bluuebunny/crossref_metadata_2025_split huggingface dataset:
Research on optimal selection of services and optimal allocation of resources in cloud manufacturing environment
Authors: Cai Xianxian , Yuan Minghai , Zhou Zhuo , Sun Chao 
Published: November 2019

Abstract
As a new manufacturing mode in recent years, cloud manufacturing has provided a new method for manufacturing industry from low efficiency to efficient utilization of resources, based on the concept of “manufacturing as a service”. Cloud manufacturing is the product of the integration of high-tech, as information technology, Internet of things and big data. To promote global manufacturing to a healthy, green direction, cloud manufacturing technology converges massive service resources, centralizes utilization, reasonably allocates, and realizes high-level utilization and real-time sharing of manufacturing resources. However, due to the large number, wide scope and complexity of cloud manufacturing resources, and the uncertainty and diversity of cloud manufacturing users, how to achieve optimal deployment of cloud manufacturing resources, it is an urgent problem to meet the different individual needs of users and to improve the efficient sharing of manufacturing resources. Therefore, this paper studies cloud manufacturing service optimization, cloud manufacturing service comprehensive evaluation system and resource optimal allocation, and uses the relevant software tools to design the system function modules and establish a cloud manufacturing service platform system.
Analysis and Prediction of Satisfaction Index of Online Learning
Authors: Wang Jian , Chai Yanmei , Zhang Wei , Zhang Yuanyuan 
Published: November 2019

Abstract
In the process of learning with the help of online platform, students’ learning satisfaction is an important factor that constitutes the effect of online teaching. On the basis of the existing research, this study proposes three factors, namely, cognitive level, technological environment and social environment, to constitute online learning satisfaction. At the same time, through statistical analysis, the key factors affecting learning satisfaction are sorted out, the selection model of identifying the key factors affecting learning satisfaction is established, and online learning satisfaction is fitted by prediction. The study shows that self-efficacy evaluation, teaching support evaluation, platform use evaluation and student-teacher interaction evaluation have a great impact on students’ learning satisfaction in the process of online learning. At the same time, the 93% prediction accuracy of the prediction model based on the above-mentioned research can be achieved. In addition, this paper also puts forward suggestions on how to strengthen and improve learning satisfaction.
An Embedded Visualization Method through Temporal Bibliographic Analysis
Authors: Wang Yan , Sun Mingyu , Hu Ning , Liu Sentao , Si Juncheng 
Published: November 2019

Abstract
Visual analytics play an important role in understanding complex datasets, e.g. the bibliographic data set. Word clouds, which use a compact visual description of words, have been leveraged widely to provide the content overview of a set of documents, especially the hot topic trends. In this paper, we proposed a visualization method that embedding the temporal patterns along the word to visually illustrate the hot topic evolution.
An Extended PEGASIS Protocol Based on Group Authentication with Merkle Tree in WSNs
Authors: Fang Wangsheng , Wang Xiangyu , Xu Haomin 
Published: November 2019

Abstract
With the constant improvement of Wireless Sensor Network, its application scenarios become more diverse. Due to the limited resources of sensor nodes, there are many researches devoted to the optimization of network structure and the prolongation of network life. The proposed extended protocol is based on the chain-based routing technique of PEGASIS. In a newly deployed network, intra-group trust is formed through the Group Authentication based on Merkle Tree, which can protect the node information and resist the deception of false message. In the steady phase, the whole network re-chain is replaced by re-chain within the group when any node dies. Simulation results show that the scheme proposed in this paper has obvious improvement in terms of residual energy and network life compared with PEGASIS.
Design of Campus Bicycle Rental Management System Based on SSM Framework
Authors: Ping Wanxin , Chen Yuankun , Hou Xiaoyan 
Published: November 2019

Abstract
In view of the chaotic management of bicycle rental in colleges and the high waste rate of resources, the purpose of this paper is designing a bicycle rental management system to make it easier and more efficient for students and leasing businesses to complete bicycle rental. According to the elaboration of the system framework, the design and implementation process of the database, the design concept and use principles of the system are introduced in detail.
A Memory Acquisition Method for Android Application Forensics
Authors: Liu Bin , Chang Ying-xian , Cong Lian-ri , Wu Xia , Deng Hua , Li Yang-chun , Xu Bo-wen 
Published: November 2019

Abstract
With the rapid development of social economy, the number of Android mobile devices has increased rapidly in recent years. At present, digital forensics experts mainly extract digital evidence from non-volatile physical memory and file system of mobile devices. However, non-volatile storage based method has little effect for some high secure Apps forensics, such as the encrypted data or deleted information, e.g. the private conversation records or payment records, in chat Apps or payment Apps. Accordingly, data residential in memory is an important source of evidence. On the other hand, relying solely on digital evidence in non-volatile storage is incomplete and unreliable as well. So, the demand for memory forensic on the Android platform has increased. In this paper, based on ptrace a scheme for Android memory extraction at the process level is proposed. For this scheme, a complete memory mirror of a specific process can be achieved, including memory space shared anonymously by the process and other processes, the memory space of the process, and the memory space of each thread in process. This method is of great importance to high secure Apps forensics, such as Chat Apps or Bitcoin Payment Apps.
Emotion recognition method of Tibetan micro-blog text based on sentiment dictionary
Authors: Sun Benwang , Tian Fang , Jia Mengmeng 
Published: November 2019

Abstract
With the development of network technology, social media represented by micro-blog has become an important platform for personal emotional expression. Automatic analysis of micro-blog texts and identification of their emotions is important for understanding people’s emotions. In this paper, the emotion of Tibetan micro-blog text is analyzed automatically for the first time, the emotion in text expression is recognized, the analysis method based on Tibetan sentiment dictionary and rules is put forward, and the language characteristics of emotion expression in Tibetan micro-blog are discussed. The experimental results show that the accuracy of emotion recognition based on Tibetan sentiment dictionary reaches 78.6%, which provides a basis for establishing a high-precision Tibetan textual sentiment classification system.
Attention Mechanism in Machine Translation
Authors: Jia Yuening 
Published: November 2019

Abstract
Machine translation is an important field in machine learning. In recent years, the way to improve the effect of machine translation through attention mechanism has been well introduced and developed, and has become an important research part in machine translation. However, how to use the attention mechanism to ensure the translation speed and accuracy at the same time has also become an important problem for researchers to solve. In this article, we will introduce the development process of attention mechanism in the field of machine translation, and introduce in detail the algorithm changes of four papers on the development of Attention in Machine translation. Through the analysis of their experimental data, the development level of attention mechanism in the field of machine translation is shown.
Text security segmentation algorithm based on key distribution
Authors: Zhang Quan , Ju Xiaoming , Qi Haojin , Wang Yong 
Published: November 2019

Abstract
The vector space projection theory of key decomposition problem is proposed. The key decomposition algorithm is given, and the theory and algorithm are introduced into the research of text segmentation problem. A text security recovery for practical secrecy is given. The algorithm is compared with the traditional text segmentation algorithm. It realizes that the text is first divided into N paragraphs, and then the paragraph is mapped to n sub-texts by using the principle of grouping key. If any m sub-texts are owned, the original text can be restored, which provides security for the storage and transmission of important texts.
Research on Fast Image Style Transformation Based on Residual Network
Authors: Xue Nan , Duan Jin , Zhang Bing , Wang Xiaoyu , Yu Lintao 
Published: November 2019

Abstract
Image style migration technology refers to the conversion of an image into a similar image to a famous painting style through learning (using a convolutional neural network). The A Neural Algorithm of Artistic Style (NAAS) proposed by Gatys uses the VGG network to design a loss network, and the style migration image is obtained through repeated iterations, and the calculation speed is slow. Li Feifei introduced the residual network on the basis of Gatys, and accelerated the calculation by using the fast connection feature of the residual element. This method has a great improvement in the generation speed but still has room for improvement. This paper proposes improvements for the following two aspects: firstly, the classical residual element structure is adjusted, and the standard convolution is converted into point convolution and deep convolution, which reduces the calculation amount while ensuring the convolution effect; secondly, the loss network is simplified. The fourth and fifth layers in the model are highly consistent in structure, and the style restoration of the two layers is basically the same as the content reconstruction effect. Therefore, the fifth layer is deleted, the redundant parameters are removed, and the parameter amount is reduced. At the same time, the effect of style restoration and content reconstruction is guaranteed.
Sparse MIMO planar array two-dimensional imaging based on IF-MMV-SBL algorithm
Authors: Chen Qiao , Tong Ningning , Li Xiaohua , Hu Xiaowei , Dong Yibei 
Published: November 2019

Abstract
MIMO sparse array can achieve two-dimensional imaging of the target based on sparse recovery algorithm, but traditional 1D-CS algorithm will lead to the problem of cell migration, which will affect the imaging quality and it’s operation time is long. In order to solve the problem, the joint sparsity of signal received by MIMO is utilized and the IF-MMV sparse bayesian learning algorithm is introduced to reconstruct the signal in fractal dimension, which can inhibit the migration of cell causing by traditional 1D-CS algorithm. By the inverse free processing, the inverse operation of matrix is transformed into the inverse of diagonal matrix, and the inverse can be obtained quickly. Simulation results show that the proposed method has good applicability under different array sparsity and SNR. We get the high resolution image of the target, and cost less operation time.
Risk Screening of Tax Compliance of Manufacturing Listed Companies Based on Association Rules
Authors: Ying Qu , Lanlan Gao , Xiaoxin Han 
Published: November 2019

Abstract
With the increasing variety of taxes and corresponding tax laws and regulations, the complexity of tax collection and management is increasing, and listed manufacturing companies are one of the important sources of tax revenue in China. Therefore, it is of great significance to construct a scientific and effective tax risk identification and assessment system. In order to improve tax compliance under the premise of complex tax work, this paper proposes a method of tax compliance risk screening for listed manufacturing companies based on association rules. The financial index data of listed manufacturing companies that are crawled are processed, and the Apriori association rule analysis is used to realize the analysis and mining that have an impact on corporate tax compliance. By dividing the tax compliance risk levels of enterprises, it is concluded that the common characteristics of enterprises with low tax compliance are weak profitability, poor debt paying ability, and a large number of overdue repayment.
Research on An Ensemble Anomaly Detection Algorithm
Authors: Wang Yupeng , Zhu Shibing , Li Changqing 
Published: November 2019

Abstract
Aiming at the problem that the applicability of single anomaly detection algorithm is not strong in aerospace experiment, an ensemble anomaly detection algorithm is proposed. This algorithm combines multiple machine algorithms and can obtain better detection performance than any other algorithm. Through comparison, k-NN, PCA and HBOS are selected. These three algorithms have fast calculation speed and different algorithm mechanisms, which can effectively process various data sets. This paper first introduces the basic concept of anomaly detection, then introduces and explains the three algorithms, then integrates the three algorithms, and introduces the voting mechanism to vote on whether the sample points are normal. Finally, the performance of the algorithm is tested through simulation experiments. Compared with a single algorithm, the ensemble algorithm has better performance in precision and accuracy.
The Database and Functional Structure Design of the Breeder Pigeon `s MIS for Optimization in Selecting and Matching Based on RFID Technology
Authors: Chen Siyu , Wu Xiumin 
Published: November 2019

Abstract
In order to improve the production and breeding efficiency of pigeon breeding farms, and at the same time to ensure the quality of pigeons, pigeon breeding farms should be managed scientifically. In the process of breeding, breeder pigeon optimization has become an important part of pigeon breeding production, which directly affects the quantity and quality of offspring pigeons. At the same time, this is also a pigeon management of the most important information subsystem. This paper hopes to develop a set of modern information management system for the optimal breeding of breeder pigeons, and build the breeder pigeon breeding management information system by combining the special RFID tags for breeder pigeons, computer network and database technology, so as to realize the effective traceability and sharing of all aspects of data of breeder pigeons. It is expected to establish corresponding mobile terminal software to realize data access and query anytime and anywhere, which can make the information management method of pigeon breeding yard more scientific and standardized, so as to achieve better economic and social benefits. Its technical achievements can also be applied to poultry farms and other breeding enterprises.
A Time-Context-Dependent Resource Diffusion Algorithm Based on User Splitting
Authors: Fan Hao , Yu Xiao-yan , Shu De-qin , Cao Hongbin 
Published: November 2019

Abstract
Personalized recommendation for smartphone applications is studied, and a time-context-dependent resource diffusion algorithm based on user splitting is proposed. The algorithm introduces time context information. According to this idea, the algorithm can make full use of user preference data information, cluster mobile applications to get more user preference categories and optimize recommendation results. In the personalized recommendation process of mobile applications, because users and projects are dynamic changes, this paper analyses the dynamic change process of the algorithm in detail, and enhances the applicability of the algorithm. Experimental results show that the proposed algorithm improves the accuracy of recommendation results compared with the previous resource diffusion algorithm.
A Comparative Analysis of the Application of Hashing Encryption Algorithms for MD5, SHA-1, and SHA-512
Authors: Long Sihan 
Published: November 2019

Abstract
This study compares different hashing encryption algorithms and provides several suggestions about how to choose different hashing encryption algorithms for particular cases. This paper presents three different kinds of hashing encryption algorithms. The author introduces the fundamental conceptions of these algorithms and their application. The author also computes some significant factors in computer science and compares these algorithms by mathematical quantity computing data. This article discusses the advantages and disadvantages of hashing encryption algorithms and proposes its potential value in the future.
Research on Latency Problems and Solutions in Cloud Game
Authors: Sun Hanlin 
Published: November 2019

Abstract
In recent years, the concept of cloud game remains a hot spot in both academic and game industry, proved by a large number of related research papers and the emergence of various cloud gaming platforms. Cloud game has competitive advantages over other traditional games. However, cloud games are more susceptible to latency than traditional online games because the data of cloud games are processed in remote servers. This paper shows the researches and progress in cloud gaming, analyzes the main aspects that may influence cloud gaming latency and proposes feasible methods to improve these problems.
Research on Water Quality Monitoring Technology of Industrial Park Based on Internet of Things and Cloud Computing
Authors: Shi Wei , Wang Yang , Tang Hui , Liu Haishan , Tang Dunbing 
Published: November 2019

Abstract
Aiming at the problems of high cost, slow response and unstable data in industrial wastewater quality monitoring in industrial parks, this paper proposes a water quality monitoring system for industrial parks based on Internet of Things and cloud computing technology by studying data acquisition technology of water quality sensors, wireless networking technology of water quality acquisition equipment, connection technology between equipment and cloud computing platform, and end of data model interface. The monitoring technology is also applied in the water quality monitoring system of an industrial park in Hebei Province, China. The data response is timely and the pollution alarm is accurate, which improves the level of water pollution control.
The effect of open-air curing on compressive strength of geopolymer mortar containing laterite soil and slaked lime
Authors: Sayfullah S M , Suherman L O A , Salam S , Mursanto D , Idwan  , Efendi A , Bahar S B , Farisatma  , Kanna T 
Published: November 2019

Abstract
Most surface layers in the Papua and Kalimantan regions are Laterite Land. When dry lateritic soil dries but when containing large amounts of water, laterite soil becomes overtime. Cement production requires a lot of energy so that geopolymer concrete and mortar is a material that has great potential as an alternative to reduce the use of Portland cement because it has mechanical properties that almost resemble Portland cement-based concrete. This study discusses the use of fly ash and alkali activator (NaOH and Na2SiO3) to bind laterite soil by adding quenched lime to reduce the use of ovens to form geopolymer mortar. Comparison of laterite and lime outages is used, namely 95%: 5% and 90%: 10%. Testing of the flow of fresh geopolymer mortar shows that all materials can be bonded well and no segregation occurs. The hardened test material is treated in air-exposed for 3, 7 and 28 days. Testing of compressive strength was analyzed to determine the behavior of geopolymer mortar. The test results showed that there was an increase in compressive strength from the age of 3 to 7 days but decreased at the age of 28 days due to rainy weather, sunlight which resulted in the specimen experiencing flowers (during rain) and shrinkage (during hot weather) so that cracks occurred cracks in specimens, as well as the use of comparison of laterite and lime soils, extinguished 90%: 10% resulting in better compressive strength compared to the use of the ratio of laterite and lime outages of 95%: 5%.
The role of schools in building student awareness of environment through adiwiyata program
Authors: Ali A M , Akbar A , Kamarudin  , Manan  , Safiuddin  , Noer E 
Published: November 2019

Abstract
This research was conducted in the Southeast Sulawesi region which was based on the importance of ecoliteration for elementary school-age children. The effort made by the government to raise awareness of ecoliteration is the Adiwiyata program. The purpose of this study was to determine the role of Adiwiyata in building environmental awareness in the Southeast Sulawesi region. The method used is a survey by taking a sample of 13 elementary schools. Data analysis used is a descriptive analysis of the four components of observation. The results of the study showed two schools from 14 elementary schools that implemented the Adiwiyata program as a whole. School as better applies the four components of Adiwiyata, the better the students in realizing the importance of protecting the environment.
Economic value analysis of the use of springs for household consumption needs
Authors: Abdullah R , Mahmuda D , Malik E , Pratiwi E T , Azaluddin  , Dja’wa A , Abdullah L O D , Jusni  , Betaubun K 
Published: November 2019

Abstract
Water is a natural resource that is very important for human survival. Not only does it provide biological benefits, but water also affects social, economic, cultural, political and national security aspects. The excessive use of water resources management that is not wise can threaten the sustainability of water sources. This study aims to estimate the economic value of the use of springs in Popalia Village, Wakatobi, Indonesia. Types of data are primary data obtained from the water user community, and secondary data obtained from the Popalia Village office. The method used is the Willingness To Pay (WTP) approach with the Contingent Valuation Method (CVM) analysis method. The results showed that the average value of Willingness To Pay (WTP) was IDR 5,969.32 per month and the total value of Willingness To Pay (WTP) is IDR 1,724,961.54 per month. The economic value of springs in Popalia Village in one year is IDR 37,584,482.28.- The government is expected to be able to apply payment for environmental services to water use and design water source management so that it can be sustainable and sustainable.
Corporate legal responsibility against environmental damage
Authors: Salam S , Parawansa S S R , Mursanto D , Karim L M , Ernawati L , Gurusi  , Rahail E B , Raf Nuvida 
Published: November 2019

Abstract
The purpose of this study was to determine the form of legal responsibility due to the environmental damage done by corporations in the mining industry. This research uses normative legal research typology, especially those relating to the enforcement of corporate criminal sanctions in the fields of mineral and coal mining. The results of the research obtained are forms of penalties in the form of criminal sanctions for corporate actors who carry out environmental damage due to mining where law enforcers must provide strict sanctions to the perpetrators of destruction where the sanctions are strict liability, for the perpetrators of environmental destruction, who can create the legal entity has been dropped in the form of a criminal fine with a spread plus 1/3 of the provisions of the maximum criminal penalty imposed.