Semantic communication(SemCom)aims to achieve high-fidelity information delivery under low communication consumption by only guaranteeing semantic accuracy.Nevertheless,semantic communication still suffers from unexpe...Semantic communication(SemCom)aims to achieve high-fidelity information delivery under low communication consumption by only guaranteeing semantic accuracy.Nevertheless,semantic communication still suffers from unexpected channel volatility and thus developing a re-transmission mechanism(e.g.,hybrid automatic repeat request[HARQ])becomes indispensable.In that regard,instead of discarding previously transmitted information,the incremental knowledge-based HARQ(IK-HARQ)is deemed as a more effective mechanism that could sufficiently utilize the information semantics.However,considering the possible existence of semantic ambiguity in image transmission,a simple bit-level cyclic redundancy check(CRC)might compromise the performance of IK-HARQ.Therefore,there emerges a strong incentive to revolutionize the CRC mechanism,thus more effectively reaping the benefits of both SemCom and HARQ.In this paper,built on top of swin transformer-based joint source-channel coding(JSCC)and IK-HARQ,we propose a semantic image transmission framework SC-TDA-HARQ.In particular,different from the conventional CRC,we introduce a topological data analysis(TDA)-based error detection method,which capably digs out the inner topological and geometric information of images,to capture semantic information and determine the necessity for re-transmission.Extensive numerical results validate the effectiveness and efficiency of the proposed SC-TDA-HARQ framework,especially under the limited bandwidth condition,and manifest the superiority of TDA-based error detection method in image transmission.展开更多
Test data compression and test resource partitioning （TRP） are essential to reduce the amount of test data in system-on-chip testing. A novel variable-to-variable-length compression codes is designed as advanced fre...Test data compression and test resource partitioning （TRP） are essential to reduce the amount of test data in system-on-chip testing. A novel variable-to-variable-length compression codes is designed as advanced fre- quency-directed run-length （AFDR） codes. Different [rom frequency-directed run-length （FDR） codes, AFDR encodes both 0- and 1-runs and uses the same codes to the equal length runs. It also modifies the codes for 00 and 11 to improve the compression performance. Experimental results for ISCAS 89 benchmark circuits show that AFDR codes achieve higher compression ratio than FDR and other compression codes.展开更多
This paper investigates the simultaneous wireless information and powertransfer(SWIPT) for network-coded two-way relay network from an information-theoretic perspective, where two sources exchange information via an S...This paper investigates the simultaneous wireless information and powertransfer(SWIPT) for network-coded two-way relay network from an information-theoretic perspective, where two sources exchange information via an SWIPT-aware energy harvesting(EH) relay. We present a power splitting(PS)-based two-way relaying(PS-TWR) protocol by employing the PS receiver architecture. To explore the system sum rate limit with data rate fairness, an optimization problem under total power constraint is formulated. Then, some explicit solutions are derived for the problem. Numerical results show that due to the path loss effect on energy transfer, with the same total available power, PS-TWR losses some system performance compared with traditional non-EH two-way relaying, where at relatively low and relatively high signalto-noise ratio(SNR), the performance loss is relatively small. Another observation is that, in relatively high SNR regime, PS-TWR outperforms time switching-based two-way relaying(TS-TWR) while in relatively low SNR regime TS-TWR outperforms PS-TWR. It is also shown that with individual available power at the two sources, PS-TWR outperforms TS-TWR in both relatively low and high SNR regimes.展开更多
In the process of encoding and decoding,erasure codes over binary fields,which just need AND operations and XOR operations and therefore have a high computational efficiency,are widely used in various fields of inform...In the process of encoding and decoding,erasure codes over binary fields,which just need AND operations and XOR operations and therefore have a high computational efficiency,are widely used in various fields of information technology.A matrix decoding method is proposed in this paper.The method is a universal data reconstruction scheme for erasure codes over binary fields.Besides a pre-judgment that whether errors can be recovered,the method can rebuild sectors of loss data on a fault-tolerant storage system constructed by erasure codes for disk errors.Data reconstruction process of the new method has simple and clear steps,so it is beneficial for implementation of computer codes.And more,it can be applied to other non-binary fields easily,so it is expected that the method has an extensive application in the future.展开更多
Recent advances in intelligent transportation system allow traffic safety studies to extend from historic data-based analyses to real-time applications. The study presents a new method to predict crash likelihood with...Recent advances in intelligent transportation system allow traffic safety studies to extend from historic data-based analyses to real-time applications. The study presents a new method to predict crash likelihood with traffic data collected by discrete loop detectors as well as the web-crawl weather data. Matched case-control method and support vector machines （SVMs） technique were employed to identify the risk status. The adaptive synthetic over-sampling technique was applied to solve the imbalanced dataset issues. Random forest technique was applied to select the contributing factors and avoid the over-fitting issues. The results indicate that the SVMs classifier could successfully classify 76.32% of the crashes on the test dataset and 87.52% of the crashes on the overall dataset, which were relatively satisfactory compared with the results of the previous studies. Compared with the SVMs classifier without the data, the SVMs classifier with the web-crawl weather data increased the crash prediction accuracy by 1.32% and decreased the false alarm rate by 1.72%, showing the potential value of the massive web weather data. Mean impact value method was employed to evaluate the variable effects, and the results are identical with the results of most of previous studies. The emerging technique based on the discrete traffic data and web weather data proves to be more applicable on real- time safety management on freeways.展开更多
Retrieving data from mobile source vehicles is a crucial routine operation for a wide spectrum of vehicular network applications, in- cluding road surface monitoring and sharing. Network coding has been widely exploit...Retrieving data from mobile source vehicles is a crucial routine operation for a wide spectrum of vehicular network applications, in- cluding road surface monitoring and sharing. Network coding has been widely exploited and is an effective technique for diffusing in- formation over a network. The use of network coding to improve data availability in vehicular networks is explored in this paper. With random linear network codes, simple replication is avoided, and instead, a node forwards a coded block that is a random combination of all data received by the node. We use a network-coding-based approach to improve data availability in vehicular networks. To deter- mine the feasibility of this approach, we conducted an empirical study with extensive simulations based on two real vehicular GPS traces, both of which contain records from thousands of vehicles over more than a year. We observed that, despite significant improve- ment in data availability, there is a serious issue with linear correlation between the received codes. This reduces the data-retrieval success rate. By analyzing the real vehicular traces, we discovered that there is a strong community structure within a real vehicular network. We verify that such a structure contributes to the issue of linear dependence. Then, we point out opportunities to improve the network-coding-based approach by developing community-aware code-distribution techniques.展开更多
Fast data synchronization in wireless ad hoc networks is a challenging and critical problem.It is fundamental for efficient information fusion,control and decision in distributed systems.Previously,distributed data sy...Fast data synchronization in wireless ad hoc networks is a challenging and critical problem.It is fundamental for efficient information fusion,control and decision in distributed systems.Previously,distributed data synchronization was mainly studied in the latency-tolerant distributed databases,or assuming the general model of wireless ad hoc networks.In this paper,we propose a pair of linear network coding(NC)and all-to-all broadcast based fast data synchronization algorithms for wireless ad hoc networks whose topology is under operator’s control.We consider both data block selection and transmitting node selection for exploiting the benefits of NC.Instead of using the store-and-forward protocol as in the conventional uncoded approach,a compute-and-forward protocol is used in our scheme,which improves the transmission efficiency.The performance of the proposed algorithms is studied under different values of network size,network connection degree,and per-hop packet error rate.Simulation results demonstrate that our algorithms significantly reduce the times slots used for data synchronization compared with the baseline that does not use NC.展开更多
To ensure agreement between theoretical calculations and experimental data,parameters to selected nuclear physics models are perturbed and fine-tuned in nuclear data evaluations.This approach assumes that the chosen s...To ensure agreement between theoretical calculations and experimental data,parameters to selected nuclear physics models are perturbed and fine-tuned in nuclear data evaluations.This approach assumes that the chosen set of models accurately represents the‘true’distribution of considered observables.Furthermore,the models are chosen globally,indicating their applicability across the entire energy range of interest.However,this approach overlooks uncertainties inherent in the models themselves.In this work,we propose that instead of selecting globally a winning model set and proceeding with it as if it was the‘true’model set,we,instead,take a weighted average over multiple models within a Bayesian model averaging(BMA)framework,each weighted by its posterior probability.The method involves executing a set of TALYS calculations by randomly varying multiple nuclear physics models and their parameters to yield a vector of calculated observables.Next,computed likelihood function values at each incident energy point were then combined with the prior distributions to obtain updated posterior distributions for selected cross sections and the elastic angular distributions.As the cross sections and elastic angular distributions were updated locally on a per-energy-point basis,the approach typically results in discontinuities or“kinks”in the cross section curves,and these were addressed using spline interpolation.The proposed BMA method was applied to the evaluation of proton-induced reactions on ^(58)Ni between 1 and 100 MeV.The results demonstrated a favorable comparison with experimental data as well as with the TENDL-2023 evaluation.展开更多
基金supported in part by the National Key Research and Development Program of China under Grant 2024YFE0200600in part by the National Natural Science Foundation of China under Grant 62071425+3 种基金in part by the Zhejiang Key Research and Development Plan under Grant 2022C01093in part by the Zhejiang Provincial Natural Science Foundation of China under Grant LR23F010005in part by the National Key Laboratory of Wireless Communications Foundation under Grant 2023KP01601in part by the Big Data and Intelligent Computing Key Lab of CQUPT under Grant BDIC-2023-B-001.
文摘Semantic communication(SemCom)aims to achieve high-fidelity information delivery under low communication consumption by only guaranteeing semantic accuracy.Nevertheless,semantic communication still suffers from unexpected channel volatility and thus developing a re-transmission mechanism(e.g.,hybrid automatic repeat request[HARQ])becomes indispensable.In that regard,instead of discarding previously transmitted information,the incremental knowledge-based HARQ(IK-HARQ)is deemed as a more effective mechanism that could sufficiently utilize the information semantics.However,considering the possible existence of semantic ambiguity in image transmission,a simple bit-level cyclic redundancy check(CRC)might compromise the performance of IK-HARQ.Therefore,there emerges a strong incentive to revolutionize the CRC mechanism,thus more effectively reaping the benefits of both SemCom and HARQ.In this paper,built on top of swin transformer-based joint source-channel coding(JSCC)and IK-HARQ,we propose a semantic image transmission framework SC-TDA-HARQ.In particular,different from the conventional CRC,we introduce a topological data analysis(TDA)-based error detection method,which capably digs out the inner topological and geometric information of images,to capture semantic information and determine the necessity for re-transmission.Extensive numerical results validate the effectiveness and efficiency of the proposed SC-TDA-HARQ framework,especially under the limited bandwidth condition,and manifest the superiority of TDA-based error detection method in image transmission.
基金Supported by the National Natural Science Foundation of China(61076019,61106018)the Aeronautical Science Foundation of China(20115552031)+3 种基金the China Postdoctoral Science Foundation(20100481134)the Jiangsu Province Key Technology R&D Program(BE2010003)the Nanjing University of Aeronautics and Astronautics Research Funding(NS2010115)the Nanjing University of Aeronatics and Astronautics Initial Funding for Talented Faculty(1004-YAH10027)~~
文摘Test data compression and test resource partitioning （TRP） are essential to reduce the amount of test data in system-on-chip testing. A novel variable-to-variable-length compression codes is designed as advanced fre- quency-directed run-length （AFDR） codes. Different [rom frequency-directed run-length （FDR） codes, AFDR encodes both 0- and 1-runs and uses the same codes to the equal length runs. It also modifies the codes for 00 and 11 to improve the compression performance. Experimental results for ISCAS 89 benchmark circuits show that AFDR codes achieve higher compression ratio than FDR and other compression codes.
基金supported by the National Natural Science Foundation of China ( No . 61602034 )the Beijing Natural Science Foundation (No. 4162049)+2 种基金the Open Research Fund of National Mobile Communications Research Laboratory,Southeast University (No. 2014D03)the Fundamental Research Funds for the Central Universities Beijing Jiaotong University (No. 2016JBM015)the NationalHigh Technology Research and Development Program of China (863 Program) (No. 2015AA015702)
文摘This paper investigates the simultaneous wireless information and powertransfer(SWIPT) for network-coded two-way relay network from an information-theoretic perspective, where two sources exchange information via an SWIPT-aware energy harvesting(EH) relay. We present a power splitting(PS)-based two-way relaying(PS-TWR) protocol by employing the PS receiver architecture. To explore the system sum rate limit with data rate fairness, an optimization problem under total power constraint is formulated. Then, some explicit solutions are derived for the problem. Numerical results show that due to the path loss effect on energy transfer, with the same total available power, PS-TWR losses some system performance compared with traditional non-EH two-way relaying, where at relatively low and relatively high signalto-noise ratio(SNR), the performance loss is relatively small. Another observation is that, in relatively high SNR regime, PS-TWR outperforms time switching-based two-way relaying(TS-TWR) while in relatively low SNR regime TS-TWR outperforms PS-TWR. It is also shown that with individual available power at the two sources, PS-TWR outperforms TS-TWR in both relatively low and high SNR regimes.
基金supported by the National Natural Science Foundation of China under Grant No.61501064Sichuan Provincial Science and Technology Project under Grant No.2016GZ0122
文摘In the process of encoding and decoding,erasure codes over binary fields,which just need AND operations and XOR operations and therefore have a high computational efficiency,are widely used in various fields of information technology.A matrix decoding method is proposed in this paper.The method is a universal data reconstruction scheme for erasure codes over binary fields.Besides a pre-judgment that whether errors can be recovered,the method can rebuild sectors of loss data on a fault-tolerant storage system constructed by erasure codes for disk errors.Data reconstruction process of the new method has simple and clear steps,so it is beneficial for implementation of computer codes.And more,it can be applied to other non-binary fields easily,so it is expected that the method has an extensive application in the future.
基金supported by the National Natural Science Foundation (71301119)the Shanghai Natural Science Foundation (12ZR1434100)
文摘Recent advances in intelligent transportation system allow traffic safety studies to extend from historic data-based analyses to real-time applications. The study presents a new method to predict crash likelihood with traffic data collected by discrete loop detectors as well as the web-crawl weather data. Matched case-control method and support vector machines （SVMs） technique were employed to identify the risk status. The adaptive synthetic over-sampling technique was applied to solve the imbalanced dataset issues. Random forest technique was applied to select the contributing factors and avoid the over-fitting issues. The results indicate that the SVMs classifier could successfully classify 76.32% of the crashes on the test dataset and 87.52% of the crashes on the overall dataset, which were relatively satisfactory compared with the results of the previous studies. Compared with the SVMs classifier without the data, the SVMs classifier with the web-crawl weather data increased the crash prediction accuracy by 1.32% and decreased the false alarm rate by 1.72%, showing the potential value of the massive web weather data. Mean impact value method was employed to evaluate the variable effects, and the results are identical with the results of most of previous studies. The emerging technique based on the discrete traffic data and web weather data proves to be more applicable on real- time safety management on freeways.
基金supported by China 973 Program(2014CB340303)NSFC(No.61170238,60903190)National 863 Program(2013AA01A601)
文摘Retrieving data from mobile source vehicles is a crucial routine operation for a wide spectrum of vehicular network applications, in- cluding road surface monitoring and sharing. Network coding has been widely exploited and is an effective technique for diffusing in- formation over a network. The use of network coding to improve data availability in vehicular networks is explored in this paper. With random linear network codes, simple replication is avoided, and instead, a node forwards a coded block that is a random combination of all data received by the node. We use a network-coding-based approach to improve data availability in vehicular networks. To deter- mine the feasibility of this approach, we conducted an empirical study with extensive simulations based on two real vehicular GPS traces, both of which contain records from thousands of vehicles over more than a year. We observed that, despite significant improve- ment in data availability, there is a serious issue with linear correlation between the received codes. This reduces the data-retrieval success rate. By analyzing the real vehicular traces, we discovered that there is a strong community structure within a real vehicular network. We verify that such a structure contributes to the issue of linear dependence. Then, we point out opportunities to improve the network-coding-based approach by developing community-aware code-distribution techniques.
基金This work is financially supported by Beijing Municipal Natural Science Foundation(No.L202012)the Open Research Project of the State Key Laboratory of Media Convergence and Communication,Communication University of China(No.SKLMCC2020KF008)the Fundamental Research Funds for the Central Universities(No.2020RC05).
文摘Fast data synchronization in wireless ad hoc networks is a challenging and critical problem.It is fundamental for efficient information fusion,control and decision in distributed systems.Previously,distributed data synchronization was mainly studied in the latency-tolerant distributed databases,or assuming the general model of wireless ad hoc networks.In this paper,we propose a pair of linear network coding(NC)and all-to-all broadcast based fast data synchronization algorithms for wireless ad hoc networks whose topology is under operator’s control.We consider both data block selection and transmitting node selection for exploiting the benefits of NC.Instead of using the store-and-forward protocol as in the conventional uncoded approach,a compute-and-forward protocol is used in our scheme,which improves the transmission efficiency.The performance of the proposed algorithms is studied under different values of network size,network connection degree,and per-hop packet error rate.Simulation results demonstrate that our algorithms significantly reduce the times slots used for data synchronization compared with the baseline that does not use NC.
基金funding from the Paul ScherrerInstitute,Switzerland through the NES/GFA-ABE Cross Project。
文摘To ensure agreement between theoretical calculations and experimental data,parameters to selected nuclear physics models are perturbed and fine-tuned in nuclear data evaluations.This approach assumes that the chosen set of models accurately represents the‘true’distribution of considered observables.Furthermore,the models are chosen globally,indicating their applicability across the entire energy range of interest.However,this approach overlooks uncertainties inherent in the models themselves.In this work,we propose that instead of selecting globally a winning model set and proceeding with it as if it was the‘true’model set,we,instead,take a weighted average over multiple models within a Bayesian model averaging(BMA)framework,each weighted by its posterior probability.The method involves executing a set of TALYS calculations by randomly varying multiple nuclear physics models and their parameters to yield a vector of calculated observables.Next,computed likelihood function values at each incident energy point were then combined with the prior distributions to obtain updated posterior distributions for selected cross sections and the elastic angular distributions.As the cross sections and elastic angular distributions were updated locally on a per-energy-point basis,the approach typically results in discontinuities or“kinks”in the cross section curves,and these were addressed using spline interpolation.The proposed BMA method was applied to the evaluation of proton-induced reactions on ^(58)Ni between 1 and 100 MeV.The results demonstrated a favorable comparison with experimental data as well as with the TENDL-2023 evaluation.
