Lithium-ion batteries are currently widely employed in a variety of applications. Precise estimation the remaining useful life (RUL) lithium-ion holds significant function intelligent battery management systems (BMS). Therefore, order to increase fidelity and stabilization predicting RUL batteries, this paper, an innovative strategy for prediction is proposed by integrating one-dimensional convolutional neural network (1D CNN) bilayer long short-term memory (BLSTM) network. Feature...

Social media analytics has many applications in collective behavior sensing and monitoring, online advertisement, opinion mining, etc. Though a number of technologies systems are proposed for analyzing social data, the overall performance advantages those not compared under similar settings. In this paper, benchmark named as BSMA, Benchmarking Media Analytics, is proposed. It distinguishes with other effort that: 1) A real-life dataset activties more than 1.6 million users 2 years followship...

The demonstration of a benchmark, named as BSMA, for Benchmarking Social Media Analytics, is introduced in this paper. BSMA designed to benchmark data management systems supporting analytical queries over social media. It different existing benchmarks that: 1) Both real-life and synthetic generator are provided. dataset contains network 1.6 million users, all their tweeting retweeting activities. can generate both networks timelines that follow distributions determined by predefined...

Certificateless aggregate signature (CLASS) scheme which combines on certificateless and aggregation solves the identity-based (ID) public key infrastructure (PKI)'s escrow problem, PK problem of traditional PKI. So, CLASS schemes can be applied in many fields to solve privacy security for example information network system medicine biology. Also there are proposed these fields. In this manuscript, we analyze VANETs 2018 is more efficient than other similar schemes. We find cannot satisfy...

Graph neural networks (GNNs) have recently demonstrated significant success. Active learning for GNNs aims to query the valuable samples from unlabeled data annotation maximize GNNs' performance at a low cost. However, most existing methods reinforced active in may lead highly imbalanced class distribution, especially skewed scenarios. This further adversely affects classification performance. To tackle this issue, paper, we propose novel class-balanced framework GNNs, namely, GraphCBAL. It...

Graph neural networks (GNNs) have recently demonstrated significant success. Active learning for GNNs aims to query the valuable samples from unlabeled data annotation maximize GNNs' performance at a low cost. However, most existing methods reinforced active in may lead highly imbalanced class distribution, especially skewed scenarios. This further adversely affects classification performance. To tackle this issue, paper, we propose novel class-balanced framework GNNs, namely, GraphCBAL. It...

Accurate origin-destination (OD) passenger flow prediction is crucial for enhancing metro system efficiency, optimizing scheduling, and improving experiences. However, current models often fail to effectively capture the asynchronous departure characteristics of OD flows underutilize inflow outflow data, which limits their accuracy. To address these issues, we propose CSP-AIT-Net, a novel spatiotemporal graph attention framework designed enhance by incorporating tracking advanced station...

In the traditional signature, anyone with public key of signer can verify validation a signature which is not suitable in some scenes where needs keeps data privacy signer. Certificateless aggregate (CL-AS) scheme solves problem two part private keys from generation center and CL-AS also reduce verification cost due to aggregation property. this manuscript, we first give security analysis on proposed recently. The detail describe types attacks shows that secure malicious enemy forgeabile an...

A framework of synthetic data generator to generate social media timeline structures is proposed in this paper, which useful for benchmarking query processing over data, and validating hypothesis users' behavior. It flexible with different distributions. With the help its asynchronized parallel model delayed update strategy, it efficient feed out structure high throughput. We show experiments that our method can realistic efficiently.

In this paper, we study the path based continuous spatial keyword queries, which find answer set continuously when query point moves on a given path. Under setting, explore two primitive namely k nearest neighbor and range query. The technical challenges lie in that: (1) retrieving qualified vertices large road networks efficiently, (2) issuing for points path, turns out to be inapplicable. To overcome above challenges, first propose backbone network index structure (BNI), supports distance...

More and more security privacy issues have been exposed which lead to the urgent requirement of solving privacy. Many universities colleges offer course education cryptography make it be an important compulsory course. However, as key technology is very theoretical hard mastered by students. In this paper, we use hot cryptosystem - certificateless signature scheme teaching case. By adopting two current schemes, analyze existing design problems these schemes in education. We give details...

Various analytical methods are applied on social media data for opinion mining, user recommondation, product advertising, and etc. They share the common requirement collecting massive data, among which messages hotspot events mostly valuable understanding users' intensions. Apparently, sampling global timeline evenly cannot meet requirement, because it may miss important messages. In this paper, a method streams, named as RS <sup xmlns:mml="http://www.w3.org/1998/Math/MathML"...

In this paper, a matching algorithm of general graph based on depth-first traversal is proposed.The does not need to shrink and expand treatment when flower searched.This algorithm's time complexity search an augmenting path equal corresponding graph's complexity, it one the most efficient algorithm.Experiments show that can correctly handle associated practical problems, have correct conclusion.

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目的 研究角质细胞生长因子(KGF)联合粒细胞集落刺激因子(G-CSF)对受照小鼠造血及重要脏器的放射防护作用。 方法 将6至8周龄C57BL/6小鼠共70只随机分成5组:空白对照组、单纯照射组、KGF给药组、G-CSF给药组、KGF联合G-CSF给药组, 经137Cs-γ射线一次性全身照射后分别给药, 通过体重、脏器指数、各脏器SOD活性、MDA含量和外周血(WBC、RBC、Hb、PLT)等指标分析KGF及G-CSF对其血液和重要脏器的影响。 结果 受照后, KGF组与G-CSF组小鼠体重回升较明显; 与G-CSF组相比, 联合组肺指数差异有统计学意义(P 结论 本研究表明联合组对小鼠造血系统的修复优于其他给药组; G- CSF对于肝脏和心脏的抗氧化能力更有效; KGF对于肺部的抗氧化能力更有效。