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2023 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2023

作者： Tong, Zhan Wu, Zhan Yang, Yang Mao, Weilong Wang, Shijie Li, Yinsheng Chen, Yang Southeast University Laboratory of Image Science and Technology Nanjing210096 China Southeast University Ministry of Education Key Laboratory of Computer Network and Information Integration Nanjing210096 China Chinese Academy of Sciences Research Center for Medical Artificial Intelligence Shenzhen Institutes of Advanced Technology Shenzhen518055 China School of Computer Science and Engineering Key Lab. of New Generation Artificial Intelligence Technology and Its Interdisciplinary Applications Jiangsu Provincial Joint International Research Laboratory of Medical Information Processing The Laboratory of Image Science and Technology Nanjing210096 China

ISBN: (纸本)9798350337488

Computed Tomography (CT) is an imaging technique widely used in clinical diagnosis. However, high-attenuation metallic implants result in the obstruction of low-energy Xrays and further lead to metal artifacts in the reconstructed CT images. Deep supervised model-based metal artifact reduction(MAR) approaches are limited in clinical applications due to the difficulty in obtaining paired artifact-affected and artifactfree data. Furthermore, these model-based methods lack the consideration of data consistency in the sinogram-domain to perform exact metal trace inpainting. To address these challenges, we propose a Data-consistent unsupErVised diffusiOn model for meTal artifact rEDuction, called DEVOTED-Net. First, DEVOTED-Net leverages prior knowledge to guide the conditional diffusion model for fine-grained metal trace inpainting. Second, an unsupervised MAR framework is designed in the reverse process for the unknown metal traces restoration in the sinogram domain. Third, to further enhance the sinogram-domain data consistency, physics-based consistency constraint loss including conjugateray consistency loss and accumulation-ray consistency loss is designed. Extensive experiments are carried out to verify the performance of our algorithm on the publicly availab.e dataset and clinical experimental dataset. This efficient, accurate, and reliable MAR approach holds great potential in clinics. © 2023 IEEE.

关键词： computed tomography deep unsupervised learning denoising diffusion probabilistic model Metal artifact reduction physics-based consistency constraint

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Resource Scheduling in URLLC and eMBB Coexistence Based on Dynamic Selection Numerology

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Wireless Communications and Mobile Computing 2024年第1期2024卷

作者： Wang, Lei Tao, Sijie Zhao, Lindong Zhou, Dengyou Liu, Zhe Sun, Yanbing School of Telecommunications and Information Engineering Nanjing University of Posts and Telecommunications Nanjing210003 China Key Lab. of Broadband Wireless Communication and Sensor Network Technology Ministry of Education Nanjing University of Posts and Telecommunications Nanjing210003 China School of Foreign Studies Jiangsu Open University Nanjing210036 China

This paper focuses on the resource allocation problem of multiplexing two different service scenarios, enhanced mobile broadband (eMBB) and ultrareliable low latency (URLLC) in 5G New Radio, based on dynamic numerology structure, mini-time slot scheduling, and puncturing to achieve optimal resource allocation. To obtain the optimal channel resource allocation under URLLC user constraints, this paper establishes a relevant channel model divided into two convex optimization problems: (a) eMBB resource allocation and (b) URLLC scheduling. We also determine the numerology values at the beginning of each time slot with the help of deep reinforcement learning to achieve flexible resource scheduling. The proposed algorithm is verified in simulation software, and the simulation results show that the dynamic selection of numerologies proposed in this paper can better improve the data transmission rate of eMBB users and reduce the latency of URLLC services compared with the fixed numerology scheme for the same URLLC packet arrival, while the reasonable resource allocation ensures the reliability of URLLC and eMBB communication. © 2024 Lei Wang et al.

关键词： Resource allocation

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A New BDI Forecasting Model based on Support Vector Machine

A New BDI Forecasting Model based on Support Vector Machine

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2016 IEEE Information technology,networking,Electronic and Automation Control Conference(ITNEC 2016)

作者： Jianmin Bao Lin Pan Yuanfa Xie Key Lab of Broadband Wireless Communication and Sensor Network Technology (Jiangsu Provincial Engineering Research Center of Telecommunications and Network Technology) Ministry of Education Baer Institute of Excellence Nanjing University of Posts and Telecommunications

ISBN: (纸本)9781467391955

BDI(Dry Baltic Index) is a barometer of the shipping market, which is very important and difficult to predict precisely. The traditional forecasting method is not enough to predict precisely for it with higher complexity. The support vector machine has strong nonlinear function approximation and strong generalization ability. In this paper, a new BDI forecasting model based on support vector machine combined with CFS(Correlation-based Feature Selection) is presented and we first introduce the macroeconomic fundamental indicators of BDI. Firstly, we studied and researched the main macroeconomic fundamental indicators of BDI, investigate the inherent law and external influence of freight index fluctuation, and then put forward the BDI forecasting model based on support vector machine and demonstrate the construction principle of the forecasting model. Finally, in order to evaluate the predictive power of support vector machines, we compare their performance with the neural network model. The results show that the SVM model has a better performance in both the trend and the forecast precision, which can provide a powerful tool for the shipping market operators and investors to grasp the market trend and avoid the price risk.

关键词： BDI support vector machine feature selection CFS modeling

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Interactive Evolutionary Multi-Objective Optimization Algorithm Using Cone Dominance

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Journal of Harbin Institute of technology(New Series) 2015年第6期22卷 76-84页

作者： Dalaijargal Purevsuren Saif ur Rehman Gang Cui Jianmin Bao Nwe Nwe Htay Win School of Computer Science and Technology Harbin Institute of Technology Key Lab of Broadband Wireless Communication and Sensor Network Technology (Jiangsu Provincial Engineering Research Center of Telecommunications and Network Technology) Ministry of Education

As the number of objectives increases,the performance of the Pareto dominance-based Evolutionary Multi-objective Optimization( EMO) algorithms such as NSGA-II,SPEA2 severely deteriorates due to the drastic increase in the Pareto-incomparable solutions. We propose a sorting method which classifies these incomparable solutions into several ordered classes by using the decision maker's( DM) preference *** is accomplished by designing an interactive evolutionary algorithm and constructing convex cones. This method allows the DMs to drive the search process toward a preferred region of the Pareto optimal front. The performance of the proposed algorithm is assessed for two,three,and four-objective knapsack problems. The results demonstrate the algorithm ' s ability to converge to the most preferred point. The evaluation and comparison of the results indicate that the proposed approach gives better solutions than that of NSGA-II. In addition,the approach is more efficient compared to NSGA-II in terms of the number of generations required to reach the preferred point.

关键词： multi-objective optimization evolutionary optimization preference information pareto dominance cone dominance

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A hybrid opportunistic Routing Scheme based on nodes grouping strategy for VANETs in Urban Scenarios

A hybrid opportunistic Routing Scheme based on nodes groupin...

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International Conference on Wireless and Optical Communications ( WOCC)

作者： Yuanfa Xie Jianmin Bao Zhihua Song Ya Zhou Bell Honors School Nanjing University of Posts and Telecommunications Nanjing China Key Lab of Broadband Wireless Communication and Sensor Network Technology Ministry of Education Jiangsu Provincial Engineering Research Center of Telecommunications and Network Technology Nanjing China

The increasing mobile devices with better wireless communication facilities trends to be a good opportunity for the development of vehicular ad-hoc networks (VANETs). The opportunistic routing protocols are generally developed from the Delay Tolerant network (DTN). In this paper, we propose an opportunistic routing algorithm called RSUS (Routing Scheme for Urban Scenarios) based on a grouping strategy which considers both internal property and external contacts of nodes. The nodes of network are divided into super nodes, backbone nodes and ordinary nodes. Each type of nodes uses different routing strategy respectively. Then simulations were carried out by the ONE simulator and evaluations compared with the traditional single opportunistic algorithms. Furthermore RSUS was simulated in three different cities. Results show that RSUS algorithm can obtain the optimal performance with a low network overhead ratio and a high delivery rate, it is also suitable for different urban scenarios.

关键词： Routing Urban areas Algorithm design and analysis Wireless communication Ad hoc networks Delays Optical fiber communication

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Energy-efficient resource allocation based on proportional fairness in OFDM multi-user systems

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Journal of Information and Computational Science 2015年第12期12卷 4705-4713页

作者： Zhang, Qian Zhu, Qi Jiangsu Key Lab. of Wireless Communications Nanjing University of Posts and Telecommunications Nanjing China Key Lab. on Wideband Wireless Communications and Sensor Network Technology of Ministry of Education Nanjing University of Posts and Telecommunications Nanjing China

This paper considers the problem of resource assignment with proportional fairness for multi-user OFDM relaying systems in single cell. An energy-efficient strategy is proposed including relay selection, subcarrier assignment and power allocation subjecting to individual power constraint. The optimal purpose is to maximize the sum of the logarithm per user rate per power. The optimization problem is decomposed into some sub-problems, since the joint optimization problem leads to a mixed-fraction time-complete problem. First, Dinkelbach's method is employed for transforming the fractional programming to integral expression. Then, continuous relaxation is used to solve the dual problem by bisection method and Lagrangian dual decomposition method. Simulation results show that the proposed algorithm has a good trade-off between the throughput and fairness compared with other schemes. Copyright © 2015 Binary Information Press.

关键词： Energy efficiency

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Energy efficient and low-latency data collection in TDMA-based WSN

Energy efficient and low-latency data collection in TDMA-bas...

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IEEE International Symposium on Personal, Indoor and Mobile Radio Communications (PIMRC)

作者： Wenxiang Zhu Pingping Xu Xingmiao You Chencheng Yang ThiOanh Bui National Mobile Communications Research Lab Southeast Uiversity Nanjing China Jiangsu Provincial Key Laboratory of Sensor Network Technology Southeast University Wuxi JS China

Data collection is a basic application of wireless sensor networks, where every sensor node collects data and then forwards data to the Sink node through a multi-hop path. In traditional TDMA scheduling, sensors consume extra energy because of the state transitions which occur numerous times in a TDMA frame. And the longer the length of a TDMA frame, the longer duration of a data collection and the larger of time latency. For the problem mentioned above, Slot Reuse Continuous Link Scheduling problem is proposed in this paper, and then formalized into a cross-layer optimization problem involving the network, medium access control, and physical layers with the objective of maximizing the energy efficiency. We transform the problem into two sub-problems: constructing a data collection tree; joint power control and link scheduling for the data collection tree. Based on an existing data collection tree, we propose an algorithm for allocating a continuous slot and transmission power on every link. Simulation results show that the proposed algorithm can shorten the duration of a data collection process, reduce the number of state transitions and energy consumption, improve network energy efficiency when compared with other existing data collection strategies.

关键词： Land mobile radio Mobile computing Wireless networks Iron Manganese

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Semantic QoS Ontology and Semantic Service Ranking Approach for IoT services

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Journal of Harbin Institute of technology(New Series) 2014年第6期21卷 102-112页

作者： Nwe Nwe Htay Win Jian-Min Bao Gang Cui Purevsuren Dalaijargal School of Computer Science and Technology Harbin Institute of Technology Key Lab of Broadband Wireless Communication and Sensor Network Technolog Jiangsu Provincial Engineering Research Center of Telecommunications and Network TechnologyMinistry of Education

Due to a rapid increase in the number of functionally equivalent web services at open and dynamic Io T service environment,Qo S has become a major discrimination factor to reflect the user's expectation and experience of using a *** are different languages and models for expressing Qo S advertisements and requirements among service providers and ***,it leads to the issues of semantic interoperability of Qo S information and semantic similarity match between a semantic description of the service being requested by the service consumer,and a formal description of the service being offered by the service *** this paper,we propose a hierarchical two-layer semantic Qo S ontology to promote the description and declaration of Qo S-based service information in detail for any domain and ***,we develop a semantic matchmaking algorithm to compare the web services according to their Qo S information and adopt analytical hierarchy process( AHP) to make decision for the ranked services depending on the Qo S *** comparison study and experimental result show that our proposed system is superior to other service ranking approaches.

关键词： IoT service environment semantic QoS ontology semantic matchmaking algorithm QoS-based service information analytical hierarchy process

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Low-latency energy-balanced data collection in wireless sensor networks

Low-latency energy-balanced data collection in wireless sens...

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International Conference on Wireless Communications and Signal Processing (WCSP)

作者： Xingmiao You Pingping Xu Wenxiang Zhu National Mobile Communications Research Lab. Southeast University Nanjing China Jiangsu Provincial Key Laboratory of Sensor Network Technology Southeast University Wuxi JS China

Wireless sensor networks monitor specific areas through periodical data collecting mechanism, where sensor nodes sense information and forward data to Sink via multi-hop wireless communications. Since the timeliness of collecting data is of great importance to many applications, a low-latency data collection network structure (LDCNS) which minimizes delays in a data collection process is proposed in this paper. The LDCNS organizes sensor nodes into multiple multi-layered clusters. The size and structure of each cluster follow certain rules so that each cluster head can transmit data to Sink over a period of time which does not overlap with each other and these time periods are continuous. In the data collection process, there has always been a cluster head to transmit data to Sink. An energy-balanced algorithm (ENSF) is designed to construct the LDCNS, which considers the distances between nodes and Sink for choosing the cluster heads. Simulation results show that the LDCNS-ENSF scheme can shorten the duration of a data collection process and prolong the network lifetime when compared with other existing collection structures.

关键词： Data collection Delays Energy consumption Wireless sensor networks Clustering algorithms Data models Algorithm design and analysis

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A Model-Matching Algorithm Based on Improved BP over Out-of-order Streams

A Model-Matching Algorithm Based on Improved BP over Out-of-...

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IEEE International Conference on Communications

作者： Kun Wang Linchao Zhuo Lei Shu Yanfei Sun Key Lab of Broadband Wireless Communication and Sensor Network Technology Nanjing University of Posts and Telecommunications Nanjing China Guangdong Provincial Key Lab. of Petrochemical Equipment Fault Diagnosis Guangdong University of Petrochemical Technology Guangdong China

Due to the explosive increment of data in big data era, it is a challenging task to analyze and extract meaningful data for users. Data needs to be timely operated because of the time sensitivity, so it faces enormous pressure in storage and computing. To deal with the problem that it is hard to achieve valuable information from out-of-order streams over big data in short time, a model-matching algorithm based on improved BP (Back Propagation) is proposed. In the algorithm, the matching model is set dynamically. Information is extracted for users according to the order of data's arriving time. Furthermore, the algorithm parameters are automatically adjusted in the process of learning and matching. Accordingly, the responding speed of learning is accelerated and the time of matching reduces. In the simulation, a group of optimum parameters of improved BP are achieved by using self-adapting adjusting mechanism. The threshold (TH), connecting weight (CW) and learning rate (LR) are equal to 1.5, 3 and 1, respectively. We implement our model-matching algorithm on 10000 sets of out-of-order streams with these parameters. Results indicate that the proposed algorithm can obviously improve the accuracy and speed of matching and achieve better stability.

关键词： Heuristic algorithms Mathematical model Out of order Convergence Accuracy Data models Software algorithms

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