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2018 International Conference on Advanced Control, Automation and Artificial Intelligence (ACAAI2018)

作者： Zhiying Gao Lijun Sun Zhihua Wei Department of Computer Science and Technology Tongji University Research Center of Big Data and Network Security Tongji University Key Laboratory of Embedded System and Service Computing Tongji University

Nowadays, with the increasing number of protein sequences all over the world, more and more people are paying their attention to predicting protein subcellular location. Since wet experiment is costly and time-consuming, the automatic computational methods are urgent. In this paper, we propose a variant model based on Long Short-Term Memory(LSTM) to predict protein subcellular location. In this model, we employ LSTM to capture long distance dependency features of the sequence data. Moreover, we adjust the loss function of the loss layer to solve multi-label classification problem. Experimental results demonstrate that, compared with the traditional machine learning methods, our method achieves the best performance in various evaluation metrics.

关键词： LSTM multi-label classification protein subcellular localization

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Null space based discriminant sparse representation large margin for face recognition

Null space based discriminant sparse representation large ma...

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International Joint Conference on Neural Networks (IJCNN)

作者： Ying Wen Lili Hou Lianghua He Department of Computer Science and Technology East China Normal University Shanghai China Key Laboratory of Embedded System and Service Computing Ministry of Education Tongji University Shanghai China

ISBN: (纸本)9781479919611

In this paper, we propose a novel subspace learning algorithm, termed as null space based discriminant sparse representation large margin (NDSLM). There are two contributions in the paper. First, we propose a new expectation to obtain the neighborhood information for large margin subspace learning, i.e., the within-neighborhood scatter and between-neighborhood scatter are modeled by the sparse reconstruction weights of the samples from the same class and different classes, respectively. Since the neighborhood information formed by sparse representation can capture non-linearities in the data, the proposed method possesses more discriminative information than the traditional large margin learning methods with the expectation using Euclidean distance, etc. Second, the large margin information integrated into the model of Fisher criterion makes the discriminating power of NDSLM further boosted. NDSLM addresses the small sample size problem by solving an eigenvalue problem in null space. Experiments on ORL, Yale, AR, Extended Yale B and CMU PIE five face databases are performed to evaluate the proposed algorithm and the results demonstrate the effectiveness of NDSLM.

关键词： Principal component analysis Silicon Pipelines Glass Databases

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An ultrasound system for tumor detection in soft tissues using low transient pulse

An ultrasound system for tumor detection in soft tissues usi...

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IEEE International Conference on Automation Science and Engineering (CASE)

作者： Ashish R. Ratnakar MengChu Zhou Department of Electrical and Computer Engineering New Jersey Institute of Technology Newark NJ USA MoE Key Laboratory of Embedded System and Service Computing Tongji University Shanghai China

This work presents a method to detect the size and location of tumor in soft tissues using ultrasound. Quantitative ultrasound is utilized to allow an ultrasound signal to be sent from a transmitter to multiple receivers. This received signal is analyzed for echogenic and echolucent tumors to differentiate between the two along with non-tumor sample and also studied for the delay to determine the size/location of the tumor. The proposed system utilizes Low Transient Pulse (LTP) technique and is implemented using Field Programmable Gate Array (FPGA) and Digital Signal Processor (DSP) technologies. In this co-design architecture, DSP carries out the analysis of received demodulated signal at a lower speed while FPGA runs at a higher one to generate LTP signal and demodulate bandpass ultrasonic signal. This work elaborates the implementation of Quadrature Amplitude Modulation (QAM) receiver on FPGA for the received signal from an ultrasound detector. LTP is applied to the tumor samples through the transmitter and the received signal at an ultrasonic receiver is passed through QAM to obtain different maxima that are then further used to compute the location and the size of the tumor using DSP. This dual platform co-design demonstrates a good application of a FPGA/DSP platform for the LTP generation and received signal processing.

关键词： Digital signal processing Field programmable gate arrays Tumors Ultrasonic imaging Clocks Quadrature amplitude modulation Receivers

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Learning Topic Emotion and Logical Semantic for Video Paragraph Captioning

SSRN

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SSRN 2024年

作者： Li, Qinyu Wang, Hanli Yi, Xiaokai Department of Computer Science & Technology Tongji University Shanghai201804 China Key Laboratory of Embedded System & Service Computing Ministry of Education Tongji University Shanghai200092 China

Video paragraph captioning aims to generate multiple descriptive sentences for videos, which strive to replicate human writing in accuracy, logicality, and richness. However, current research focuses on the accuracy and temporal order of events, ignoring emotion and other critical logical relations embedded in human language, such as causal and adversative relations. The ignorance impairs the reasonable transition across generated event descriptions and restricts the vividness of expression, resulting in a gap from the standard of human language. To resolve the problem, a framework that integrates logic and emotion representation learning is proposed to narrow the gap. Concretely, a large-scale inter-event relation corpus is constructed based on the EMVPC dataset. This corpus is named EMVPC-EvtRel (standing for "EMVPC-Event Relations") and contains six widely-used logical relations in human writing, 127 explicit inter-sentence connectives, and over 20,000 pairs of event segments with newly annotated logical relations. A logical semantic representation learning method is developed for recognizing the dependencies between visual events, thereby enhancing the characteristics of video contents and boosting the logicality of generated paragraphs. Moreover, a fine-grained emotion recognition module is designed to uncover emotion features embedded in videos. Finally, experimental results on the EMVPC dataset demonstrate the superiority of the proposed method compared to existing state-of-the-art approaches. © 2024, The Authors. All rights reserved.

关键词： Emotion Recognition

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Microservices Architecture Based Cloudware Deployment Platform for service computing

Microservices Architecture Based Cloudware Deployment Platfo...

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2016 IEEE Symposium on service-Oriented system Engineering (SOSE)

作者： Dong Guo Wei Wang Guosun Zeng Zerong Wei Tongji Branch National Engineering & Technology Center of High Performance Shanghai China The Key Laboratory of Embedded System and Service Computing Ministry of Education Tongji University Shanghai China

With the rising of Cloud computing, evolution have occurred not only in datacenter, but also in software development, deployment, maintain and usage. How to build cloud platform for traditional software, and how to deliver cloud service to users are central research fields which will have a huge impact. In recent years, the development of microservice and container technology make software paradigm evolve towards Cloudware in cloud environment. Cloudware, which is based on service and supported by cloud platform, is an important method to cloudalize traditional software. It is also a significant way for software development, deployment, maintenance and usage in future cloud environment. Furthermore, it creates a completely new thought for software in cloud platform. In this paper, we proposed a new Cloudware PaaS platform based on microservice architecture and light weighted container technology. We can directly deploy traditional software which provides services to users by browser in this platform without any modification. By utilizing the microservice architecture, this platform has the characteristics of scalability, auto-deployment, disaster recovery and elastic configuration.

关键词： Cloud computing Containers Computer architecture Rendering (computer graphics) Virtualization Servers

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Automated web service composition supporting conditional branch structures

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Enterprise Information systems 2014年第1期8卷 121-146页

作者： Wang, Pengwei Ding, Zhijun zhijun_ding@*** Jiang, Changjun Zhou, Mengchu Department of Computer Science and Technology Tongji University Shanghai 201804 China Key Laboratory of “Embedded System and Service Computing” Ministry of Education Shanghai 201804 China Department of Electrical and Computer Engineering New Jersey Institute of Technology Newark NJ 07102 USA

The creation of value-added services by automatic composition of existing ones is gaining a significant momentum as the potential silver bullet in service-oriented architecture. However, service composition faces two aspects of difficulties. First, users' needs present such characteristics as diversity, uncertainty and personalisation; second, the existing services run in a real-world environment that is highly complex and dynamically changing. These difficulties may cause the emergence of nondeterministic choices in the process of service composition, which has gone beyond what the existing automated service composition techniques can handle. According to most of the existing methods, the process model of composite service includes sequence constructs only. This article presents a method to introduce conditional branch structures into the process model of composite service when needed, in order to satisfy users' diverse and personalised needs and adapt to the dynamic changes of real-world environment. UML activity diagrams are used to represent dependencies in composite service. Two types of user preferences are considered in this article, which have been ignored by the previous work and a simple programming language style expression is adopted to describe them. Two different algorithms are presented to deal with different situations. A real-life case is provided to illustrate the proposed concepts and methods. [ABSTRACT FROM AUTHOR]

关键词： conditional branch structure control construct service composition user preference web service

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Improved condition for controllability of strongly dependent strict minimal siphons in Petri nets

Improved condition for controllability of strongly dependent...

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IEEE International Conference on Networking, Sensing and Control

作者： GuanJun Liu ChangJun Jiang MengChu Zhou Key Laboratory of the MoE for Embedded System and Service Computing University of Tongji Shanghai China Department of Electrical and Computer Engineering New Jersey Institute of Technology Newark NJ USA

Li and Zhou propose an important concept for Petri nets: elementary siphons. They partition siphons into elementary and dependent ones. The controllability of the latter can be ensured by the former's proper control. They give a sufficient condition to decide whether a dependent siphon is controlled by its elementary ones in S 3 PR. However, this condition is so loose that in many cases the controllability of a dependent SMS cannot be determined although it is actually controlled. In this paper, we propose an improved condition to decide the controllability of strongly dependent SMS.

关键词： Controllability system recovery Nickel Flexible manufacturing systems Petri nets Sufficient conditions Control theory

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Long term bank failure prediction using Fuzzy Refinement-based Transductive Transfer learning

Long term bank failure prediction using Fuzzy Refinement-bas...

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IEEE International Conference on Fuzzy systems (FUZZ-IEEE)

作者： Vahid Behbood Jie Lu Guangquan Zhang Decision Systems & E-Service Intelligence Research Laboratory Centre of Qua ntum Computing and Intelligent System School of Software Faculty of Engineering and Information Technology University of Technology-Sydney Broadway NSW Australia

Machine learning algorithms, which have been considered as robust methods in different computational fields, assume that the training and test data are drawn from the same distribution. This assumption may be violated in many real world applications like bank failure prediction because training and test data may come from different time periods or domains. An efficient novel algorithm known as Fuzzy Refinement (FR) is proposed in this paper to solve this problem and improve the performance. The algorithm utilizes the fuzzy system and similarity concept to modify the instances' labels in target domain which was initially predicted by shift-unaware Fuzzy Neural Network (FNN) proposed by [1]. The experiments are performed using bank failure financial data of United States to evaluate the algorithm performance. The results address a significant improvement in the predictive accuracy of FNN due to applying the proposed algorithm.

关键词： Prediction algorithms Fuzzy neural networks Pragmatics Training Inference algorithms Accuracy Machine learning algorithms

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Upper bounds on lifetime of ordinary clustering ultra wide band sensor networks

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Ruan Jian Xue Bao/Journal of Software 2011年第2期22卷 313-322页

作者： Xu, Juan Hong, Yong-Fa Wang, Cheng Bai, Xing-Zhen College of Electronics and Information Engineering Tongji University Shanghai 200092 China Key Laboratory of Embedded System and Service Computing of the Ministry of Education Tongji University Shanghai 200092 China College of Information Science and Engineering Shandong University of Science and Technology Qingdao 266510 China

This paper considers the time hopping impulse radio ultra wide band (TH-IR UWB) sensor networks, with n sensor nodes uniformly and independently located on a square and a Sink. The upper bounds on the lifetime of ordinary clustering dense and extended TH-IR UWB sensor networks are derived respectively. For ordinary clustering networks, the cluster head aggregates data from the nodes within its own cluster, and relays data to other cluster heads. The results indicate that the upper bounds on the lifetime of ordinary clustering dense TH-IR UWB are in proportion with the node density (or the number of nodes), while the upper bounds on the lifetime of extended networks are inversely proportional to the size of the deployment area (or the number of nodes). The results also reveal that the upper bound on the lifetime of dense network in the ideal case are longer than those of the static network by a factor of (n/log n)1/2, and the upper bound on the lifetime of extended network in the ideal case are longer than those of the static network by a factor of (λn/log(λn))1/2. Therefore, sensor nodes, or the Sink moving randomly in the square, can improve the lifetime of ordinary clustering TH-IR UWB sensor network. © 2011 ISCAS.

关键词： Energy dissipation

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GraphInstruct: Empowering Large Language Models with Graph Understanding and Reasoning Capability

arXiv

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arXiv 2024年

作者： Luo, Zihan Song, Xiran Huang, Hong Lian, Jianxun Zhang, Chenhao Jiang, Jinqi Xie, Xing Huazhong University of Science and Technology Wuhan China Microsoft Research Asia Beijing China The National Engineering Research Center for Big Data Technology and System Service Computing Technology and Systems Laboratory Cluster and Grid Computing Lab School of Computer Science and Technology Huazhong University of Science and Technology China

Evaluating and enhancing the general capabilities of large language models (LLMs) has been an important research topic. Graph is a common data structure in the real world, and understanding graph data is a crucial part for advancing general intelligence. To evaluate and enhance the graph understanding abilities of LLMs, in this paper, we propose a benchmark named GraphInstruct, which comprehensively includes 21 classical graph reasoning tasks, providing diverse graph generation pipelines and detailed reasoning steps. Based on GraphInstruct, we further construct GraphLM through efficient instruction-tuning, which shows prominent graph understanding capability. In order to enhance the LLM with graph reasoning capability as well, we propose a step mask training strategy, and construct a model named GraphLM+. As one of the pioneering efforts to enhance the graph understanding and reasoning abilities of LLMs, extensive experiments have demonstrated the superiority of GraphLM and GraphLM+ over other LLMs. We look forward to more researchers exploring the potential of LLMs in the graph data mining domain through GraphInstruct. Our code for generating GraphInstruct is released publicly at: https://***/CGCL-codes/GraphInstruct. Copyright © 2024, The Authors. All rights reserved.

关键词： Computational linguistics

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