•We developed a hybrid multi-step ahead freeway traffic flow forecasting approach.•We analyze the traffic data as periodic trend, deterministic and volatility parts.•The hybrid method identifies and ...captures the periodic trend and traffic volatility.•The method improves the interpretability of the data by providing explicit equations.•The method generates accurate and reliable multi-step forecasts.
Short-term traffic flow prediction is a critical aspect of Intelligent Transportation System. Timely and accurate traffic forecasting results are necessary inputs for advanced traffic management systems (ATMS) and advanced traveler information systems (ATIS). Despite the proliferation of advanced methodologies, modeling the uncertainty of traffic conditions is still a challenge, especially during congested situations. This paper presents a hybrid model for multi-step ahead traffic flow forecasting in a freeway system with real-time traffic flow data. This proposed methodology forecasts traffic flow by decomposing the data into three modeling components: an intra-day or periodic trend by introducing the spectral analysis technique, a deterministic part modeled by the ARIMA model, and the volatility estimated by the GJR-GARCH model. The aim of this study is to provide deeper insights into underlining traffic patterns and to improve the prediction accuracy and reliability by modeling these patterns separately. The forecasting performance of the proposed hybrid model is investigated with real time freeway traffic flow data from Houston, Texas. The experimental results demonstrate that the proposed method is able to unearth the underlying periodic characteristics and volatility nature of traffic flow data and show promising abilities in improving the accuracy and reliability of freeway traffic flow forecasting in multi-step ahead forecasting.
Device-to-device (D2D) communication is viewed as one promising technology for boosting the capacity of wireless networks and the efficiency of resource management. D2D communication heavily depends ...on the participation of users in sharing contents. Thus, it is imperative to introduce new incentive mechanisms to motivate such user involvement. In this paper, a contract-theoretic approach is proposed to solve the problem of providing incentives for D2D communication in cellular networks. First, using the framework of contract theory, the users' preferences toward D2D communication are classified into a finite number of types, and the service trading between the base station and users is properly modeled. Next, necessary and sufficient conditions are derived to provide incentives for users' engagement in D2D communication. Finally, our analysis is extended to the case in which there is a continuum of users. Simulation results show that the contract can effectively incentivize users' participation, and increase capacity of the cellular network than the other mechanisms.
In device-to-device (D2D) communication, mobile users communicate directly without going through the base station. D2D commutation has the advantage of improving spectrum efficiency. But the ...interference introduced by resource sharing of D2D has become a significant challenge. In this paper, we try to optimize the system throughput while simultaneously meeting the quality of service (QoS) requirements for both D2D users and cellular users (CUs). We implement matching theory to solve the resource allocation problem. We utilize two efficient stable matching algorithms to optimize the social welfare while ensuring the network stability. More importantly, we introduce the idea of cheating in matching to further improve D2D users' throughput. It is proven that the cheating mechanism benefits a subset of D2D users without hurting the performance of the rest. Through the simulation results, we demonstrate the effectiveness of both the stable matching and cheating algorithms in terms of improving both D2D users and the overall throughput in D2D communications.
The prevalence of high performance mobile devices such as smartphones and tablets has brought fundamental changes to existing wireless networks. The growth of multimedia and location-based mobile ...services has exponentially increased network congestion and the demands for more wireless access. This has led to the development of advanced techniques to address the resulting challenges based on the concept of cooperation in various heterogeneous network scenarios. Thus, innovative incentive mechanisms in wireless networks are needed to ensure the participation of third party nodes, such as access points, small cells, and users. In this tutorial, we demonstrate the effectiveness of contract theory to design incentive mechanisms for a wide range of application scenarios in wireless networks. In contract theory, participants are offered properly designed rewards based on their performances to encourage better participation. First, we present an overview of basic concepts and models of contract theory, with comparisons to other related methods from economics. We then discuss incentive mechanisms, with a focus on the design of rewards in a contract. We demonstrate how contract theory can be utilized for developing effective incentive mechanisms for emerging wireless network scenarios such as traffic offloading, mobile crowdsourcing, and spectrum trading.
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•Three-dimensional (3D) porous lignin-modified graphene aerogel (LGA) was fabricated by one-step hydrothermal treatment.•The LGA was compressive, ultralight and fire-resistant with ...hydrophobic skeletons.•The LGA exhibits efficient selectivity, high capacity and good recyclability for oils and organic solvents.•The absorption capacity can be improved by carbonation treatment maximum up to 522 times.
Compressive, ultralight and fire-resistant graphene aerogel is facilely modified by renewable lignin biomass with hydrophobic and porous skeletons. The lignin-modified graphene aerogel (LGA) show highly efficient absorption of not only petroleum oils, but also toxic solvents such as toluene, chloroform and carbon tetrachloride (up to 350 times of its own weight), which is superior to that of graphene aerogel (GA) and among the highest in previous reported absorbents. Even after several compressive and release cycles, their absorption capacity are also maintained at 96%. Moreover, the absorption capacity can be further improved by carbonation treatment maximum up to 522 times of its own weight. Importantly, the LGA can be regenerated by repeated heat treatment and squeezing method, yielding almost full release of adsorbates. Such a high efficient, recyclable and renewable LGA exhibits it a potential candidate for applications in oil-water separation and also paves way to high-valued utilization of biomass waste.
Alkaline phosphatase (ALP) that is a crucial biomarker for the diagnosis of hepatobiliary and skeletal diseases is widely distributed in human bone, liver, intestine, placenta and other tissues. The ...abnormal level of ALP is also associated with some other diseases, such as extrahepatic biliary obstruction, intrahepatic space occupying lesions, rickets and cancers. In recent years, to understand the roles of ALP in these diseases, various fluorescent probes have been developed to detect ALP activity in serum, and image ALP in cells and tumor tissues. In this paper, we put the emphasis on the properties of these fluorescent probes and provided two tables for more intuitive understanding of their performance in ALP detection. We hope this review can provide some help and enlightenment for the future works.
•Detecting ALP activity is significant for the diagnosis of various diseases and understanding the roles of ALP in diseases.•The detection mechanisms of fluorescent sensors for ALP are summarized.•The performances of these fluorescent sensors are discussed for the analysis of ALP activity.•Some prospects for future research on constructing ALP sensors are proposed.
Device-to-device (D2D) communication is seen as a major technology to overcome the imminent wireless capacity crunch and to enable new application services. In this paper, a novel social-aware ...approach for optimizing D2D communication by exploiting two layers, namely the social network layer and the physical wireless network layer, is proposed. In particular, the physical layer D2D network is captured via the users' encounter histories. Subsequently, an approach, based on the so-called Indian Buffet Process, is proposed to model the distribution of contents in the users' online social networks. Given the social relations collected by the base station, a new algorithm for optimizing the traffic offloading process in D2D communications is developed. In addition, the Chernoff bound and approximated cumulative distribution function (cdf) of the offloaded traffic are derived and the validity of the bound and cdf is proven. Simulation results based on real traces demonstrate the effectiveness of our model and show that the proposed approach can offload the network's traffic successfully.
There are many factors that affect the compressive strength of concrete. The relationship between compressive strength and these factors is a complex nonlinear problem. Empirical formulas commonly ...used to predict the compressive strength of concrete are based on summarizing experimental data of several different mix proportions and curing periods, and their generality is poor. This article proposes an improved artificial bee colony algorithm (IABC) and a multilayer perceptron (MLP) coupled model for predicting the compressive strength of concrete. To address the shortcomings of the basic artificial bee colony algorithm, such as easily falling into local optima and slow convergence speed, this article introduces a Gaussian mutation operator into the basic artificial bee colony algorithm to optimize the initial honey source position and designs an MLP neural network model based on the improved artificial bee colony algorithm (IABC-MLP). Compared with traditional strength prediction models, the ABC-MLP model can better capture the nonlinear relationship of the compressive strength of concrete and achieve higher prediction accuracy when considering the compound effect of multiple factors. The IABC-MLP model built in this study is compared with the ABC-MLP and particle swarm optimization (PSO) coupling algorithms. The research shows that IABC can significantly improve the training and prediction accuracy of MLP. Compared with the ABC-MLP and PSO-MLP coupling models, the training accuracy of the IABC-MLP model is increased by 1.6% and 4.5%, respectively. This model is also compared with common individual learning algorithms such as MLP, decision tree (DT), support vector machine regression (SVR), and random forest algorithms (RF). Based on the comparison of prediction results, the proposed method shows excellent performance in all indicators and demonstrates the superiority of heuristic algorithms in predicting the compressive strength of concrete.
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•Nano-carbon powder or nano-Al2O3 addition showed positive effects on AD performance.•Nano-ZnO or nano-CuO addition showed negative effects on AD performance.•All conductive ...nanomaterials could shorten the lag phase of AD sludge.•Nano-ZnO and nano-CuO addition inhibited microbial community diversity and richness.
The effects of four conductive nanomaterials (nano-carbon powder, nano-Al2O3, nano-ZnO, nano-CuO) on sludge anaerobic digestion (AD) performance and microbial community were investigated through a 36-day fermentation experiment. Results showed that biogas production enhanced by 16.9% and 23.4% with nano-carbon powder and nano-Al2O3 added but decreased by 90.2% and 17.3% with nano-ZnO and nano-CuO. Total solids (TS) removal efficiency was increased by 38.73% and 27.11% with nano-carbon powder and nano-Al2O3 added but decreased by 70.67% and 43.70% with nano-ZnO and nano-CuO. Kinetic analysis indicated four conductive nanomaterials could shorten the lag phase of AD sludge with an average rate of 51.75%. 16S rRNA amplicon sequencing results demonstrated microbes such as Syntrophomonas and Methanosaeta were enriched in nano-carbon powder and nano-Al2O3 reactors. However, microbial community diversity and richness were both inhibited by adding nano-ZnO and nano-CuO. Redundancy analysis (RDA) revealed that genera belong to Firmicutes and Chloroflexi could conduce to methanogenesis process.
With the wide adoption of smart mobile devices, there is a rapid development of location-based services. One key feature of supporting a pleasant/excellent service is the access to adequate and ...comprehensive data, which can be obtained by mobile crowdsourcing. The main challenge in crowdsourcing is how the service provider (principal) incentivizes a large group of mobile users to participate. In this paper, we investigate the problem of designing a crowdsourcing tournament to maximize the principal's utility in crowdsourcing and provide continuous incentives for users by rewarding them based on the rank achieved. First, we model the user's utility of reward from achieving one of the winning ranks in the tournament. Then, the utility maximization problem of the principal is formulated, under the constraint that the user maximizes its own utility by choosing the optimal effort in the crowdsourcing tournament. Finally, we present numerical results to show the parameters' impact on the tournament design and compare the system performance under the different proposed incentive mechanisms. We show that by using the tournament, the principal successfully maximizes the utilities, and users obtain the continuous incentives to participate in the crowdsourcing activity.
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