Efficient Gaussian Process Classification-based Physical-Layer Authentication with Configurable Fingerprints for 6G-Enabled IoT

Physical-Layer Authentication (PLA) has been recently believed as an endogenous-secure and energy-efficient technique to recognize IoT terminals. However, the major challenge of applying the state-of-the-art PLA schemes directly to 6G-enabled IoT is the inaccurate channel fingerprint estimation in low Signal-Noise Ratio (SNR) environments, which will greatly influence the reliability and robustness of PLA. To tackle this issue, we propose a configurable-fingerprint-based PLA architecture through Intelligent Reflecting Surface (IRS) that helps create an alternative wireless transmission path to provide more accurate fingerprints. According to Baye's theorem, we propose a Gaussian Process Classification (GPC)-based PLA scheme, which utilizes the Expectation Propagation (EP) method to obtain the identities of unknown fingerprints. Considering that obtaining sufficient labeled fingerprint samples to train the GPC-based authentication model is challenging for future 6G systems, we further extend the GPC-based PLA to the Efficient-GPC (EGPC)-based PLA through active learning, which requires fewer labeled fingerprints and is more feasible. We also propose three fingerprint selecting algorithms to choose fingerprints, whose identities are queried to the upper-layers authentication mechanisms. For this reason, the proposed EGPC-based scheme is also a lightweight cross-layer authentication method to offer a superior security level. The simulations conducted on synthetic datasets demonstrate that the IRS-assisted scheme reduces the authentication error rate by 98.69% compared to the non-IRS-based scheme. Additionally, the proposed fingerprint selection algorithms reduce the authentication error rate by 65.96% to 86.93% and 45.45% to 70.00% under perfect and imperfect channel estimation conditions, respectively, when compared with baseline algorithms.Comment: 12 pages, 9 figure

BigDataBench: a Big Data Benchmark Suite from Internet Services

As architecture, systems, and data management communities pay greater attention to innovative big data systems and architectures, the pressure of benchmarking and evaluating these systems rises. Considering the broad use of big data systems, big data benchmarks must include diversity of data and workloads. Most of the state-of-the-art big data benchmarking efforts target evaluating specific types of applications or system software stacks, and hence they are not qualified for serving the purposes mentioned above. This paper presents our joint research efforts on this issue with several industrial partners. Our big data benchmark suite BigDataBench not only covers broad application scenarios, but also includes diverse and representative data sets. BigDataBench is publicly available from http://prof.ict.ac.cn/BigDataBench . Also, we comprehensively characterize 19 big data workloads included in BigDataBench with varying data inputs. On a typical state-of-practice processor, Intel Xeon E5645, we have the following observations: First, in comparison with the traditional benchmarks: including PARSEC, HPCC, and SPECCPU, big data applications have very low operation intensity; Second, the volume of data input has non-negligible impact on micro-architecture characteristics, which may impose challenges for simulation-based big data architecture research; Last but not least, corroborating the observations in CloudSuite and DCBench (which use smaller data inputs), we find that the numbers of L1 instruction cache misses per 1000 instructions of the big data applications are higher than in the traditional benchmarks; also, we find that L3 caches are effective for the big data applications, corroborating the observation in DCBench.Comment: 12 pages, 6 figures, The 20th IEEE International Symposium On High Performance Computer Architecture (HPCA-2014), February 15-19, 2014, Orlando, Florida, US

Unraveling (electro)-chemical stability and interfacial reactions of Li 10 SnP 2 S 12 in all-solid-state Li batteries

Abstract(#br)Li 10 SnP 2 S 12 (LSPS) with high ionic conductivity and moderate price is a promising solid electrolyte for all-solid-state batteries. However, the instability of LSPS and LSPS/electrodes interfaces would cause poor cycle performance issues in the LSPS-based all-solid-state batteries, which have not been well understood. Herein, we address and unravel the decomposition products of LSPS and their Li + transfer characteristics, especially on the surface of LSPS/electrodes by using solid-state nuclear magnetic resonance (ss NMR) spectroscopy coupled with X-ray photoelectron spectroscopy (XPS). The results reveal that the high mechanical energy during ball-milling process leads to the decomposition of LSPS into Li 4 SnS 4 and Li 3 PS 4 . During charge/discharge cycling, specific capacity fading of batteries originates from the formation of new interfacial layer at LSPS/Acetylene black cathode and LSPS/Li metal anode interfaces. Furthermore, our results demonstrate that the rough and porous morphology of the interface formed after cycling, rather than the decomposition products, is the critical factor which results in the increases of the interfacial resistance at LSPS/Li interface and serious formation of Li dendrite. Our results highlight the significant roles of (electro)chemical and interfacial stability of sulfide solid electrolyte in the development of all-solid-state batteries

Multi-Connectivity Enhanced Communication-Incentive Distributed Computation Offloading in Vehicular Networks

Flexible resource scheduling and network forecast are crucial functions to enhance mobile vehicular network performances. However, BaseStations (BSs) and their computing unit which undertake the functions cannot meet the delay requirement because of limited computation capability. Offloading the time-sensitive functions to User Equipment (UE) is believed to be an effective method to tackle this challenge. The disadvantage of the method is offloading occupies communication resources, which deteriorate the system capability. To better coordinate offloading and communication, a multi-connectivity enhanced joint scheduling scheme for distributed computation offloading and communication resources allocation in vehicular networks is proposed in this article. Computation tasks are divided into many slices and distributed to UEs to aggregate the computation capability. A communication-incentive mechanism is provided for involving UEs to compensate the loss of UEs, while multi-connectivity is adopted to enhance the system throughput. We also defined offloading failure ratio as a conclusive condition for offloading size by analyzing the movement of UEs. By a two-step optimization, the co-scheduling of offloading size and throughput is solved. The system-level simulation results show that the offloading size and throughput of the proposed scheme are larger than comparisons when the time constraint is tight

Understanding the failure process of sulfide-based all-solid-state lithium batteries via operando nuclear magnetic resonance spectroscopy

All-solid-state lithium batteries performance is affected by the solid electrolyte interphase (SEI) and electrically disconnected (“dead”) Li metal. Here, via operando NMR measurements, the authors quantify the Li metal in the SEI and “dead” regions using various inorganic solid-state electrolytes

Comprehensive Evaluation of Appreciation of <i>Rhododendron</i> Based on Analytic Hierarchy Process

Qinting Lake Park has effectively imported Rhododendron varieties from Zhejiang Province. The analytic hierarchy process was employed to devise an evaluation framework to evaluate the ornamental and adaptive features of these species. Subsequently, we conducted a standardized evaluation of 24 species for their ornamental and adaptive traits under controlled cultivation conditions. The findings indicated that the percentage of ornamental flowers in the first-level index was significantly greater than the other two factors, indicating that the ornamental value of flowers was the most important in the evaluation of Rhododendron ornamental value. Among the secondary indicators, the proportion of flower color and flower weight was significantly higher than that of other factors, which had the greatest impact on the evaluation results. The 24 Rhododendron species were classified into two grades based on their ornamental value, as determined by index weights and scoring standards. Rhododendron ‘Xueqing’, Rhododendron ‘Big Qinglian’, and Rhododendron ‘Jinyang No. 9’ exhibited superior ornamental value and demonstrated more favorable suitability for garden applications

Stabilizing Li₁₀SnP₂S₁₂/Li Interface via an in Situ Formed Solid Electrolyte Interphase Layer

Despite the extremely high ionic conductivity, the commercialization of Li₁₀GeP₂S₁₂-type materials is hindered by the poor stability against Li metal. Herein, to address that issue, a simple strategy is proposed and demonstrated for the first time, i.e., in situ modification of the interface between Li metal and Li₁₀SnP₂S₁₂ (LSPS) by pretreatment with specific ionic liquid and salts. X-ray photoelectron spectroscopy and electrochemical impedance spectroscopy results reveal that a stable solid electrolyte interphase (SEI) layer instead of a mixed conducting layer is formed on Li metal by adding 1.5 M lithium bis­(trifluoromethanesulfonyl)­imide (LiTFSI)/<i>N</i>-propyl-<i>N</i>-methyl pyrrolidinium bis­(trifluoromethanesulfonyl)­imide (Pyr₁₃TFSI) ionic liquid, where ionic liquid not only acts as a wetting agent but also improves the stability at the Li/LSPS interface. This stable SEI layer can prevent LSPS from directly contacting the Li metal and further decomposition, and the Li/LSPS/Li symmetric cell with 1.5 M LiTFSI/Pyr₁₃TFSI attains a stable cycle life of over 1000 h with both the charge and discharge voltages reaching about 50 mV at 0.038 mA cm^–2. Furthermore, the effects of different Li salts on the interfacial modification is also compared and investigated. It is shown that lithium bis­(fluorosulfonyl) imide (LiFSI) salt causes the enrichment of LiF in the SEI layer and results in a higher resistance of the cell upon a long cycling life

Data_Sheet_1_Genome-wide identification and adaptive evolution of CesA/Csl superfamily among species with different life forms in Orchidaceae.pdf

Orchidaceae, with more than 25,000 species, is one of the largest flowering plant families that can successfully colonize wide ecological niches, such as land, trees, or rocks, and its members are divided into epiphytic, terrestrial, and saprophytic types according to their life forms. Cellulose synthase (CesA) and cellulose synthase-like (Csl) genes are key regulators in the synthesis of plant cell wall polysaccharides, which play an important role in the adaptation of orchids to resist abiotic stresses, such as drought and cold. In this study, nine whole-genome sequenced orchid species with three types of life forms were selected; the CesA/Csl gene family was identified; the evolutionary roles and expression patterns of CesA/Csl genes adapted to different life forms and abiotic stresses were investigated. The CesA/Csl genes of nine orchid species were divided into eight subfamilies: CesA and CslA/B/C/D/E/G/H, among which the CslD subfamily had the highest number of genes, followed by CesA, whereas CslB subfamily had the least number of genes. Expansion of the CesA/Csl gene family in orchids mainly occurred in the CslD and CslF subfamilies. Conserved domain analysis revealed that eight subfamilies were conserved with variations in orchids. In total, 17 pairs of CesA/Csl homologous genes underwent positive selection, of which 86%, 14%, and none belonged to the epiphytic, terrestrial, and saprophytic orchids, respectively. The inter-species collinearity analysis showed that the CslD genes expanded in epiphytic orchids. Compared with terrestrial and saprophytic orchids, epiphytic orchids experienced greater strength of positive selection, with expansion events mostly related to the CslD subfamily, which might have resulted in strong adaptability to stress in epiphytes. Experiments on stem expression changes under abiotic stress showed that the CslA might be a key subfamily in response to drought stress for orchids with different life forms, whereas the CslD might be a key subfamily in epiphytic and saprophytic orchids to adapt to freezing stress. This study provides the basic knowledge for the further systematic study of the adaptive evolution of the CesA/Csl superfamily in angiosperms with different life forms, and research on orchid-specific functional genes related to life-history trait evolution.</p