2021，9，5： | 0 |
| 11 | Mask guided diverse face image synthesis显示文摘Recent studies have shown remarkable success in face image generation task.However,existing approaches have limited diversity,quality and controllability in generating results.To address these issues,we propose a novel end-to-end learning framework to generate diverse,realistic and controllable face images guided by face masks.The face mask provides a good geometric constraint for a face by specifying the size and location of different components of the face,such as eyes,nose and mouse.The framework consists of four components:style encoder,style decoder,generator and discriminator.The style encoder generates a style code which represents the style of the result face;the generator translate the input face mask into a real face based on the style code;the style decoder learns to reconstruct the style code from the generated face image;and the discriminator classifies an input face image as real or fake.With the style code,the proposed model can generate different face images matching the input face mask,and by manipulating the face mask,we can finely control the generated face image.We empirically demonstrate the effectiveness of our approach on mask guided face image synthesis task. | Song SUN Bo ZHAO Muhammad MATEEN Xin CHEN Junhao WEN | 2022 | Frontiers of Computer Science2022，16，3： | 0 |
| 12 | Effort-aware cross-project just-in-time defect prediction framework for mobile apps显示文摘As the boom of mobile devices,Android mobile apps play an irreplaceable roles in people’s daily life,which have the characteristics of frequent updates involving in many code commits to meet new requirements.Just-in-Time(JIT)defect prediction aims to identify whether the commit instances will bring defects into the new release of apps and provides immediate feedback to developers,which is more suitable to mobile apps.As the within-app defect prediction needs sufficient historical data to label the commit instances,which is inadequate in practice,one alternative method is to use the cross-project model.In this work,we propose a novel method,called KAL,for cross-project JIT defect prediction task in the context of Android mobile apps.More specifically,KAL first transforms the commit instances into a high-dimensional feature space using kernel-based principal component analysis technique to obtain the representative features.Then,the adversarial learning technique is used to extract the common feature embedding for the model building.We conduct experiments on 14 Android mobile apps and employ four effort-aware indicators for performance evaluation.The results on 182 cross-project pairs demonstrate that our proposed KAL method obtains better performance than 20 comparative methods. | Tian CHENG Kunsong ZHAO Song SUN Muhammad MATEEN Junhao WEN | 2022 | Frontiers of Computer Science2022，16，6： | 0 |
| 13 | Thermoelectric Properties of n-type Full-Heusler Fe_(2-2x)Co_(2x) TiSn Prepared by an Ultra-fast Synthesis Process显示文摘Full-Heusler alloy Fe_(2)TiSn was predicted to be a potential thermoelectric material with high mechanical properties and stability.Fe_(2)TiSn was usually prepared by arc-melting followed by annealing for 2 weeks,which takes a long time and consumes a large amount of energy.In this paper,Fe_(2)TiSn was prepared by an ultra-fast method,self-propagating high-temperature synthesis (SHS) combined with spark plasma sintering.The bulk materials with uniform element distribution,well controlled composition and relative densities of over 97.5% were prepared.The undoped Fe_(2)TiSn samples show p-type transport behavior.Co was heavily doped at the Fe site to prepare n-type Fe_(2-2x)Co_(2x) TiSn samples.The thermoelectric properties measurements carried out on the Co-doped samples show a highest ZT=0.02 at 300 K,which is about tripe the performance of the pristine Fe_(2)TiSn.This study provides a new approach for the rapid and low-cost preparation of full-Heusler thermoelectric materials. | 赵东艳 陈艳宁 WANG Yubo ZHANG Haifeng FU Zhen WANG Shuaipeng YU Wen DU Jian WANG Wenhe QIU Junhao 鄢永高 | 2021 | Journal of Wuhan University of Technology(Materials Science)2021，36，4： | 0 |
| 14 | Monte Carlo Simulation-Based Robust Workflow Scheduling for Spot Instances in Cloud Environments显示文摘When deploying workflows in cloud environments,the use of Spot Instances(SIs)is intriguing as they are much cheaper than on-demand ones.However,Sls are volatile and may be revoked at any time,which results in a more challenging scheduling problem involving execution interruption and hence hinders the successful handling of conventional cloud workflow scheduling techniques.Although some scheduling methods for Sls have been proposed,most of them are no more applicable to the latest Sls,as they have evolved by eliminating bidding and simplifying the pricing model.This study focuses on how to minimize the execution cost with a deadline constraint when deploying a workflow on volatile Sls in cloud environments.Based on Monte Carlo simulation and list scheduling,a stochastic scheduling method called MCLS is devised to optimize a utility function introduced for this problem.With the Monte Carlo simulation framework,MCLS employs sampled task execution time to build solutions via deadline distribution and list scheduling,and then returns the most robust solution from all the candidates with a specific evaluation mechanism and selection criteria.Experimental results show that the performance of MCLS is more competitive comparedwithtraditionalalgorithms. | Quanwang Wu Jianzhao Fang Jie Zeng Junhao Wen Fengji Luo | 2024 | Tsinghua Science and Technology2024，29，1： | 0 |
| 15 | A Length-Adaptive Non-Dominated Sorting Genetic Algorithm for Bi-Objective High-Dimensional Feature Selection显示文摘As a crucial data preprocessing method in data mining,feature selection(FS)can be regarded as a bi-objective optimization problem that aims to maximize classification accuracy and minimize the number of selected features.Evolutionary computing(EC)is promising for FS owing to its powerful search capability.However,in traditional EC-based methods,feature subsets are represented via a length-fixed individual encoding.It is ineffective for high-dimensional data,because it results in a huge search space and prohibitive training time.This work proposes a length-adaptive non-dominated sorting genetic algorithm(LA-NSGA)with a length-variable individual encoding and a length-adaptive evolution mechanism for bi-objective highdimensional FS.In LA-NSGA,an initialization method based on correlation and redundancy is devised to initialize individuals of diverse lengths,and a Pareto dominance-based length change operator is introduced to guide individuals to explore in promising search space adaptively.Moreover,a dominance-based local search method is employed for further improvement.The experimental results based on 12 high-dimensional gene datasets show that the Pareto front of feature subsets produced by LA-NSGA is superior to those of existing algorithms. | Yanlu Gong Junhai Zhou Quanwang Wu MengChu Zhou Junhao Wen | 2023 | IEEE/CAA Journal of Automatica Sinica2023，10，9： | 0 |
| 16 | Practice and Study of Training Model for Professional Master Degree in Software Engineering显示文摘The culture of professional degree graduate students is a new form of postgraduate education in China. It focuses on cultivating high-level and applied talents compared with original academic degree graduate students. Considering about the source of full-time professional degree graduate students in domain of software engineering and the current college educational system, this paper makes a few beneficial explorations about curriculum, practice teaching, process management and puts forward the mode and method to improve full-time professional degree graduate education in domain of Software Engineering. | Yi Zhang Xinyi Yang Jun Liao Junhao Wen Qingyu Xiong | 2018 | 计算机教育2018，，12： | 0 |
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