bluuebunny/crossref_metadata_2025 huggingface dataset:
Acoustical multi-frequency filtering by a defective asymmetric phononic serial loop structure
Authors: El kadmiri Ilyass , Elamri Fatima Zahra , Ben Ali Youssef , Khaled Aissam , Kerkour El Miad Abdelhamid , Bria Driss
Published: July 2020

In this paper, we investigate the existence of defect modes in the phononic band structure and in the transmission spectrum of a one-dimensional phononic asymmetric loop (ASL) structure. This structure exhibits large acoustic bandgaps that originate both from the periodicity of the system and the loop resonant modes that create zeros of transmission. The defect modes result from the presence of a defective segments and loops in the ASL structure and may occur in these gaps. The localized states (defect modes) appear as very narrow peaks in the transmission spectrum and in the map of transmission of a finite serial loop structure. The defect mode behavior is analyzed as a function of the defect lengths, the position of the defects, and the ratio between the loops undisturbed. Our theoretical analysis is performed using the continuous medium interface response theory, which makes it possible to calculate the Green function of any composite material.
Signal-to-noise ratio enhanced electrode configurations for magnetoelectric cantilever sensors
Authors: Schmalz Julius , Krantz Matthias C. , Knies Alexander , Lüder Hannes , Gerken Martina
Published: July 2020

Magnetoelectric cantilevers consisting of strain-coupled magnetostrictive and piezoelectric (PE) layers are applicable to magnetic-field sensing. For the first bending mode, the magnetic field-induced stress distribution is of equal sign along the cantilever length. Thus, a plate-capacitor electrode configuration encompassing the complete PE layer may be used for collecting the strain-induced charge. For higher order modes, stress regions of the opposite sign occur in the cantilever length direction. To prevent charge cancellation and to harvest the piezoelectric induced charge efficiently, segmented electrodes are employed. This study investigates the effect of the electrode configuration on the signal-to-noise ratio (SNR) for higher order bending modes. The charges collected by the electrodes are calculated using a finite element method simulation considering the mechanical, electrical, and magnetic properties of the cantilever. By combination with an analytic noise model, taking into account the sensor and amplifier noise sources, the SNR is obtained. We analyze a 3 mm long, 1 mm wide, and 50 μm thick silicon cantilever with layers of 2 μm magnetostrictive soft amorphous metal (FeCoSiB) and 2 μm piezoelectric aluminum nitride. We demonstrate that an SNR-optimized electrode design yields an SNR improvement by 2.3 dB and 2.4 dB for the second and third bending modes compared to a signal optimized design.
Does policy change to allow pharmacist provision of influenza vaccination increase population uptake? A systematic review
Authors: Spinks Jean , Bettington Emilie , Downes Martin , Nissen Lisa , Wheeler Amanda
Published: July 2020

Objective The aims of this study were to estimate the effect of pharmacists’ vaccinating for influenza on overall vaccination rates and to assess whether any effect differs for at-risk subgroups compared with the general population. Methods A systematic review was undertaken, adhering to the Preferred Reporting Items for Systematic reviews and Meta-Analyses (PRISMA) guidelines. Databases were searched during July 2019 and included Medline (Ovid), Cumulative Index to Nursing and Allied Health Literature (CINAHL), Scopus and the Cochrane Library. Results The largest difference reported in overall population vaccination rates associated with pharmacists undertaking influenza vaccinations was an increase of 10%; the smallest showed no discernible effect. The effect was graduated: pharmacists with the most autonomy demonstrated the largest rate increases. There was evidence of substitution by pharmacists, but the effect size was small. Conclusions The effect of allowing pharmacists to administer influenza vaccinations appears positive, but small. Given that pharmacists are likely to provide vaccinations at a lower cost than doctors, there may be cost-savings to the health system and consumers. Future research may include evaluating pharmacist-provided vaccinations compared with (or in combination with) other strategies, such as advertising, to increase access and uptake across the range of providers, as well as ongoing research to address vaccine hesitancy. What is known about the topic? In Australia, and many other countries, community pharmacies provide an alternative and accessible option for influenza vaccination; however the effect on overall vaccination rates remains unclear. What does this paper add? This systematic review of the international literature suggests that pharmacist-provided vaccinations increase uptake; substitution of doctors by pharmacists may result in cost savings. What are the implications for practitioners? The findings of this study are important for health policy makers and health workforce researchers aiming to maximise population vaccination rates and workforce efficiency. In the absence of available Australian data, data from the international experience of legislating pharmacists to vaccinate against influenza are summarised and critiqued. Results can be used when determining the best health workforce and policy mix with regard to the vaccination workforce.
Dietary addition of lysophospholipids and vitamin C affects growth performance, serum metabolites, antioxidant capacity and carcass characteristics of broiler chickens reared under low ambient temperature
Authors: Zangeneh Samira , Torki Mehran , Abdolmohammadi Alireza , Saki Aliasghar
Published: July 2020

Context
Evaluating performance of broilers fed diet included feed additives in stress conditions.

Aims
This study was conducted to investigate the effects of adding lysophospholipids (LPLs) and vitamin C (VC) to diet on growth performance, blood metabolites, antioxidant capacity and carcass traits in broiler chickens reared under low ambient temperature

Methods
A total of 288 male chicks (Ross 308) were allotted to four treatments with six replicates (n = 12) when they were 1-day-old. Based on a 2 × 2 factorial arrangement, four diets including dietary LPLs (0 or 1000 mg/kg) and VC (0 or 500 mg/kg) were formulated. According to the catalogue of LPL product, 100000 kcal/Kg metabolisable energy was considered for LPLs. The house temperature was 32°C during the first week and 30°C for a second week. To induce cold stress, house temperature was decreased to 14°C by the step-down temperature program during the third week and maintained between 12 and 14°C for the rest of the study.

Key results
Increased feed intake and feed conversion ratio (FCR) were observed in chickens fed the LPL-supplemented diet during the first 2 weeks, but there was no significant difference in growth performance between the birds fed LPL-supplemented diet with control during cold stress condition. Decreased feed intake and bodyweight gain were observed in chickens fed VC-supplemented diet compared with control in cold stress condition. Dietary VC decreased blood concentration of triglyceride (TG) and very-low-density lipoprotein (VLDL). Decreased activity of superoxide dismutase (SOD) in breast muscle was observed in chickens fed VC-supplemented diet. A significant interaction between dietary LPLs and VC on relative weight and length of jejunum and ileum were detected. Comparable effects of LPLs and VC on inhibiting lipid peroxidation were observed. The free radical scavenging assay showed higher antioxidant activity of VC compared with LPLs.

Conclusions
Overall, dietary LPL supplementation did not improve broiler performance in cold stress condition, while the utilisation of 500 mg/kg VC in the ration reduced performance of broilers in low ambient temperature.

Implications
In low ambient temperature, adding 500 mg/kg VC to diet of broilers can be an effective to reduce blood concentration of TG and VLDL, with no adverse effect on FCR.
Cargo and cell‐specific differences in extracellular vesicle populations identified by multiplexed immunofluorescent analysis
Authors: Burbidge Kevin , Zwikelmaier Virginia , Cook Ben , Long Michael M. , Balva Barak , Lonigro Michael , Ispas Grace , Rademacher David J. , Campbell Edward M.
Published: July 2020

Extracellular vesicles (EVs) have been implicated in a wide variety of biological activities, have been implicated in the pathogenesis of numerous diseases, and have been proposed to serve as potential biomarkers of disease in human patients and animal models. However, characterization of EV populations is often performed using methods that do not account for the heterogeneity of EV populations and require comparatively large sample sizes to facilitate analysis. Here, we describe an imaging‐based method that allows for the multiplexed characterization of EV populations at the single EV level following centrifugation of EV populations directly onto cover slips, allowing comprehensive analysis of EV populations with relatively small samples. We observe that canonical EV markers are present on subsets of EVs which differ substantially in a producer cell and cargo specific fashion, including differences in EVs containing different HIV‐1 proteins previously reported to be incorporated into pathogenic EVs. We also describe a lectin binding assay to interrogate EVs based on their glycan content, which we observe to change in response to pharmacological modulation of secretory autophagy pathways. These studies collectively reveal that a multiplexed analysis of EV populations using fluorescent microscopy can reveal differences in specific EV populations that may be used to understand the biogenesis of specific EV populations and/or to interrogate small subsets of EVs of interest within larger EV populations in biological samples.
Pluripotent stem cells with low differentiation potential contain incompletely reprogrammed DNA replication
Authors: Paniza Theodore , Deshpande Madhura , Wang Ning , O’Neil Ryan , Zuccaro Michael V. , Smith Morgan Elizabeth , Madireddy Advaitha , James Daylon , Ecker Joseph , Rosenwaks Zev , Egli Dieter , Gerhardt Jeannine
Published: July 2020

Reprogrammed pluripotent stem cells (PSCs) are valuable for research and potentially for cell replacement therapy. However, only a fraction of reprogrammed PSCs are developmentally competent. Genomic stability and accurate DNA synthesis are fundamental for cell development and critical for safety. We analyzed whether defects in DNA replication contribute to genomic instability and the diverse differentiation potentials of reprogrammed PSCs. Using a unique single-molecule approach, we visualized DNA replication in isogenic PSCs generated by different reprogramming approaches, either somatic cell nuclear transfer (NT-hESCs) or with defined factors (iPSCs). In PSCs with lower differentiation potential, DNA replication was incompletely reprogrammed, and genomic instability increased during replicative stress. Reprogramming of DNA replication did not correlate with DNA methylation. Instead, fewer replication origins and a higher frequency of DNA breaks in PSCs with incompletely reprogrammed DNA replication were found. Given the impact of error-free DNA synthesis on the genomic integrity and differentiation proficiency of PSCs, analyzing DNA replication may be a useful quality control tool.
Humility as a Virtue: Oral and Visual Religious Indoctrination to Purify the Female Gender in Italy in the Early Quattrocento
Authors: Stefanacci Davide
Published: July 2020

The Madonna of Humility has been a subject of great interest in the twentieth century. Scholars such as Millard Meiss and H. W. van Os have long dwelled on the origin and dissemination of this emblematic iconography. Nevertheless, scholars have said little regarding its role and possible reverberation on women of the late Middle Ages. The need to domesticate the female gender inspired great orators like Saint Bernardino of Siena (1380–1444), who used humility as a means to control society. Not only could humility, if perceived as a virtue, keep women within their limited social spaces, it would have allowed them—by following a specific fabricated way of life—to spiritually lead their households, gaining the possibility of eternal salvation. This article explores the faith-based concept of humility to unlock the forces that pushed toward the diffusion of a religious iconography, capable of imposing a modest way of life that was more in keeping with the Catholic teachings of the late Trecento and early Quattrocento. Several portrayals of the Madonna of Humility are proposed to investigate the role these paintings might have played in Italy in exalting humility as a noble virtue.
Facing Another: The Attenuation of Contact as Space in Dhofar, Oman
Authors: Russell Kamala
Published: July 2020

This article considers the properly spatial aspects of communicative practices among speakers of Śħerēt, a Modern South Arabian language, living in Dhofar, Oman. I argue that participants in face-to-face interactions (particularly the domestic hospitality that dominates daily activity) move, speak, and position themselves in ways that attenuate interactional contact itself. This drawing out of contact is a site of normative practice across modalities including body posture, gaze, movement, and seating position in participation frameworks. Not simply creating distance or imposing categorical bounds on relationality, these signs attenuate the intensity of contact as the spatial extent of possible or actual encounters with others by complicating the accessibility of participants. As such, I constitute attenuation as an analytic that registers distortions of contact as manipulations of social space in a way that runs alongside (not counter to) other semiotic functions of gradation and categorization. The role of space as the medium of contact with others and its attenuation points to Dhofari concerns about accessibility that locally structure both interactional performance and understandings of sociality as such. This article in turn indicates new ways we can describe the nonneutrality of the spaces of social life.
Enterprise Investment Value Analysis Based on Machine Learning Model of Rapidminer
Authors: Chong Zhang , Xinrui Zhang , Zipei Yang
Published: July 2020

Whether an enterprise has investment value and how to measure the investment value of an enterprise are the primary concerns of every investor. Effective evaluation of enterprises’ investment values can not only help enterprises to recognize their own problems and values and to achieve faster growth, but also help investors to obtain more investment returns. The investment value of enterprises is reflected both in financial data and non-financial data. This paper is based on data mining and analysis of 3500 listed companies to establish a more comprehensive and objective evaluation model of enterprise investment value. Also, after data cleaning, data are trained by machine learning in RapidMiner software to compare the accuracy of several models, thus key factors affecting enterprise investment value are analyzed and investment advice will be given to investors, and enterprises can strengthen their capabilities in concerning areas to enhance their own value to attract more investment.
Breast Cancer Classification using Deep Convolutional Neural Network
Authors: Aslam Muhammad Aqeel , Aslam  , Cui Daxiang
Published: July 2020

Over the last decade, the demand for early diagnosis of breast cancer has resulted in new research avenues. According to the world health organization (WHO), a successful treatment plan can be provided to individuals suffering from breast cancer once the non-communicable disease is diagnosed at an early stage. An early diagnosis of cure disease can reduce mortality all over the world. Computer-Aided Diagnosis (CAD) tools are widely implemented to diagnose and detect different kinds of abnormalities. In the last few years, the use of the CAD system has become common to increase the accuracy in different research areas. The CAD systems have minimum human intervention and producing accurate results. In this study, we proposed a CAD technique for the diagnosis of breast cancer using a Deep Convolutional Neural Network followed by Softmax classifier. The proposed technique was tested on the Wisconsin Breast Cancer Datasets (WBCD). The proposed classifier produced an accuracy of 100% and 99.1% for two different datasets, which indicates effective diagnostic capabilities and promising results. Moreover, we test our proposed architecture with different train-test partitions.
The Design of Improved Neighborhood Rough Set Algorithm and Its Application in Diabetes Prediction Research
Authors: Gao Jing , Cheng Ming , Shen Ruifang , Hu Wei
Published: July 2020

In order to reduce the importance of neighboring rough set only by single attribute, this paper proposes an improved neighborhood rough set attribute reduction algorithm (INRS), which increases the dependence of conditional attributes based on considering the importance of individual features. Relationship, that is, whether it affects the effect of other conditional attributes on decision attributes after deleting the attribute. The importance of a certain attribute to the decision attribute is divided into two parts: direct influence (after the attribute is deleted, the obtained decision attribute depends on the degree of reduction of the conditional attribute) and indirect influence (relative to the influence of other conditional attributes on the role of the decision attribute when there is no such attribute), so that the importance of each attribute can be clearly identified. When the attribute is reduced, the potential attributes are not reduced. In this paper, the data of diabetes in a hospital of the National Population and Health Science Data Sharing Service Platform was collected. The attribute reduction algorithm was used to attribute the diabetes dataset, and the random forest (RF) was used for classification prediction, which formed high precision. The Diabetes Prediction Model aims to provide support for doctors’ clinical diagnosis and disease research to improve the level of clinical diagnosis and treatment.
Robust Beamforming and Power Minimization Design in MISO Health Monitoring System
Authors: Pei Mingjun , Jia Xuemeng , Fu Rong , Jiao Zhanwei
Published: July 2020

In this paper, we study the power splitting (PS) scheme for each user in a multiple-input single-output (MISO) health monitoring system, while considering simultaneous wireless information and power transmission (SWIPT). We construct an optimization problem with robust power minimization constrained by the signal-to-inference-plus-noise ratio (SINR) and energy harvesting (EH). For channel uncertainty, this problem is a non-convexity and is not easy to solve and it can be translated into semidefinite program (SDP) by utilizing S-Procedure. Then the above optimization problem is combined with different channel uncertainty models, and the Bernstein-type inequality and Gaussian error function are introduced to further simplify the optimization problem. Simulation results prove the performance of the proposed robust scheme and point out its effective help for the development of modern telemedicine systems.
Research on Decision-making Method for Allocation of Product Maintenance Spare Parts
Authors: Qian Wu , Chaowei Wang , Fei Pei , Yingcheng Xu , Xiaowei Lu
Published: July 2020

Under the current market situation, improving the efficiency and quality of after-sales service has become one of the effective means for improving the competitiveness of an enterprise. In this paper, the cost coefficient method is introduced into the research on decision-making method for allocation of product maintenance spare parts. By analyzing the factors influencing the transportation of maintenance spare parts, a model is established for the allocation cost coefficient of maintenance spare parts. The optimal transportation route of maintenance spare parts is calculated by using A-star algorithm. The optimal allocation scheme is obtained according to the table-manipulation method on linear programming. The feasibility of the model is verified by an example. The method is scientific, reasonable, simple and easy to learn. With strong generalization and operability, the method can effectively improve the allocation efficiency of maintenance spare parts and save the cost of after-sales service.
Target Tracking Based on Deep Optimization Features
Authors: Yang Tingting , Wei Haiping , Qi Yuanchen , Cui Naixiao
Published: July 2020

Target tracking algorithm based on deep learning generally adopts offline trained deep network to extract features, but with unsatisfactory separation effect of the target and the background. A target tracking algorithm based on deep optimization features is proposed to solve this problem. First, the Conv3-1 and Conv4-3 layers are selected from the offline trained convolutional neural network model VGGNet16 for basic feature extraction. Then the loss function is used to quantitatively describe the effectiveness of different filter positioning target in the basic feature layer. Finally, the selected high-efficiency filters are fused to extract deep optimization features and achieve effective tracking under the correlation filtering framework. The experimental results show that compared with other related algorithms, this algorithm can better recognize the target and present better results.
Study on Consumer Product Supplier Evaluation Method Based on Actor Analysis Thinking
Authors: Heliang Song , Xiaowei Lu , Qian Wu , Yingcheng Xu , Ya Li
Published: July 2020

This paper, based on the existing results of studying supplier evaluation indexes and Actor Analysis Thinking, and by combining the characteristics of consumer product suppliers, first establishes a consumer product supplier evaluation index system covering 10 indexes including product price, product quality, product performance, product series, timeliness of delivery, response capability, collaborative capacity, technical support capability and service attitude; then, refines the traditional Actor Analysis Method, reasonably converts some non-economic factors into economic factors, and improves the scientificity of the non-economic factor evaluation method by using comprehensive weighted average method; and finally proves the feasibility of the method proposed herein with practical application cases. The consumer product supplier evaluation method based on Actor Analysis Thinking proposed herein is scientific, rational, simple and easy to operate, and can provide technical support for enterprises and research institutions to carry out supplier evaluation, supply chain management, etc.
Stochastic Power Flow Calculation of High-Density Correlation Input Power Grid Based on Hybrid Gaussian Model
Authors: Qing Wang , Li Hongxin , Wei Wang , Rong Xue
Published: July 2020

Traditional stochastic power flow calculation assumes that the input variables are uncorrelated and directly used to calculate high-density correlation input variables has certain errors. To this end, this paper proposes a stochastic power flow algorithm based on mixed Gaussian models that takes into account input correlation. First, a mixed Gaussian model is established based on load data, then uniform sampling and Naf transformation are used to process random variables, and the high-density correlation in the original space is converted into independent random variables, and the piecewise linear Monte Carlo method is used to carry out random power flow. Calculation can greatly reduce the calculation time and reduce the truncation error as much as possible. Finally, combined with the actual calculation examples of IEEE-30, the results show that the algorithm can simplify the actual calculation process, improve the calculation efficiency, and has certain practical value in engineering.
Research on New Media Advertising Marketing Strategy in China under the “Internet +” Background
Authors: Wu Qixiang
Published: July 2020

In the context of the “Internet +” era, new media advertising marketing is essentially different from the original advertising marketing. At the same time, there are also some emerging problems, for which corresponding optimization strategies are proposed. According to the analysis results of new media advertising marketing status under the background of “Internet +”, the development prospects of advertising marketing is analysed. The analysis shows that overall environment restricts the new media advertising marketing, the industry system transformation impacts the new media advertising marketing, and its own business model advertising and marketing development have limitations. To address the above problems, the paper put forward corresponding strategies, including promoting the leading position of communicators, optimizing the internal industrial structure of new media, broadening advertising channels, and determining the cultural characteristics of advertising audiences. The proposed strategies can be deployed to optimize the new media marketing methods, enhance the advertising company’s information dissemination capabilities, enhance its economic returns, and promote the development of China’s new media advertising industry.
Evaluation of Energy Consumption in Block-Chains with Proof of Work and Proof of Stake
Authors: Zhang Rong , Chan Wai Kin (Victor)
Published: July 2020

Although there are several special features in block-chain technology such as machine trust, traceability, and security, high energy consumption remains an issue in broadening the applications of block-chain technology. Some researchers proposed the use of proof of stake (PoS) mechanism rather than proof of work (PoW) mechanism to reduce energy consumption of block-chain. However, because PoS cannot guarantee fairness, mixed consensus mechanisms could be a solution and has been adopted in many studies. This paper aims to evaluate the performances of PoW, PoS and mixed consensus mechanisms from three aspects: energy consumption, fairness, and reliability. An agent-based model of a typical block-chain system equipped with different consensus mechanisms is created in NetLogo. This model simulates and evaluates the performances of different consensus mechanisms in the block-chain system.
Reliability Analysis of Distribution Network Operation Based On Short-Term Future Big Data Technology
Authors: Jing Zhe , Yu Cong , Xi Feiruo , Wu Fengzhi , Tao Zhixiang , Yang Peihao
Published: July 2020

This paper firstly establishes a four-dimensional index system for distribution network operation reliability. Using principal component analysis method, it extracts the main evaluation indicators from a large amount of data, and analyzes the influencing factors of the indicators according to the main evaluation indicators. According to the parallel association rules The method establishes the relevant model, and extracts the main indicators of operational reliability and the strong correlation rules between each influencing factors, so as to obtain the main influencing factors. The artificial neural network is proposed to predict, based on historical data and real-time data. The main influencing factors are used as the input and output of the forecast, and the output is expressed by the main evaluation index, and the operational reliability index for a period of time is judged. The calculation of the proposed strategy can quickly and effectively predict the operational reliability of the distribution network.
Research on Interference Test of 24GHz Millimeter Wave Radar to 5G Equipment
Authors: Xu Y , Zhaojun Q
Published: July 2020

The millimeter wave frequency band tends to be developed with the application of radar and communication systems for civil use. It is necessary to analyze the interference coexistence between millimeter wave communication system and radar system. In order to make good use of frequency planning for the millimeter wave frequency band, a microwave anechoic room experiment is tested in this paper. The experiment includes a 24GHz 5G base station, a 24GHz 5G test terminal and a radar to verify the interference of 24GHz millimeter-wave radar to 5G equipment operating at nearby frequencies. This experiment tests and evaluates the detection capability of a single target in the limit state as much as possible and data of base station sensitivity, 5G uplink throughput and 5G downlink throughput have been tested in multiple situations to verify the accuracy and feasibility to this design of radar system. Therefore, the reference and support for 24GHz spectrum allocation can be provided through this method.
Research on the e2e Latency Calculation Considering the Gate Mechanism in Time-Sensitive Networking
Authors: Cao Zhipeng , Liu Qinrang , Liu Dongpei
Published: July 2020

Time-Sensitive Networking (TSN) is an emerging technology that solves the problem of Ethernet deterministic transmission. As its main idea, TSN is compatible with traditional Ethernet Best Effort transmission, while enabling transmission with bounded delay, low jitter, and low packet loss rate for Time-Sensitive traffic. However, existing methods of solving the problem of delay calculation are either too complex or too impractical. This paper proposed a Time-aware calculation method that can calculate the transmission delay in TSN. Firstly, we analyze the 802.1Qbv Time-Aware shaper for specifying its function; Secondly, the network topology, the network traffic, and especially the function of the switch are modeled. We divide the switch into 3 time-windows. Finally, a Time-aware calculation method is proposed, and the transmission cost is calculated considering the frame size, bandwidth, and the percentage of protected window. The experiments show that the method can calculate the end-to-end translation with different senarios and parameters with low complexity.
Modeling and Solution Algorithm for Fourth-Party Logistics Routing Problem Based on Service Composition
Authors: Min Xiaochuan , Meng Fanchao , Chu Dianhui , Wang Lei
Published: July 2020

Aiming at the problems of limited transportation resources and high transportation costs of a single third-party logistics supplier, our research proposes a route planning model based on service combination from the perspective of fourth-party logistics, which aims to find the route with minimum total cost under the premise of meeting customer needs. In order to improve solution efficiency, a specific genetic algorithm is designed. The algorithm adopts backtracking idea and adaptive operations, which can avoid infeasible solution caused by strict constraints, while reducing the time required for crossover and mutation operations to repair infeasible solutions. In addition, Dijkstra-based heuristic algorithm, traditional genetic algorithm and traditional ant colony algorithm are implemented. The comparison of computational experiments on different scales instances shows that the specific genetic algorithm can obtain the optimal solution in small-scale instances, and the solution quality in large-scale problems is better than other algorithms.
Wireless Sensor Networks Congestion Control Algorithm Based on Fusion Judgment
Authors: Xiang Haiyue
Published: July 2020

With the rapid development of sensor network, the network scale is expanding and nodes are deployed in a large amount. The dynamic change of wireless link quality and sudden traffic of sensor network are easy to cause network congestion, packet loss and waste of energy. In this paper, a congestion avoidance control algorithm (FJCA) for wireless sensor networks was proposed based on the fusion judgment method, and factors such as the distance from node to base station, the residual energy of node and the length of cache queue were considered. And compared it with TADR and MDD algorithms, the results show that the algorithm has higher energy efficiency and balance of nodes, which can improve network throughput more effectively, extended the life cycle of wireless sensor networks, and improve the service quality of network.
Development of a High Precision Multi-channel Electric Control Pump Signal Monitoring System
Authors: Bo Wen , Yi Jiangang , Xu Ping
Published: July 2020

The electric control hydraulic pump, which is the core of the hydraulic system, is widely used in modern industry. Therefore, it is necessary to monitor and control the signals of the electric control hydraulic pump in real time to improve the safety of the whole hydraulic system. In order to solve the safety and reliability problems of the operation of the electric control hydraulic pump equipment, a new high-precision multi-channel electric control pump signal monitoring system is proposed in this paper. The signal monitoring system of the electric control pump integrates high-precision power supply, multi-channel signal monitoring instrument and computer monitoring software as one automatic control and measuring device. The developed multi-channel signal monitor is powered by the power supply with good linearity and adjustable range voltage, and the monitor completes the data acquisition and data transmission task of the electric control pump system. The monitoring software on the remote computer processes and analyzes the real-time data of the equipment obtained from the network. The developed system improves the utilization ratio of electric hydraulic pump and has good application value.
Development of Reader Service System for Digital Library
Authors: Xu Chuanjie , Bo Wen
Published: July 2020

Digital library is an extensible knowledge network system based on computer communication and sharing in the network environment. To meet the needs of digital library, a reader oriented reader service system for digital library is developed by using computer technology, communication technology and network technology. The system includes user management, book borrowing and returning, book reservation, book display, book review and other functions. Combined with the push function of mobile phone, the system realizes the purpose of carrying out book borrowing service for readers more efficiently. Through the integration of library service and digital communication, the reader service system of digital library can make readers enjoy digital information resources conveniently and quickly at any time and any place.
MSFA-Net: a Network for Single Image Deraining
Authors: Wu Shun , Zhou Jun
Published: July 2020

Rain streaks degrade the quality of image. Many methods have been proposed to solve single image rain streaks removal recently. However, some methods over-smooth the recovered image. A deep network architecture called Multi-Scale Feature Attention Network (MSFA-Net) is proposed in this paper. We propose a novel basic block structure to exploit the image features, which consists of multi-scale residual learning block and feature attention block. Several basic block structures with a local residual learning compose a group architecture. The outputs of each group architecture are concatenated for final multi-scale feature fusion. Then the features are fed into feature attention block and reconstruction module. Finally, a global residual learning module restore the clean image. Besides, the feature attention block combines channel attention with spatial attention. The proposed MSFA-Net removes the rain streaks which study a non-linear mapping relationship between the rainy and clean image from synthesized dataset. Through comparing with other state-of-the-art algorithms, our algorithm performs better for both synthesized rainy image data and real rainy image data.
Character Design of Somatic Game from Perspective of Intangible Heritage Digital Protection
Authors: Yingfang Zhang , Ding Qiaoying , Shen Dini
Published: July 2020

Due to the development of the times and the progress of society, many traditional cultures are gradually disappearing, and the protection of intangible cultural heritage has become the focus of social attention. With the continuous innovation of science and technology, computer somatic games are also constantly developing. Due to the mode of human-computer interaction, it is suitable for all ages and is loved by the majority of players. This paper takes Lu-style Xinyi Quan as the research object, which is popular among Shanghai, and explores the artistic style, modeling design and three-dimensional model creation of character design based on the digital protection of intangible cultural heritage. Players can watch the action demonstration teaching of characters and imitate learning, while feeling the charm of the Quan, stretch their limbs and experience the fun of fitness and Chinese traditional martial arts indoors, thus promoting the digital protection of intangible cultural heritage.
A Method for Preprocessing State Data of Power Transmission and Transformation Equipment
Authors: Zhou Chao , Qin Jiafeng , Lin Ying , Zheng Wenjie , Bai Demeng , Yi Yang
Published: July 2020

In the era of big data, transportation and inspection data of power transmission and transformation equipment are characterized by diversity and richness. Massive data provide data support for state assessment of power transmission and transformation equipment, but at the same time, higher requirements are put forward for traditional data management and data quality model. How to clean the errors and invalid data in the transportation and inspection data, how to effectively repair the missing data, establish the data quality evaluation model, and improve the quality of the transportation and inspection data of the transmission and transformation equipment are of great significance to the equipment status evaluation.. For the acquired data, this paper carries out preliminary cleaning work on the data, and carries out preliminary cleaning on the data through time series analysis and other technologies to ensure the validity, consistency and integrity of the data.
Target Tracking Algorithm Suitable for Fisheye Camera in Vehicle Environment
Authors: Dong Jinghua , Wei Haiping , Yu Hongfei , Yang Tingting
Published: July 2020

Moving target tracking is one of the core issues in the fields of automobile assisted driving and autonomous driving. This algorithm proposes a target tracking algorithm suitable for fisheye cameras in vehicle environment. A background point removal method based on median ordering is proposed to optimize the optical flow method to solve the problem of target scale change in fisheye camera videos. Multi-scale scaling processing for frames, tracking algorithm based on cyclic matrix structure (CSK), target tracking for multiple images after zooming, using fitting to determine the maximum corresponding value, reducing the error caused by target deformation on tracking results. The tracking test results of multiple fisheye camera videos in the vehicle environment show that the algorithm has high real-time tracking accuracy.
Recognition of the Name of Quality Inspection Institutions Based on CRF and Rules
Authors: Ning Xiuli , Su Xueyan , Peng Bin
Published: July 2020

In recent years, the case of injuries, deaths and property losses caused by product quality and safety issues occurred frequently. The analysis and processing of product quality and safety data can provide data support for government departments in decision-making, which is significant for improving product quality and safety in general. Institution name recognition is an important link in the analysis and processing of quality inspection data. A recognition method which combined CRF and rules for the name of quality inspection institution is put forward in this paper. Firstly, summarizing the rules and features of the name of quality inspection institution by the analysis of the composition characteristics, and then the entity recognition model based on statistics and rules is constructed in combination with CRF. The experimental results show that the method proposed this paper has high accuracy, recall rate and F value for the quality inspection institution names of different scales.
A Two-layer Mechanism Identification Method for VIN Adversarial Examples
Authors: Wang Yingdi , Liu Jiqiang , Chen Tong , Xiang Yingxiao , Tong Endong , Niu Wenjia
Published: July 2020

With the rapid development of machine learning algorithms, the security problems are gradually emerging. Most existing machine learning algorithms may be attacked by adversarial examples. Especially in the domain of path planning, the adversarial maps may result in multiple harmful consequences on the paths predicted by Deep Reinforcement Learning (DRL) algorithms. However, there is no suitable approach to automatically identify them. To our knowledge, all previous work used manual observation method to identify the adversarial maps, which is time-consuming. Therefore, this paper explores a two-layer mechanism method to automatically identify the adversarial examples in Value Iteration Networks (VIN). We define the four categories of attack results and identify them by combining path feature comparison and path image classification. Experiments show that this method can achieve an effective identification on VIN adversarial examples.
Modeling and Optimization of Multiphase Flow in Pump Station
Authors: Sedlář M , Machalka J , Komárek M
Published: July 2020

This paper presents the numerical analysis of flow in the pumping station including the influence of free water level in the suction and discharge objects. The suction object is based on a draft tube. Two solutions of the discharge objects (with the overflow walls and with the welded siphon) are compared so as to optimize the efficiency and start-up of the station. All calculations are based on the ANSYS CFX software with the SAS-SST and the DES scale resolving simulations. The numerical solution of the free-surface flow is carried out by means of the Volume-of-Fluid method. Calculations of flow inside one complete pump station passage provide a good picture of the distribution of water velocities and the corresponding heights of water level in front of the suction draft tube, above the overflow wall crown as well as inside and behind the siphon during the start-up. The calculations are verified with some experiments carried out in the hydraulic laboratory of the Centre of Hydraulic Research. Conclusions show the higher overall efficiency of the station with the siphon-based discharge objects but also indicate some special requirements for the start-up of this station.
Efficient EK-means: Extended K-means Clustering for Categorical data with High Processing Speed
Authors: Xi Chen , Shuo Peng
Published: July 2020

The typical representative of the hard clustering algorithm, K-means, is one of the fastest processing algorithms with good scalability. However, it cannot deal with categorical attributes, which is one of the important indicators to measure the pros and cons. Due to the lack of processing capabilities on categorical attributes, k-means has a large limit on data processing capabilities. This paper proposes a clustering algorithm extends from K-means. This algorithm introduces the concept of a Pseudo-mean distance calculation formula and a counting-table so that categorical attributes can be processed while reducing the time cost as much as possible. Experimental results illustrate the proposed Pseudo-means can extend the processing range of k-means to category-type data, and the counting table also effectively reduces the time cost.
A capacitive electric-field energy harvester with double-layer copper foil for 220V power line
Authors: Yan Dong , Li Jie , Zhang Jiajia , Tian Xingliang , Ou Dexu , Gu Jing
Published: July 2020

The output power of electric-field energy harvesting is limited by displacement current produced in the capacitive coupling between the harvester and power line. This paper presents a capacitive electric-field energy harvester (CEFEH) that obtains energy from 220V power line by displacement current. The CEFEH consists of copper foil wound around the power line and ground electrode. In order to improve the output power of CEFEH, a double-layer copper foil is used to enhance the capacitive coupling, thereby increasing the displacement current. With the help of larger displacement current, the harvesting power of CEFEH with double-layer copper foil is 1.6 times higher than that of the single-layer copper foil. However, the electric-field energy around the 220V power line is very weak, which makes wireless sensor node unable to work directly. A power management circuit is designed for CEFEH. The test results show that the proposed CEFEH collects 2.468mJ in 400s and drives the ultra-low power wireless temperature sensor node to operation for 800ms. This CEFEH can be used in wireless sensor node with a short-term ultra-low power.
Analysis on the impact characteristics of grounding device considering spark effect
Authors: Li Hengzhen , He Zilan , Chen Sixiang , Zhang Ming , Shu Yingjun , Hu Chen
Published: July 2020

Under the effect of lightning current which is with large amplitude, the grounding device and surrounding soil will have spark effect, which makes device show complex impact characteristics and affect the current dissipation process. In this paper, using the parallel plate device, the quantitative relationship between the resistivity of sandy and brown yellow soil and the field strength is obtained, which is expressed as a piecewise function. Considering this relationship, a finite element model of impact dissipation for grounding device is established. A test platform is built, and the impact test data of different topological forms is used to compare with the results of the model, which can verify that the model can effectively analyse the spark effect of the grounding body. After carrying out simulation for the grounding body of different topological forms, this paper analyses the impact dissipation characteristics of the horizontal grounding body and the grounding body with short conductors.
Improved Reactive Power Control of Voltage Fluctuation Caused by Photovoltaic Concentrated Integration
Authors: Liu Guang , Luo Zhongyou , Hou Bing , Wang Yue , Cai Yongjun
Published: July 2020

In the past few years, the number of large-scale photovoltaic (PV) power station is increasing quickly. Due to the power fluctuation of PV station, the voltage in the power grid with large-scale PV stations integrated may fluctuate irregularly. It may cause transformer tap or shunt capacitor switching frequently. To smooth the voltage fluctuation, a typical solution is to install energy storage system which needs high investment. The alternative way is to use reactive power to regulate the voltage. This paper introduces the ability of reactive power control to mitigate the above voltage fluctuation problem. An improved ΔQ(ΔP) control is proposed. Comparing with the common Q(U) droop control, the results of an actual PV station case verifies its good performance.
Trench based structure to modulate the stress induced by silicide metallized electrodes in semiconductor device
Authors: Wen Houdong , Luo Qian , Meng Siyuan , Jiang Xuanqing
Published: July 2020

Though the silicide metallized electrodes which are widely used in semiconductor devices have their advantage of low contact resistance, they often induce harmful stress in devices. Considering this, a trench-based structure designed to manipulate the silicide induced stress is reported in this letter. The effects of the structure are demonstrated by the numerical simulation results based on the typical PMOSFETs with their electrodes formed by CoSi2 and NiSi. It is shown that, while the trench-based structure is applied, the harmful tensile channel stress caused by the silicide electrode can be reduced as low as about 50%. As a result, the output current can be increased about 7.5%. These results indicate the potential of this novel trench based structure to serve as the stress modulation structure in the semiconductor device with silicide electrodes.