bluuebunny/crossref_metadata_2025_split huggingface dataset:
A server consolidation method with integrated deep learning predictor in local storage based clouds
Authors: Zhang Guoliang , Bao Weidong , Zhu Xiaomin , Zhao Weiwei , Yan Huining 
Published: May 2018

SummaryServer consolidation is one of the critical techniques for energy‐efficiency in cloud data centers. As it is often assumed that cloud service instances (eg, Amazon EC2 instances) utilize the shared storage only. In recent years, however, cloud service providers have been providing local storage for cloud users, since local storage can offer a better performance with identified price. However, these cloud instances usually contain much more data than shared storage cloud instances. Thus, in such local storage based cloud center, the migration cost can be really high and is in dire need of an efficient resource pre‐allocation. If we can predict the resource demand in advance, the migration oscillation will be reduced to minify the migration cost. We have found that there are some related work about server consolidation based on forecasting. Unfortunately, their latest work did not consider the background of “local storage” as we mentioned above. At the same time, some research about local storage did not involve the prediction strategy, which plays a significant part in server consolidation. To address this issue, this paper proposes Losari, a consolidation method, which takes numeric forecasting and local storage architecture into consideration. Losari consolidates servers on the basis of the resource demand predicted value using a statistical learning method. We model the workload from real cloud production environment as a time series. Taking deep learning as a frame of reference, multiple deep belief networks integrated with ARIMA model was trained to study the feature of historical workload. The experimental results have showed that its average predicted error is only 10.7% in the short term, which is much lower than the most common model based on threshold (19.8%) on the same dataset. What is more, the results show that Losari not only simulates the true sequences in high accuracy but also scales the compute resource well, which demonstrated the validity of this integrated deep learning model.
Research on index weight of logistics integration based on cloud models
Authors: Qian Guo 
Published: May 2018

SummaryAccurate evaluation on development of logistics integration is conducive to the coordinated development in Beijing‐Tianjin‐Hebei region. Results of the index weight setting directly influence the accuracy of the evaluation results. Weight is cognition and evaluation of objective things made by human based on aspect of important degree of objective things. People's subjective initiative in setting index weight, in a sense, leads to the natural language having obvious fuzziness and randomness, uncertainty. In this paper, based on the research of weight setting in China and abroad, the weight system is designed qualitatively and quantitatively by using the cloud models so that the weight results are close to human cognition and easy to understand and accept.
A full‐duplex relay selection strategy based on potential game in cognitive cooperative networks
Authors: Zhanjun Liu , Zhaoyi Li , Yuxia Cheng , Xiaoge Huang , Qianbin Chen 
Published: May 2018

SummaryIn this paper, we study the full‐duplex relay selection strategy based on a potential game in a cognitive cooperative network under the interference power constraint from secondary users to the primary receivers, the total available transmission power constraint for the secondary system, and the self‐interference constraint at each secondary relay. The relay selection problem is modeled as a non‐cooperative game where the total rate of a cognitive cooperative network has common utility. Then, we prove that the game is a potential game that has at least a pure strategy Nash equilibrium (NE), and the optimal strategy set that able to maximize cognitive cooperative system rate is also a pure strategy NE of the proposed game model. On the premise of having no information of infeasible strategy sets, we solve the feasibility conditions of the pure NE in the proposed game. Furthermore, we propose a cognitive full‐duplex relay iterative algorithm that can achieve a pure strategy NE, and the complexity and the convergence of the proposed algorithm are studied. Simulation results show that the proposed algorithm can achieve optimal or near optimal rate performance with low complexity and offers significant performance gain compared with the traditional half‐duplex mode.
Adaptive predistortion algorithm based on the multilinear multiplier fusion
Authors: Shen Yijun , Zhang Guanhong 
Published: May 2018

SummaryAiming at solving the problem of the insufficiency in the predistortion structure and low accuracy of the memory nonlinear power amplifier in the wireless communication system, an adaptive predistortion method for dual loop learning structure based on the fusion of multilinear multiplier model recognition is put forward. On the basis of the real number delay multilinear multiplier model, an improved quantum behaved optimization (QBO) algorithm is adopted in this method to carry out indirect learning structure off‐line training of the multilinear multiplier, so as to determine the model parameters as an initial value of the predistorter. And then, the least square method (LSM) algorithm is used to carry out direct learning structure on‐line micro adjustment of the parameters of the predistorter and to conduct fitting on the nonlinearity and memory effect of the power amplifier. The method has the advantages of simple structure, fast convergence, and high precision, which has avoided the local optimum. The experimental results show that the adjacent channel power in this scheme is improved by approximately 7 dB compared with that of the classical dual loop structure predistortion method, and the linearization performance of the amplifier has been significantly improved, thus its feasibility has been verified.
Weight‐based strategy for an I/O‐intensive application at a cloud data center
Authors: Peng Junjie , Liu Danxu , Wang Yingtao , Zeng Ying , Cheng Feng , Zhang Wenqiang 
Published: May 2018

SummaryApplications with different characteristics in the cloud may have different resources preferences. However, traditional resource allocation and scheduling strategies rarely take into account the characteristics of applications. Considering that an I/O‐intensive application is a typical type of application and that frequent I/O accesses, especially small files randomly accessing the disk, may lead to an inefficient use of resources and reduce the quality of service (QoS) of applications, a weight allocation strategy is proposed based on the available resources that a physical server can provide as well as the characteristics of the applications. Using the weight obtained, a resource allocation and scheduling strategy is presented based on the specific application characteristics in the data center. Extensive experiments show that the strategy is correct and can guarantee a high concurrency of I/O per second (IOPS) in a cloud data center with high QoS. Additionally, the strategy can efficiently improve the utilization of the disk and resources of the data center without affecting the service quality of applications.
Self‐balancing robot bionic intelligence multi‐dimensional decision‐making evaluation algorithm
Authors: Ding Caichang , Chen Yiqin , Chen Lin , Zhong Baorong 
Published: May 2018

SummaryThe self‐balancing robot multi‐dimensional decision‐making evaluation (SRMDE) algorithm is a new bionic intelligent algorithm, which adopts an overall updating evaluation strategy for the solution. For solving the multi‐dimensional function optimization problem, due to the mutual interference between the various dimensions, the convergence rate and the quality of the solution will be deteriorated by using the overall update evaluation strategy. In order to compensate for this defect, a multi‐dimensional decision‐making algorithm for self‐balancing robot based on bionic intelligence is proposed. In the iterative process of the improved algorithm, updating evaluation strategy by the dimensionality is adopted for the solution. It combines the updated value of each dimension with the value of other dimensions to form a new solution and accept the update value using greedy way this can improve the solution quality. The results show that the improved strategy can effectively improve the convergence rate of the SRMDE algorithm, and the quality of the solution is improved. Compared with the relative improved self‐balancing robot multi‐dimensional decision‐making algorithm and other evolutionary algorithms, the improved algorithm is competitive in solving the continuous function optimization problem.
Improved collusion‐resisting secure nearest neighbor query over encrypted data in cloud
Authors: Zhu Youwen , Zhang Yue , Li Xingxin , Yan Hongyang , Li Jing 
Published: May 2018

SummarySecurely performing nearest neighbor query over encrypted data in cloud is an important topic in the area of cloud computing, for which Wang et al recently put forward a scheme (ie, CloudBI‐II) to address the challenging security problem: resisting the collusion of cloud server and query users. In this paper, we propose an efficient attack method that indicates CloudBI‐II will reveal the difference vectors under the collusion attack. Furthermore, we show that the difference vector disclosure will result in serious privacy breach and, thus, attain an efficient attack method to break CloudBI‐II. Namely, CloudBI‐II cannot achieve their declared security. Through theoretical analysis and experiment evaluation, we confirm that our proposed attack approach can fast recover the original data from the encrypted data set in CloudBI‐II. Finally, we provide an enhanced scheme that can efficiently resist the collusion attack.
Energy‐based tuning of metaheuristics for molecular docking on multi‐GPUs
Authors: Pérez‐Serrano J. , Imbernón B. , Cecilia J.M. , Ujaldón M. 
Published: May 2018

SummaryVirtual Screening (VS) methods simulate molecular interactions in silico to look for the best chemical compound that interacts with a given molecular target. VS is becoming increasingly popular to accelerate the drug discovery process and constitute hard optimization problems with a huge computational cost. To deal with these two challenges, we have created METADOCK, an application that (1) enables a wide range of metaheuristics through a parametrized schema and (2) promotes the use of a multi‐GPU environment within a heterogeneous cluster. Metaheuristics provide approximate solutions in a reasonable time frame, but, given the stochastic nature of real‐life procedures, the energy budget goes hand in hand with acceleration to validate the proposed solution. This paper evaluates energy trade‐offs and correlations with performance for a set of metaheuristics derived from METADOCK. We establish a solid inference from minimal power to maximal performance in GPUs, and from there, to optimal energy consumption. This way, ideal heuristics can be chosen according not only to best accuracy and performance but also to energy requirements. Our study starts with a preselection of parameterized metaheuristic functions, building blocks where we will find optimal patterns from power criteria while preserving parallelism through a GPU execution. We then establish a methodology to figure out the best instances of the parameterized kernels based on energy patterns obtained, which are analyzed from different viewpoints, ie, performance, average power, and total energy consumed. We also compare the best workload distributions for optimal performance and power efficiency among Pascal and Maxwell GPUs on popular Titan models. Our experimental results demonstrate that the most power efficient GPU can be overloaded in order to reduce the total amount of energy required by as much as 20%, finding unique scenarios where Maxwell does it better in execution time, but with Pascal always ahead in performance per watt, reaching peaks of up to 40%.
An urban location service for vehicular area networks
Authors: Nebbou Tawfiq , Lehsaini Mohamed , Fouchal Hacène , Ayaida Marwane 
Published: May 2018

SummaryPosition‐based routing, also called geographic routing, is widely recognised as an efficient routing approach for highly dynamic and mobile networks as vehicular ad hoc networks (VANETs). In this kind of networks, the high‐speed mobility of vehicles causes rapid changes on the network topology measured with vehicles density, limited‐time communication links, link failures, etc. In the meantime, the need of location service is a key issue; indeed, it will allow finding the position of a target node in order to reach it with a message. Some theoretical studies have proposed location services based on sharing nodes informations in different ways with hierarchy mechanism or with distribution mechanism or with centralization process. This paper proposes a location service deployed on RSUs (Road Side Units) for unicast routing over VANETs in urban environment. The proposed approach is able to measure the connectivity of a route. We propose then a new metric called Link Connectivity (LC) which measures this connectivity. Additionally, we have implemented our proposal using OMNET++ simulator and we have conducted extensive simulations with various scenarios to evaluate its scalability and robustness against frequent topology changes. As a conclusion, the proposed mechanism provides significant performance improvements in terms of packet delivery ratio, end‐to‐end delay, and overhead when it is compared to some other known proposals.
A sparse matrix‐vector multiplication method with low preprocessing cost
Authors: Aktemur Barış 
Published: May 2018

SummarySparse matrix‐vector multiplication (SpMV) is a crucial operation used for solving many engineering and scientific problems. In general, there is no single SpMV method that gives high performance for all sparse matrices. Even though there exist sparse matrix storage formats and SpMV implementations that yield high efficiency for certain matrix structures, using these methods may entail high preprocessing or format conversion costs. In this work, we present a new SpMV implementation, named CSRLenGoto, that can be utilized by preprocessing the Compressed Sparse Row (CSR) format of a matrix. This preprocessing phase is inexpensive enough for the associated cost to be compensated in just a few repetitions of the SpMV operation. CSRLenGoto is based on complete loop unrolling and gives performance improvements in particular for matrices whose mean row length is low. We parallelized our method by integrating it into a state‐of‐the‐art matrix partitioning approach as the kernel operation. We observed up to 2.46× and on the average 1.29× speedup with respect to Intel MKL's SpMV function for matrices with short‐ or medium‐length rows.
A Simple Strategy to Construct Amorphous Metal‐Free Room Temperature Phosphorescent and Multi‐Color Materials
Authors: Chen Peng‐Zhong , Chen Yu‐Zhe , Tung Chen‐Ho , Yang Qing‐Zheng 
Published: May 2018

AbstractIt is urgent to develop a universal strategy for producing small organic molecules exhibiting efficient room temperature phosphorescence (RTP). An important contribution made by Ma and Tian et al. provides a general and applicable strategy to obtain amorphous organic molecules with efficient RTP emission by simply modifying phosphors onto β‐cyclodextrin (β‐CD). The nonradiative decay processes and oxygen quenching have been significantly suppressed by the strong intermolecular hydrogen bonding between β‐CD derivatives. Furthermore, the cavity of β‐CDs endows them with the ability to incorporate the adamantane moiety of the fluorescent guest molecules to construct a supramolecular system which exhibits excellent RTP‐fluorescence dual emission properties and multicolor emission by altering the host to guest ratio and the excitation wavelength.
Why is Benzene Unique? Screening Magnetic Properties of C6H6Isomers
Authors: Janda Tomáš , Foroutan‐Nejad Cina 
Published: May 2018

AbstractMagnetic properties are commonly used to identify new aromatic molecules because it is generally believed that magnetization and energetic stability are correlated. To verify the potential correlation between the energy and magnetic response properties, we examined a set of 198 isomers of C6H6. The energy and magnetic properties of these molecules can be directly compared with no need to invoke any arbitrary reference state because the studied systems are all isomers. Benzene is the global minimum on the potential energy surface of C6H6, 35 kcal mol−1lower in energy than the second most stable isomer, fulvene. Unlike its electronic energy, isotropic magnetizability of benzene is slightly lower than the average magnetizability of its isomers. Altogether,44isomers of C6H6were identified to have more negative magnetic susceptibility than benzene but were between 67.0 to 168.6 kcal mol−1higher in energy than benzene. However, benzene is unique in two ways. Analyzing the paramagnetic contribution to the magnetic susceptibility as originally suggested by Bilde and Hansen (Mol. Phys., 1997,92, 237) revealed that53 molecules have lower paramagnetic susceptibility than benzene but amongmonocyclicsystems benzene has theleast paramagnetic susceptibility. Furthermore, benzene hasthe largest out‐of‐plane magnetic susceptibilitythat originates from thestrongest ring currentamong all studied species.
Metal‐ and Additive‐Free Oxidation of Sulfides into Sulfoxides by Fullerene‐Modified Carbon Nitride with Visible‐Light Illumination
Authors: Chen Xi , Deng Kejian , Zhou Peng , Zhang Zehui 
Published: May 2018

AbstractPhotocatalytic selective oxidation has attracted considerable attention as an environmentally friendly strategy for organic transformations. Some methods have been reported for the photocatalytic oxidation of sulfides into sulfoxides in recent years. However, the practical application of these processes is undermined by several challenges, such as low selectivity, sluggish reaction rates, the requirement of UV‐light irradiation, the use of additives, and the instability of the photocatalyst. Herein, a metal‐free C60/graphitic carbon nitride (g‐C3N4) composite photocatalyst was fabricated by a facile method, and well characterized by TEM, SEM, FTIR spectroscopy, XRD, X‐ray photoelectron spectroscopy, diffuse reflectance spectroscopy, and photoluminescence spectroscopy. The C60/g‐C3N4 catalyst exhibited a high photocatalytic activity at room temperature for the selective oxidation of sulfides into the corresponding sulfoxides in the presence of other functional groups, due to the synergetic roles of C60 and g‐C3N4. Several important parameters have been screened, and this method afforded good to excellent yields of sulfoxides under optimal conditions. The superoxide radical (.O2−) and singlet oxygen (1O2) were identified as the oxidative species for the oxidation of sulfides into sulfoxides by exploring EPR experiments, and hence, a plausible mechanism for this oxidation was proposed. Moreover, the C60/g‐C3N4 catalyst can be easily recovered by filtration and then reused at least four times without loss in activity.
GATE, a game theory approach on traffic volume aware channel width adaptation for WBAN medical applications
Authors: Manirabona Audace , Boudjit Saadi 
Published: May 2018

SummaryTraditional single channel communication in Wireless Sensor Networks (WSN) offers limited network throughput due to frequent interferences and congestion caused by concurrent transmissions in the same neighborhood. On the one hand, successful packet delivery requires mostly multiple retransmissions because of frequent collisions which also uses much battery. On the other hand, concurrent transmissions over multiple channels not only offer better network throughput and delays, but also reduce power consumption as packet collisions are minimized or eliminated depending upon the efficiency of the concerned channel assignment scheme. This may ensure QoS requirements of transmissions demanding high bandwidth and those that are delay sensitive such as in the case of wireless body area networks. In this paper, we consider a multiple channel wireless body area networks and propose GATE, a theoretical game approach to adapt the channel bandwidth to the volume traffic requirement. In this way, medical video and audio traffics which are likely to be much bandwidth consumer are mainly considered using their priority classes. The simulation results show good performances of the proposed system in terms of increasing throughput and significantly reducing delay and energy consumption.
Analysis of cis and trans 3‐methylfentanyl by liquid chromatography–high resolution mass spectrometry and findings in forensic toxicology casework
Authors: Fogarty Melissa F. , Papsun Donna M. , Logan Barry K. 
Published: May 2018

Abstract3‐methylfentanyl (3‐MF), N‐(3‐methyl‐1‐phenethyl‐4‐piperidyl)‐N‐phenyl‐propanamide, has reappeared on the US illicit drug market since its disappearance after a series of overdose deaths in 1988. 3‐MF presents an analytical challenge, due to presence of cis and trans stereoisomers, each with different potencies, and ultimately very low concentrations in the blood after use. A method was developed using liquid chromatography–time‐of‐flight–mass spectrometry for the analysis of (±)‐cis‐3‐MF and (±)‐trans‐3‐MF in blood specimens after solid phase extraction. The linear dynamic range of this method was 0.1–10 ng/mL. Blood samples from 25 postmortem cases and 2 human performance case involving 3‐MF were submitted for quantitative analysis. The mean and median concentration for the (±)‐cis‐3‐MF were 0.84 ng/mL (±0.81) and 0.67 ng/mL, respectively, range 0.14–3.43 ng/mL. The resulting (±)‐trans‐3‐MF mean concentration was 0.46 ng/mL (±0.38) and the median concentration was 0.37 ng/mL with a range of 0.11–1.90 ng/mL. The resulting (±)‐cis‐3‐MF and (±)‐trans‐3‐MF concentrations were summed to give the total amount of 3‐MF present in the case with the resulting average concentration at 1.28 ng/mL (±1.16), median at 1.01 ng/mL and range 0.18–5.18. As the estimated dose of this compound is approximately 0.1 mg–0.5 mg with the resulting concentrations in the sub‐nanogram range, it is necessary for forensic toxicology laboratories to obtain instruments sensitive enough to detect these substances in driving under the influence of drugs and postmortem cases. Quantitation of 3‐MF with separation of (±)‐cis and (±)‐trans‐3‐MF provides additional detail for more specific toxicological interpretation.