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Partial discharge (PD) detection and diagnosis based on the ultra-high frequency (UHF) signals is one of the most widely adopted methods to evaluate the internal insulation status of high voltage equipment. Benefit from the rapid development of computing hardware and data processing algorithms, the intelligent PD fault diagnosis method based on the UHF data has made considerable progress in the past two decades. This two-part paper aims to give a comprehensive review about the application of signal processing and machine learning technologies in UHF PD detection and diagnosis. These technologies are divided into three categories according to their respective purpose, which are the preprocessing technology, source localization technology and pattern recognition technology. As the first one of the two-part review, we focus on the preprocessing and localization approaches in this paper. Specifically, for the preprocessing topic, the methods for signal denoising, multi-source separation, and pulse segmentation are included. While for the localization topic, the time difference of arrival (TDOA) method, direction of arrival (DOA) method, received signal strength indicator (RSSI) method, and other latest methods are reviewed. For each topic, the basic ideas, recent research progresses, advantages and limitations are discussed in detail. Before the conclusion, we also make a discussion about the application effects of the above technologies and prospect some future directions accordingly. In the second paper, the pattern recognition problems based on the UHF PD data will be concentrated, especially the application of deep learning algorithms.

Purpose Monetary incentives have been widely adopted by brands to promote consumer engagement in their brand communities on social networking sites. This paper aims to explore how the interactions triggered by an emerging monetary incentive, red packets, affect consumers’ brand attitude in the context of WeChat brand groups (WCBGs). Design/methodology/approach According to whether brands ask for commercial returns from consumers, two types of interactions were identified, namely, exchange red packet interaction (ERPI) and communal red packet interaction (CRPI). The corresponding influences on brand attitude were examined in three experiments. Findings Compared to CRPIs, ERPIs elicit greater normative community pressure, inducing a less favorable brand attitude. Moreover, this impact is moderated by the time frame of brand communities. In the long-term WCBGs, a significant difference exists between ERPIs and CRPIs, while such difference attenuates or even disappears in short-term WCBGs. Practical implications When using red packets as an engagement strategy, brand managers should be alert to their potential negative influence. Specifically, in short-term brand communities, ERPIs enable managers to acquire commercial returns without hurting brand attitude. In long-term brand communities, managers are advised to implement CRPIs to foster a positive brand attitude. Originality/value This study investigates red packet interactions in brand communities, which have been widespread but unexplored. The results expand the literature by addressing the undermining effect of ERPI and the moderating effect of the time frame.

Ecosystem issues have been severely concerned and studied when the coal resource is one of major energy generators, and green mining innovation techniques involving artificial-restorations have addressed and significantly lessened negative impacts on the ecological environment. The ecosystem of a coal-mined area, however, is able to naturally restore with the processes of natural succession, similar to the human body system that has the immune ability to self-heal a wound over time if the wound does not deeply hurt the health. Here we analyze multiple discipline real data from two mining sites, and evidently show an ability of nature that the coal mining related problems such as geological cracks, damaged aquifers and destroyed soils in Quaternary period can naturally recover around a half-year after the end of mining. Our results temporally and spatially demonstrate that the damaged ecosystem has a capability of unaided nature-remediation from the ground to the subsurface, which is very useful to the countries worldwide with abundant coal reserves and intense energy demands for their development.

This paper focuses on the inventory management of agricultural products, a specific type of perishable items carrying the deterioration property. In practice, the deterioration rate of agricultural products is varying with time and can be slowed downviainvesting in the preservation technology. This objective of this paper is to maximize the firm’s total profit per unit time by simultaneously determining dynamic pricing, replenishment cycle length, replenishment quantity and preservation technology investment. We first derive pricing policy by solving a dynamic optimization problem and then propose a solution procedure to obtain the optimal strategies that maximize profit. Furthermore, numerical examples and sensitivity analysis are conducted to gain more managerial insights. We find that the firm should take a penetration pricing policy. In addition, if the shelf life of products is very long, the firm should not take preservation technology investment. When the unit holding cost is relatively small or the unit purchasing cost is relatively large, the firm should increase preservation technology investment.

Noting the rise of dominant retailers, we explore the retailer’s strategies to deter the manufacturer from encroaching in a retailer-led setting where the manufacturer keeps his own direct selling cost private. Our results show that the dominant retailer is always worse off while the manufacturer is always better off by manufacturer encroachment in a retailer-led supply chain when the fixed encroaching cost is negligible. This gives rise to a question that whether there exist effective anti-encroachment strategies for the retailer. We investigate a noted and prevailing strategy of retailers, retail service investing, to examine if it can help the retailer to prevent encroachment. Results show that the retail service level is reduced by encroachment. Retail service investing may actually be an effective anti-encroachment measure for the dominant retailer, especially when retail service investing is highly efficient and the retailer holds a great downward estimation deviation on the direct selling cost of the manufacturer. Retail service investing may lead to Pareto improvement for both the supply chain members and consumers. Additionally, the manufacturer may have incentives to share cost information with the retailer, depending on the retailer’s estimation deviation on the direct selling cost. Finally, we find that a prisoner’s dilemma may occur for a moderate fixed cost of encroachment.

Purpose: In order to compensate for the early intrauterine growth restriction, small-for-gestational age (SGA) infants have “catch-up growth” after birth. Increased caloric intake has been suggested for SGA infants conventionally. It is important to determine if the early growth rate of body mass index (BMI) is associated with risk of persistent obesity later in life. In this longitudinal cohort study, we assessed the BMI of a large cohort of children who were SGA at birth to determine their risk of persistent obesity at school age (6–7 years) due to excessive weight gain in the first 3 years of life.Methods: We collected the height and weight data of 23,871 SGA babies. A polynomial function was used to fit the BMI-for-age z-score (BAZ) values of 0–6 years old SGA children and interpolate their growth trajectory. In addition, we screened out 6,959 children from 23,871 children to further evaluate the dynamic changes of early childhood BMI. We divided the school-age children into groups as non-obese (BAZ < 2) and obese (BAZ > 2), and determined the association between changes in BMI and school-age obesity.Results: From the perspective of BMI distribution, the interpolated growth trajectory indicated that SGA children reaching overweight status or developing obesity by 3 years of age, continued to have obesity until school age (R2, 0.65; R2, 0.21). The retrospective analysis showed that children who were overweight and had obesity during school age had a high BMI from early age. By analyzing the changes in early BMI, we found that the fastest growth of SGA children occurred in the early infancy before 6 months and they continued to grow rapidly for a period of time. Interestingly, former SGA children who maintained a near overweight (1 < BAZ < 2) status before the age of 2 maintained an appropriate growth rate and usually did not develop obesity.Conclusions: A rapid increase in BMI during early infancy in former SGA newborns leads to a persistent risk of obesity. The energy intake of SGA infants should appropriately meet the infants' growth needs and early BMI changes should be closely monitored for an optimal integrated management.

Aiming at the problems of large storage error and low determination coefficient in traditional information storage model, a network privacy information storage model based on holographic digital watermarking technology is proposed. By identifying the network privacy information, the least square method is used to filter the non significant information of network privacy information, and the fuzzy adaptive equalization storage method is used to compensate the error of symbol output To the steady-state characteristic solution of network privacy information, the holographic digital watermarking technology is introduced to construct the network privacy information storage model. The experimental results show that the improved model can effectively reduce the root mean square error, improve the decision coefficient of information storage, and increase the effect of storage.

Aiming at the problems of low accuracy and long time consuming in traditional block based secure storage method, a block based secure storage method of network information resources based on data sensitivity analysis is proposed. Relying on the big data network environment, the required storage network information resources are classified according to their storage capacity and computing capacity, and the block processing is realized according to the classification results combined with resource sensitivity; the block security storage model of network information resources is constructed through deviation compensation. The results show that the block storage method of network information resources based on data sensitivity analysis meets the design requirements, and it is safe, efficient and implementable.

The computed tomography (CT) reconstruction algorithm is one of the crucial components of the CT system. To date, total variation (TV) has been widely used in CT reconstruction algorithms. Although TV utilizes the a priori information of the longitudinal and lateral gradient sparsity of an image, it introduces some staircase artifacts. To overcome the current limitations of TV and improve imaging quality, we propose a multidirectional anisotropic total variation (MATV) that uses multidirectional gradient information. The surrounding rock of coal mining faces uses principles of tomography similar to those of medical X-rays. The velocity distribution for the surrounding rock can be obtained by the first-arrival traveltime tomography of the transmitted waves in the coal mining face. Combined with the geological data, we can interpret the geological hazards in the coal mining face. To perform traveltime tomography, we first established the objective function of the first-arrival traveltime tomography of the transmitted waves based on the MATV regularization and then used the split Bregman method to solve the objective function. The simulated data and real data show that the MATV regularization method proposed in this paper can better maintain the boundaries of geological anomalies and reduce the artifacts compared with the isotropic total variation regularization method and the anisotropic total variation regularization method. Furthermore, this approach describes the distribution of geological anomalies more accurately and effectively and improves imaging accuracy.

As information technology slowly penetrates into people’s daily lives, the application range of computer networks has become wider and wider, becoming one of the indispensable communication methods for people. The popularization of computer networks in the information age has brought great convenience to people on the one hand, but also has major hidden dangers that damage public privacy and safety. Enterprises must not only rely on computer networks and databases to share data, but also protect sensitive and valuable data from being stolen or tampered with. By trying to analyze the current status of information security protection strategies, this paper proposes an information security evaluation method in a complex network environment to guide information security protection work and provide a reference for evaluating the effectiveness of network protection.

Consumer uncertainty about product valuation is a significant economic issue in online retailing. In many markets, even though the product quality information is completely disclosed, consumers may still remain unsure about their valuation-for-quality. This paper investigates the effects of consumers’ uncertain valuation-for-quality on a platform’s and a firm’s profits under commonly used wholesale price contract and consignment contract in a distribution channel. Our analysis reveals that regardless of the contract types, when the product quality is relatively low, both the platform and the firm benefit from a higher degree of informativeness of information; when the product quality is relatively high, however, the profits of both the platform and the firm show nonmonotonicity with respect to the informativeness degree (namely, first decrease then increase), which is driven by the joint effects of the value-enhancement effect and the segmentation effect incurred from the consumers’ uncertain valuation-for-quality. Additionally, we find that when the quality is of medium level, the firm and the platform may achieve a consensus on contract preferences on the wholesale price contract or the consignment contract, critically dependent on the informative degree.

With the booming of online mobile games (OMGs), game operators need to provide high-quality game service for users. Using relay has become the de factor approach for game streaming today, because it is easy to use (e.g., game sessions can be redirected via CDN servers) and has good scalability. Today, it has become the norm rather than the exception for game operators to hire CDN servers for their game services in a pay-per-use manner to serve massive users. Given the limited resource, selecting game sessions which are relayed has become a critical decision that can significantly affect users' quality of experience (QoE). Conventional strategies are generally rule-based, e.g., assigning game sessions to relay paths according to their past network performance, but cannot guarantee any particular QoE level because network performance dynamically changes. In this paper, we propose using data-driven approach to study network performance of game sessions in temporal and spatial patterns. Our findings indicate that there is obvious regularity for network performance of game sessions in temporal and spatial patterns. We design a machine learning-based predictive model to capture the quality of a game session given particular network performance metrics. Based on that, we strategically assign game sessions to relay paths to maximize the overall QoE. Trace-driven experiments are used to demonstrate the effectiveness and efficiency of our design.

Most children with autism spectrum disorder (ASD) are not diagnosed until the age of 4, thus missing the opportunity for early intervention. The objective of this study was to investigate the feasibility of an early screening program for ASD applied during well-child visits in a community-based sample. The study lasted for 4 years and was divided into two stages. Stage I involved the implementation of the basic screening model in 2014. Toddlers received level 1 screening via section A of the Chinese-validated version of the Checklist for Autism in Toddlers (CHAT-23) during 18- and 24-month well-child visits in Xuhui District, Shanghai, China. Screen-positive children were referred to receive section B of the CHAT-23 for level 2 screening, and those still screen-positive were referred to undergo diagnosis and evaluation. Stage II involved the implementation of the improved screening model from 2015 to 2017 with the following modifications: (a) an added observational component in level 1 screening; (b) telephone follow-ups with the screen-positive families; and (c) dissemination of information on ASD to families. The results showed that 42 of 22,247 screened children were diagnosed with ASD. The ASD diagnosis rates were 0.1% in Stage I and 0.21% in Stage II. The screen-positive rate and the show rate of referral for level 1 screening increased by 76.92% and 58.43%, respectively, in Stage II compared to Stage I. Our results suggest that with appropriate logistic support, this two-level screening model is feasible and effective for the early screening of ASD during well-child visits. Autism Res 2018, 11: 1206-1217. © 2018 International Society for Autism Research, Wiley Periodicals, Inc. LAY SUMMARY: Difficulty in the timely identification of autism spectrum disorder (ASD) results in missed opportunities for many ASD children to receive early intervention. In this study, we established an early screening model for ASD among children aged 18-24 months in the community by relying on the three-level child healthcare system in China. The results showed that this model can effectively identify and diagnose ASD in children at an early age and thus enable early intervention.

This article examines the link between corporate social responsibility(CSR) and cost of bond(COB) in China. We find that there exists a negative relationship between CSR and COB. In particular, when the bond issuer is a state-owned enterprise, or when the credit rating of bond is high, the negative association between CSR and COB is strengthened. The findings indicate that CSR plays a significant role in reducing the risk premium of corporate bonds through an insurance-like effect. Moreover, the effect of CSR on COB also depends on contextual factors such as firm ownership and bond credit rating.

The rapid development of online ride-hailing sharing economic platform provided an efficient way to mitigate the carbon emission of modern traffic in China. However, its development was blocked by the social management system whose update is relatively slow. How to resolve the conflict between the new economic paradigm development under the technology empowerment and the old public administration system and effectively solve the new economic and social problems it brought by are the major challenges for the healthy and sustainable development of this type of sharing economy. To shed light on the solutions to such conflict, the present paper conducts a case study on China’s largest online ride-hailing platform ‘Didi Chuxing’. The results indicate that the separation of ownership and use rights following the sharing economy brings a new approach to the efficient use of resources. The development of Didi displays a bottom-up policy innovation and institutional change. The path choice of enterprise development will affect its acquisition of legitimacy to a great extent. In this mobile Internet era, the public plays a critical role in shaping the new policy.

The ultra-high frequency (UHF) partial discharge (PD) monitoring is one of the most effective ways to detect the insulation failure in electrical equipment. Although the UHF method avoids the intensive low-frequency noise, various electromagnetic interferences in substation can still influence its effectiveness and reliability. Most existing denoising algorithms, however, are unable to suppress different kinds of noise simultaneously. Meanwhile, the main focus of these algorithms is on the degree of noise reduction, while pay little attention to feature preservation. Therefore, a novel denoising method namely optimised variation mode decomposition and wavelet (OVMDW) is developed in this paper. In OVMDW, an optimised variational mode decomposition (VMD) algorithm is presented firstly to decompose the original signal into several band-limited modes. Then, a determination rule is designed to identify the effective components from these modes. Finally, the wavelet-based denoising method is employed to remove the residual white noise. Denoising results for simulative and experimental data show that the proposed method can remove various interferences from UHF PD signals. Additionally, new indexes are introduced to evaluate the performance of denoising algorithms in practical situations. Comparison results based on these indexes reveal that the proposed method using the VMD approach can preserve quite well the features of original signals.

Ultra-high-frequency (UHF) partial discharge (PD) detection has been proved as a powerful tool to evaluate the status of electrical equipment. Unfortunately, on-site UHF detection suffers from intensive noise interference and great computational burden, which have long been the key bottleneck for its wide utilization in the field environments. In order to provide more valuable information for subsequent processing like PD location, pattern recognition, or severity assessment, a combined preprocessing method for UHF PD detection is proposed in this paper. This scheme integrates a novel Ensemble Empirical Mode Decomposition-based signal reconstruction method and a kurtosis-based pulse window extraction method. To demonstrate the effectiveness of the presented technique, both simulated and laboratory measured PD data are obtained and further tested. Results reveal that this preprocessing method can accurately detect and extract the PD pulse from raw data, which may lessen the computational burden for...

Partial discharge (PD) detection and recognition are of great significance to the condition monitoring of gas-insulated switchgear (GIS). In the current work, ultra-high-frequency (UHF) signals induced by PD current pulses are measured and used to represent PD source. For PD classification, feature parameters need to be extracted from UHF signals. Therefore, this study proposes a new feature extraction method that is based on S-transform (ST) and singular value decomposition (SVD). PD UHF signals generated by four kinds of artificial defects are collected and analysed. ST is used to acquire the joint time–frequency information of the PD UHF signal. SVD is used to acquire the time–frequency characteristics of the UHF signal. Based on the distribution difference of time–frequency characteristics of different kinds of PDs, a 24-demensional feature vector is finally extracted. Support vector machine optimised by particle swarm optimisation algorithm is employed as classifier to recognise the four kinds of PDs. Results show that the proposed feature extraction method can effectively identify the designed four kinds of PDs even with few samples and strong background noise.

As one of the most effective detection methods for partial discharge (PD), analysis of the radiated electromagnetic (EM) signals detected by ultra high frequency (UHF) sensor has gained broad attentions. However, the main bottlenecks for this method are probably the massive storage requirements and various noise interferences. Therefore, this paper is focused on investigating a new pulse segmentation technique, which is capable of separating PD pulses from noisy measured data to save the storage space and improve the signal noise ratio (SNR). First, a designed average multi-scale morphological dilate-erode filter (AMMDEF) is developed to obtain the smooth envelope shape of PD pulses. Then, instantaneous phase (IP) of the envelope shape is calculated by the Hilbert Transform (HT) and further smoothed using AMMDEF. Finally, a robust IP based boundary identification criterion (IPBIC) is proposed to accurately extract PD pulses from raw data. Various experiments have been carried out and results show that this method could achieve an average detection error rate (DER) at 0.1375 and an average absolute precision error (APE) at 23.1 ns respectively, even the SNR of signal is as low as 0 dB. Superiority of the developed method over traditional pulse segmentation techniques is also demonstrated.

The Internet is the darling of the information age. Its rapid development has brought a lot of wealth to the society, but it has also brought about increasingly serious security problems. In particular, the widespread application of e-commerce has made network security the most important part of the development of network technology. Network security technology is increasingly valued by computer researchers. Most of the existing security products are passive. The firewall can only be statically disabled. Although the Intrusion Detection System can dynamically detect the intrusion behavior, it cannot block the detected attack behavior. However, the impact of the intrusion prevention system on network performance and the high intrusion detection false alarm rate restrict the development and application of the IPS system. Especially on gigabit high-speed networks, performance has become the primary bottleneck of IPS systems. In view of the above problems, this paper proposes a distributed intrusion detection and blocking system that can run efficiently on high-speed networks. Such systems are also known as intrusion prevention systems IPS. Explain the structure of distributed high-speed network intrusion prevention system, and also introduce the related implementation technology and the realization of each part of distributed intrusion prevention system.

In the era of rapid development of Internet technology, more and more Web application systems have emerged, and the security problems of Web applications have become more prominent. This paper analyzes the vulnerability detection methods of Web application systems and analyzes the scanners of black box testing. And the characteristics of the white box test tool, the scanner detects fast but can not locate the loophole, proposes a web application system vulnerability location method based on dynamic stain analysis technology, designs the system prototype and conducts experimental verification and testing.

This paper considers a supply chain where a manufacturer builds the capacity and sets the wholesale price, and a retailer sets retail price and holds the advantage of demand information. There are two means to solve supply-demand mismatch: the retailer makes the forecast information-sharing strategy, and the manufacturer chooses volume flexibility that can postpone production after demand is observed. We focus on the retailer’s incentive for sharing private forecast information which is made to affect the follow-up action of manufacturer’s volume flexibility choice. A multi-stage game is formulated and the equilibria are obtained. It is shown that if the market fluctuation is relatively large, the manufacturer is more willing to choose volume flexibility under information sharing than under no information sharing; otherwise, the manufacturer is less willing to choose volume flexibility under information sharing than under no information sharing. Further, when the investment cost is relatively large and market fluctuation is relatively small, there may arise a prisoner’s dilemma, such that neither means (information sharing or volume flexibility) is taken, but higher profits are attained through implementing the two means. Last, if information-sharing commitment is made after volume flexibility choice, the retailer never shares the forecast information when the manufacturer commits to choosing volume flexibility, which enlarges the system parameter region for the prisoner’s dilemma occurring. Thus, it is optimal for both parties with the information-sharing decision made before volume flexibility choice.

This article examines the intra-industry market reaction to successive environmental accidents associated with Sinopec and PetroChina in China. Evidence indicates that a significantly negative intra-industry reaction occurred after these accidents. Furthermore, intra-industry firms with ex-ante environmental disclosures experienced a less negative reaction after successive accidents. Specifically, the mitigating effect of ex-ante environmental disclosures has certain extent of time delay, which differs from the immediate impact of ex-ante environmental disclosure within the context of developed countries.

This article examines the link between corporate social responsibility and cost of bank loans in China. We find that there exists an inverse U-shape relationship between CSR and CBL. In addition, CSR threshold for SOEs is higher than for non-SOEs. In particular, CSR threshold for SOEs is lower in regions with high degree of marketization than in regions with low degree of marketization. The findings indicate that value-destroying effect occurs during CSR under-investment phase which is different from the over-investment view. Moreover, the effect of CSR on CBL also depends on contextual factors such as firm ownership and marketization level.

The rapid development of society has made the production and living requirements of electrical energy supply higher and higher. Large-scale data collection and analysis of people’s lives and social production, and making corresponding judgments based on the results, are of great significance for optimizing power planning, saving energy and reducing emissions, facilitating residents’ lives, and coordinating social production. State Grid Co., Ltd. proposes to build “three types of two networks”, in which the ubiquitous power Internet of Things shoulders the existing power grid and further communicates the tasks of the user side and the generation, transmission and distribution side. In terms of function, the ubiquitous power IoT can be basically divided into four structures: perception layer, network layer, node centre and dispatch layer. According to the role of each structure, the development and construction are targeted. The system coordinates the construction of the ubiquitous power Internet of Things based on the overall structure, so that things are connected and characters interact, and a shared energy interconnection ecosystem is built.

Online mobile game (OMG) is booming recently, which has driven user expectations for high-quality game service. Therefore, it is crucial for game operators to understand if and how system factors (i.e. network quality metrics such as delay and mobile phone's rendering performance such as frame rate) affect gaming experience and how to optimize resource allocation to improve it. This paper is a first step towards addressing these problems. Despite the rich literature on multimedia services and Quality of Experience (QoE) measurement, the understanding of gaming experience is limited because the game platform shifts from traditional PC end to the mobile end, which has yet to be explored in depth. Based on a large-scale dataset collected from Honour of Kings, the world's top grossing mobile game, we carry out elaborate studies to explore gaming experience from the aspects of user behavior and game quality. Our key findings are as follows. First, user behavior is mainly limited to the game logic itself, such as I of a game is restricted by game rules. Therefore, it cannot well represent gaming experience. Second, among all system factors, the biggest impact on game quality comes from network performance rather than the frame rate of device, which is different from the influence mode in PC games. Third, some context factors, such as AP/BaseStations used by mobile phones, can have an indirect but huge impact on gaming experience. Based on the above observations, we provide insights that can enhance OMG's system from the perspective of resource allocation and real-time gaming experience monitoring. To the best of our knowledge, we are the first to conduct large-scale measurement to study gaming experience of OMGs in the wild. We believe our study is not only crucial for the understanding of gaming experience, but also helpful for game operators to optimize their systems.

In China, south of the Yangtze River, there are a large number of carbon sources, while the Sichuan Basin is the largest sedimentary basin; it makes sense to select the targets for CO2 geological storage (CGUS) early demonstration. For CO2 enhanced oil and gas, coal bed methane recovery (CO2-EOR, EGR, and ECBM), or storage in these depleted fields, the existing oil, gas fields, or coal seams could be the target areas in the mesoscale. This paper proposed a methodology of GIS superimposed multisource information assessment of geological suitability for CO2 enhanced water recovery (CO2-EWR) or only storage in deep saline aquifers. The potential per unit area of deep saline aquifers CO2 storage in Central Sichuan is generally greater than 50 × 104 t/km2 at P50 probability level, with Xujiahe group being the main reservoir. CO2 storage potential of depleted gas fields is 53.73 × 108 t, while it is 33.85 × 108 t by using CO2-EGR technology. This paper recommended that early implementation of CGUS could be carried out in the deep saline aquifers and depleted gas fields in the Sichuan Basin, especially that of the latter because of excellent traps, rich geological data, and well-run infrastructures.

Using content delivery networks (CDNs) for video distribution has become a de facto approach for today's video streaming, due to the easy usage and good scalability. Today, it has become a norm rather than an exception for video providers to hire multiple cloud CDNs for their video services in a pay-per-use manner, to not only serve users at different locations, but also reduce the operation costs. Given the multiple CDNs and their peering servers at many different locations, mapping a user to an edge CDN server has become a critical decision that can affect the quality of experience (QoE) of users. Conventional user mapping strategies are generally rule-based, e.g., assigning users to CDN servers according to only their locations or ISPs, which cannot guarantee any QoE. In this paper, we first propose to use a data-driven approach to study factors determining the streaming QoE in the multi-cloud CDN paradigm. Our findings suggest that the streaming QoE is affected by a combination of not only network factors but also user factors including their preference of video content. Then, we design a machine learning based predictive model to capture the QoE given the network conditions and user preference. Finally, we formulate the user mapping problem as an optimization problem and design algorithms to solve it: our algorithms identify users whose QoE are mostly affected by QoS and assign users to CDN servers so that the overall QoE can be maximized. Trace-driven experiments further verify the effectiveness of our design.

Much empirical evidence shows that many real-world networks fall into the broad class of small-world networks and have a modular structure. The modularity has been revealed to have an important effect on cascading failure in isolated networks. However, the corresponding results for interdependent modular small-world networks remain missing. In this paper, we investigate the relationship between cascading failures and the intra-modular rewiring probabilities and inter-modular connections under different coupling preferences, i.e. random coupling with modules (RCWM), assortative coupling in modules (ACIM) and assortative coupling with modules (ACWM). The size of the largest connected component is used to evaluate the robustness from global and local perspectives. Numerical results indicate that increasing intra-modular rewiring probabilities and inter-modular connections can improve the robustness of interdependent modular small-world networks under intra-attacks and inter-attacks. Meanwhile, experiments on three coupling strategies demonstrate that ACIM has a better effect on preventing the cascading failures compared with RCWM and ACWM. These results can be helpful to allocate and optimize the topological structure of interdependent modular small-world networks to improve the robustness of such networks.

Seismic physical modeling technique is a kind of experimental methods, the seismic physical modeling experiments are mainly used for the exploration and development of oil and gas, this technique in the coal fields is rarely used to solve practical problems at present. In order to achieve the fine exploration of the geological condition of coal seam, aimed at the geological conditions of the coalfield,the distribution of coal strata and lithologic features,completes the production seismic geology model of coal measure strata. The results show seismic physical modeling can simulate the typical geologic structure of coal mine, simulate complex geological phenomenon of coal mine, validate mathematical calculation method, validate related theory, reduce costs, also introduce the prospect of coal seismic physical modeling technology.

To meet the needs of high-accuracy seismic sampling, a kind of 32-bit high performance digital geophone was designed. The digital geophone was designed with the high performance, low power microcontroller MSP430F1232 as the acquisition controller and the 32-bit high-resolution analog-to-digital converter-ADS1282 as a central part. The digital geophone was able to achieve such functions: one channel seismic vibrations gathering, data converting, data memorizing and data transmitting. By using the internal function of ADS1282 and adopting anti-jamming manner, not only the circuit was simplified, but also the acquisition quality and system stability was assured. The features of ADS1282 are introduced in the paper. The hardware composing, the interface of the digital geophone with MSP430 and the sampling control flow chart are also introduced. The digital geophone is suitable for the application that has strict demands on power, size and precision.

In order to meet the needs of application in high resolution seismic data acquisition, a kind of 24-bit high performance digital geophone was designed. The digital geophone was designed with MSP430F1232 as controller and a new kind of ferroelectric memory FM25L256 as data storage. The operation principle of FM25L256, the application interface circuit and testing program in C-language are introduced in the text. The testing program has been validated on the board, result shows that the FM25L256 has such characteristic: high-speed writing, right storage and high reliability. It is suitable for the design demanding of the digital geophone which is low power, small size, high-speed sampling and memory.

In order to meet the needs of the new technology in mine seismic prospecting, a new intrinsic safe distributed 3-component seismic data acquisition system is developed, which is composed of several digital 3-compoent geophones, one portable host computer and data processing software. The host computer is composed of a high performance 32-bit embedded microprocessor PXA270 and corresponding software, it is able to monitor and manage the digital geophones and has the ability of some timely data processing. The digital geophone with high performance seismic data acquisition circuit which is based on MCU, has the ability of sampling and transmitting the data of the 3-component seismic signal. The acquisition system adopt distributed control mode and the information is transmitted by network based on RS-485 bus. The system has the strong ability of anti-interference, and the geophones can be easily assembled or take down. Furthermore, the whole system is intrinsic safety. This paper mainly introduces the development about digital 3-compoent geophones and portable host computer, the construction of data transmission system, the development of the data processing software and some applications of this system.

As one of the most important mesoscopic properties of networks, the community structure plays an important role in cascading failures on isolated networks. However, the study for understanding the influences of the community structure on the cascading failures on interdependent scale-free networks remains missing. In this paper, we investigate cascading failures on interdependent modular scale-free networks under inner attacks and hub attacks from the global and local perspective. We mainly analyse the inter-community connections and coupling preferences, i.e. random coupling in communities (RCIC), assortative coupling in communities (ACIC) and assortative coupling with communities (ACWC). We find that increasing inter-community connections can enhance the robustness of interdependent modular scale-free networks for both inner attacks and hub attacks. Furthermore, we also find that the ACIC is more beneficial to resisting cascading failures compared with RCIC or ACWC. For ACIC, the cascading failures propagate mainly in a local community where the initial failure occurs. It is meaningful to control the cascading failures on interdependent modular scale-free networks by constructing ACIC.

The issue of quality of service is becoming increasingly important in the public area as a result of new public management reform. This paper mainly discusses on defining and measuring quality in public areas. The content includes explaining the changing quality concepts in the public areas, selecting the right quality measures and indicators and involving the right stakeholders during the measuring process.

To study the impact of modern coal mining on overlying strata and its water bearing conditions, integrated time-lapse geophysical prospecting integrating 3D seismic, electrical and ground penetrating radar method were used. Through observing and analyzing the geophysical data variations of all stages of pre-mining, mining and post-mining as well as post-mining deposition stable period, impacts of coal mining on stratigraphic structure and its water bearing were studied and modern coal mining induced stratigraphic change pattern was summarized. The research result shows that the stratigraphic structure and the water bearing of surface layer during modern coal mining have self-healing pattern with mining time; the self-healing capability of near-surface strata is relatively strong while the roof weak; water bearing self-healing of near-surface strata is relatively high while the roof strata adjacent to mined coal beds low. Due to integrated time-lapse geophysical prospecting technology has extra time dimension which makes up the deficiency of static analysis of conventional geophysical methods, it can better highlight the dynamic changes of modern coal mining induced overburden strata and its water bearing conditions.