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Research on the Matthews correlation coefficients metrics of personalized recommendation algorithm evaluation

International Journal of Hybrid Information Technology 2015年第1期8卷 163-172页

作者： Liu, Yingbo Cheng, Jiujun Yan, Chendan Wu, Xiao Chen, Fuzhen Key Laboratory of Embedded System and Service Computing of Ministry of Education Tongji University Shanghai China Department of Computer Science and Technology Tongji University Shanghai China

The personalized recommendation systems could better improve the personalized service for network user and alleviate the problem of information overload in the Internet. As we all know, the key point of being a successful recommendation system is the performance of recommendation algorithm. When scholars put forward some new recommendation algorithms, they claim that the new algorithms have been improved in some respects, better than previous algorithm. So we need some evaluation metrics to evaluate the algorithm performance. Due to the scholar didn’t fully understand the evaluation mechanism of recommendation algorithms. They mainly emphasized some specific evaluation metrics like Accuracy, Diversity. What’s more, the academia did not establish a complete and unified assessment of recommendation algorithms evaluation system which is credibility to do the work of recommendation evaluation. So how to do this work objective and reasonable is still a challengeable task. In this article, we discussed the present evaluation metrics with its respective advantages and disadvantages. Then, we put forward to use the Matthews Correlation Coefficient to evaluate the recommendation algorithm’s performance. All this based on an open source projects called mahout which provides a rich set of components to construct the classic recommendation algorithm. The results of the experiments show that the applicability of Matthews correlation coefficient in the relative evaluation work of recommendation algorithm. © 2015 SERSC.

关键词： Recommender systems

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A study on the optimum state for classroom learning from brain cognition perspective-research on relaxed alertness

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Journal of Convergence Information Technology 2012年第23期7卷 564-571页

作者： Gu, Rong Li, Jie Department of Electronic Science and Technology Tongji University Shanghai China The Key Laboratory of Embedded System and Service Computing Ministry of Education Tongji University Shanghai China

Booming development in brain science injects new vitality into the reform of teaching methods. Based on the perspective of brain cognition, this article addresses the optimum state for classroom learning- the relaxed alertness. This is a good state of mind combined low threats with high challenges. Specially, the vigilance is estimated by extracting useful electroencephalogram (EEG) information in time-domain, frequency-domain and spatial distribution. It is used as an indicator to judge whether a student is in the optimum state. Focusing on how to achieve that ideal state, this article discusses some new teaching methods, including the use of Baroque music to stimulate alpha brainwave, the design of effective pattern of guiding class to arouse positive emotions of students and the conversion of teaching forms as novel stimuli to heip them improve vigilance and tide over thinking trough. The effectiveness of these methods is verified by the relevant experimental results.

关键词： Electroencephalography

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An algorithm for generating home states of Petri nets

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Journal of Computational Information systems 2011年第12期7卷 4225-4232页

作者： Wang, Pengwei Ding, Zhijun Chai, Hua Key Laboratory of Embedded System and Service Computing Ministry of Education Shanghai 200092 China Department of Computer Science and Technology Tongji University Shanghai 201804 China

Home states are ground markings which can be reached from any other reachable markings of a Petri net. The existence of home states is a strong property, and it is not only of important theoretical research meaning, but also of great practical value. This paper presents an algorithm for generating home states. For any bounded Petri net, the algorithm can judge whether it contains home states or not, and obtain the set of all its home states. The correctness of the algorithm is proved, and its complexity is analyzed, the result shows that it is a polynomial-time algorithm, so it is effective. Meanwhile, we implemented the algorithm in the popular Petri net tool PIPE2, which can be used for experimental purposes. Then a number of conclusions about the relationships between home state and deadlock are given, which bring great convenience to judge deadlock and exert control pointedly. Copyright © 2011 Binary Information Press.

关键词： Petri nets

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SGED-Net: A Self-organizing Graph Embedding Deep Network for Travel Time Estimation

SGED-Net: A Self-organizing Graph Embedding Deep Network for...

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International Joint Conference on Neural Networks (IJCNN)

作者： Jiankai Zuo Yaying Zhang Key Laboratory of Embedded System and Service Computing of Ministry of Education Tongji University Shanghai China Shanghai Artificial Intelligence Laboratory Shanghai China

In recent years, the travel time prediction has been receiving sustained attention because of the prevalence of location based applications, smart city engineering and online car-hailing. In this paper, a Self-organizing Graph Embedding Deep Network (SGED-Net) model is proposed to address the challenging Origin-Destination(OD) based travel time estimation (TTE). Specifically, SGED-Net comprises four modules, involving travel feature extraction, spatial association graph generation, graph embedding, and travel time deep learning prediction modules. First, we comprehensively extract three travel characteristics and feed them into a modified LightGBM component for learning the importance sort of features for different trips. Second, considering the lack of intermediate trajectories in the OD-based TTE, we employ a self-organizing feature mapping (SOM) approach to obtain the prominent nodes among pick-up and drop-off locations. Meanwhile clustering algorithm is used to divide a city into n-clusters districts of variant sizes. The topology learned by SOM is combined with the districts divided by clustering algorithm to obtain a district-based spatial association graph. Moreover, an improved SDNE algorithm is leveraged to gain a low-dimension spatial association representation while preserving the global and local structure of the graph. Then, we design a deep neural network for learning the captured spatial association representation. Finally, a series of experiments in two real-world large-scale datasets demonstrate the SGED-Net's excellent performance.

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An immune approach for detecting the user's behavior of electronic transaction process

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Journal of Computational Information systems 2015年第2期11卷 683-692页

作者： Jiang, Shaoping Yan, Chungang Zhao, Peihai Wang, Mimi Department of Computer Science and Technology Tongji University Shanghai China Key Laboratory of Embedded System and Service Computing Ministry of Education Tongji University Shanghai China

In the process of electronic transaction, there are many abnormal conditions such as user's own mistakes, account theft and so on. Inspired by mechanisms of immune homeostasis, immune surveillance and immune update from the biological immune system, an immune approach for detecting the user's behavior of electronic transaction process is proposed to solve these problems and make the user's behaviors credible. By computing age of each log and cleaning up the aging logs, logs which can reflect the user's habit could be gotten and the mechanism of immune homeostasis is realized. With the newly-generated transaction sequence detected to be abnormal or not, the mechanisms of immune surveillance is achieved. Updating related sets is the realization of immune update, and the goal of detecting the user's behavior can be reached. The experimental results show that the true positive rate can reach 92% when the false positive rate is 10.8%. 1553-9105/Copyright © 2015 Binary Information Press

关键词： Physiology

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Design and Implementation of DSP Cache 21

Design and Implementation of DSP Cache

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21st IEEE International Conference on Communication Technology, ICCT 2021

作者： Liang, Kunkun Wu, Jun Ren, Haoqi Zhang, Zhifeng Tan, Bin Tongji University Electronics and Information Engineering College Key Laboratory of Embedded System and Service Computing Ministry of Education Shanghai201804 China School of Computer Science Fudan University Shanghai200438 China College of Electronics and Information Engineering Jinggangshan University Ji'an343009 China

ISBN: (纸本)9781665432061

The cache can improve the DSP processor's access speed to external memory and solve the 'Storage Wall' problem. Designing an efficient and flexible cache module plays an vital role in improving the memory access efficiency and overall performance of the DSP. Based on the analysis of DSP storage level design requirements, combined with the actual pipeline structure of the DSP processor SWIFT independently developed by our laboratory, in this paper, we design and implement first- level instruction and data cache. For L1 D-Cache, the relevant conflict detection and processing module is designed to support four parallel Load/Store access requests. The size of the cache can be flexibly configured according to actual application requirements to achieve a balance between power consumption and latency. To write back the modified data left in the cache before the cache size is changed, the Cacheclean instruction is designed. Finally, module-level functional verification and logic synthesis are carried out. The results show that the cache function meets expectations, and the critical path after logic synthesis optimization meets the requirement of 1GHz frenuency. © 2021 IEEE.

关键词： Pipelines

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A comprehensive QoS determination model for Infrastructure-as-a-service clouds

A comprehensive QoS determination model for Infrastructure-a...

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2013 IEEE International Conference on Automation Science and Engineering, CASE 2013

作者： Xia, Yunni Zhou, Mengchu Luo, Xin Zhu, Qingsheng Software Theory and Technology Chongqing Key Lab Chongqing University Chongqing 400030 China Key Laboratory of Embedded System and Service Computing Ministry of Education Tongji University Shanghai 201804 China Department of Electrical and Computer Engineering New Jersey Institute of Technology Newark NJ 07102 United States

ISBN: (纸本)9781479915156

Cloud computing is a recently developed new technology for complex systems with massive service sharing, which is different from the resource sharing of the grid computing systems. In a cloud environment, service requests from users go through numerous provider specific steps from the instant it is submitted to when the service is fully delivered. Quality modeling and analysis of clouds are not easy tasks because of the complexity of the provisioning mechanism and the dynamic cloud environment. This study proposes an analytical modelbased approach for quality evaluation of Infrastructure-as-a-service cloud and consider expected request completion time, rejection probability, and system overhead rate as key QoS metrics. It also features with the modeling of different warming and cooling strategies of machines and the ability to identify the optimal balance between system overhead and performance. © 2013 IEEE.

关键词： Quality control

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C2G2FSnake: automatic tongue image segmentation utilizing prior knowledge

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Science China(Information Sciences) 2013年第9期56卷 154-167页

作者： SHI MiaoJing LI GuoZheng LI FuFeng The Key Laboratory of Embedded System and Service Computing Ministry of Education Department of Control Science and Engineering Tongji University Laboratory of Information Access and Synthesis of TCM Four Diagnosis Shanghai University of Traditional Chinese Medicine

Extraction of the tongue body from digital images is essential for automated tongue diagnoses in traditional Chinese medicine. This paper presents a fully automated active contour initial method that utilizes prior knowledge of the tongue shape and its location in tongue images. Then colorspace information is introduced to control curve evolution. Combining the geometrical Snake model with the parameterized GVFSnake model, a novel approach for automatic tongue segmentation: C2G2FSnake (color control-geometric & gradient flow Snake) is proposed. This method increases the curve velocity but decreases the complexity. C2G2FSnake greatly extends practical usage to tongue segmentation, at the same time increasing the precision. Compared with other state-of-the-art works using different images of tongue color, C2G2FSnake realizes automatic tongue segmentation with greatly improved accuracy.

关键词： tongue diagnosis tongue segmentation color space-control Snake parameterized Snake geomet- ric Snake

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Spatial-Temporal Flow Holistic Interaction Graph Convolution Network for Bidirectional Traffic Flow Forecasting

Spatial-Temporal Flow Holistic Interaction Graph Convolution...

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IEEE International Conference on Big Data

作者： Canyang Zhang Qi Zheng Yaying Zhang Key Laboratory of Embedded System and Service Computing Ministry of Education Tongji University Shanghai China Shanghai Artificial Intelligence Laboratory Shanghai China

Traffic flow forecasting is indispensable in modern urban life. Considering the complexity, variability and strong timeliness of traffic flow, traffic flow forecasting is a worth exploring but challenging research field. To achieve better traffic flow forecasting effect, we focus on two critical aspects that assume noteworthy importance: i) the features inside the traffic outflows and inflows. ii) the supplementary information regarding exterior region which is the area outside the grid division regions. To address these challenges, we propose a novel deep learning model Spatial-Temporal Flow Holistic Interaction Graph Convolution Network (STHGCN). In STHGCN, graph convolution based modules are applied through multi-step simulation. An exterior region feature estimation module is designed to estimate the influence of the special exterior region through the characteristics of complete trajectories, which enables a more comprehensive reasoning for traffic flow forecasting in grid division regions. Furthermore, a flow feature fusion integrator and stackable convolution modules are proposed to aggregate the intermediate features extracted from various perspectives, which simulate the constantly-updating and interlinked states of traffic flows through the process of multi-layer feature separation and fusion. We conduct extensive experiments on real-world traffic datasets and our proposed model outperforms all baselines.

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Design and Implementation of Communication Module in Passive ultrasonic Sensor Networks

Design and Implementation of Communication Module in Passive...

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2010 International Conference on Computer,Mechatronics,Control and Electronic Engineering(2010计算机、机电、控制与电子工程国际会议 CMCE 2010)

作者： Lina Han Rui Zhao Key Laboratory of Embedded System and Service Computing Ministry of EducationTongji University Shan The Third Research Institute of The Ministry of Public Security Shanghai China

ISBN: (纸本)9781424479573

Passive sensor networks can achieve accurate detection of target under complex environment In order to adapt to different communication demands of sensor networks in different environments, this paper designed and implemented a wireless and wired mixed communication module, that is, a communication system combined short-distance wireless communication based on radio frequency technology with broadband cable communication. Simulation results show that our system can achieve the desired requirements in different circumstances.

关键词： sensor network wireless communication radio frequency (RF) wired communication

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