bluuebunny/crossref_metadata_2025_split huggingface dataset:
Assessment of the thermoelectric conversion potential of low-temperature waste heat from textile dry-cleaning processes
Authors: Fiaschi Daniele , Talluri Lorenzo 
Published: August 2019

Even though textile industry is not considered an energy intensive sector, it comprises a large number of plants consuming and wasting a significant amount of energy that could be, at least partially, conveniently recovered. The objective of this work is to assess the possibilities and convenience of energy recovery from waste heat of different processes of a dry industrial textile laundry.
The various thermal wastes from the processes were identified and characterised, in order to estimate their potential recovery and conversion into electricity.
A suitable system layout was conceived, in order to exploit the heat deriving from thermal waste of different machinery in the factory, having distinct temperature levels, to an ORC powerplant, which converts the recovered heat into electricity.
The ORC cycle was optimized to maximize the thermoelectric efficiency, comparing different possible working fluids. The best fluid was RC318, from which 92.5 kW power output was achieved, at 9.2% efficiency.
The economic analysis revealed, conservatively, a payback period of 7 years for the whole system, which is potentially very interesting. The amount of electricity produced by the waste heat recovery equipment is well matched to the company's electrical needs, resulting in a significant reduction of electricity consumption, greatly reducing the electrical withdrawal from the grid and the related costs.
The case study, the proposed solutions and the methodology have general aspects and may be extended to a wide range of cases in the sector of industrial textile laundry.
Die Senkniere
Authors: Corts Magga 
Published: August 2019

SummaryDie Niere kann aus verschiedenen Gründen absinken. Zum Beispiel bei starkem Gewichtsverlust, weil sich das Fettgleitlager der Niere zu stark reduziert. Dann können in der Nähe liegende Nerven irritiert werden, was wiederum zu nervenspezifischen Symptomen führen kann.
Im Klartext: Der Hygieneplan
Authors: Handke Denis 
Published: August 2019

SummaryMit dem Tag der Praxiseröffnung muss der Betreiber einen Hygieneplan erstellen, der alle innerbetrieblichen Maßnahmen der Infektionshygiene regelt. Als wichtigste rechtliche Grundlagen dienen das Infektionsschutzgesetz, die KRINKO-Empfehlungen des Robert Koch-Instituts, die Hygieneverordnungen der Länder und die TRBA 250. Der Hygieneplan umfasst unter anderem die Risikoanalyse und Gefährdungsbeurteilung, Patienten- und Personalhygiene, Ver- und Entsorgung, Qualitätsmanagement sowie den Umgang mit Arzneimitteln und Medizinprodukten.
Influence of the excitation frequency on the RF power transfer efficiency of low pressure hydrogen ICPs
Authors: Rauner D , Briefi S , Fantz U 
Published: August 2019

Abstract
The influence of the excitation frequency on the RF power transfer of inductively heated hydrogen plasmas is investigated in the pressure range between 0.3 and 10 Pa. The experiments are conducted at a cylindrical ICP at frequencies in the range between 1 and 4 MHz and RF powers up to 1 kW. By applying a subtractive method which quantifies the transmission losses within the plasma coil and the RF network, the RF power transfer efficiency is determined. The key plasma parameters of the discharges are measured via optical emission spectroscopy and a double probe. By increasing the frequency from 1 to 4 MHz at a moderate RF power of 520 W, a significant enhancement of the RF power transfer efficiency is observed. It is most prominent at the presently considered low and high pressure limits and allows to reach high efficiencies of up to 95% at pressures between 3 and 5 Pa. While the AC loss resistance of the coil and the RF circuit only displays a relatively weak variation with the applied frequency due to the skin effect, the observed increase of the power transfer efficiency at higher frequencies is dominated by a considerable enhancement of the plasma equivalent resistance. This increased capability of the plasma to absorb the provided power is discussed against the background of collisional and collisionless heating of electrons. Thereby it is demonstrated that the observed behaviour can most likely be attributed to a decreasing difference between the angular excitation frequency and the effective electron collision frequencies. If the RF power is increased however, the RF power transfer efficiency increases globally while frequency induced differences tend to get less pronounced, as the plasma is generally capable of absorbing most of the provided power due to an increasing electron density.
A Feature Selection Method based on the Pearson’s Correlation and Transformed Divergence Analysis
Authors: Zhang Ying , Wang Lin , Geng Danyang , Ai Yunfei , Xia Wei , Bai Xuejiao , Sun Shikai 
Published: August 2019

Abstract
An improved feature selection method has been presented, which is based on Transformed Divergence (TD) considering weights of classes and Pearson’s correlation analysis. Using the improved method, this study evaluated several derived vegetation indices and texture measures based on Landsat-8 OLI data to determine their effect on improving the land cover classification separability in Jiangle county, Sanming city of Fujian province, China. The best vegetation indices combination was selected by the improved feature selection method and likewise, best textural combinations at different spatial resolution levels from multi-spectral bands or panchromatic band were obtained. The improved feature selection method found that a single feature could not maximize the separability of vegetation classes. When selecting four vegetation indices, the separability of vegetation classes can be maxmized significantly; and two textural measures were suitable for maxmizing the separability of vegetation classes. Overall, the result verifies that the feature selection method considering weights of classes and Pearson’s correlation coefficient can select optimal features to maximize class separability.
Analysis of Vegetable Price Fluctuation Law and Causes based on Lasso Regression Model
Authors: Yu Weige , Zhao Chunjiang , Wu Huarui , Peng Cheng 
Published: August 2019

Abstract
In recent years, the sharp price fluctuation of vegetables has attracted wide attention. In order to explore the causes of price fluctuation, the price fluctuation law of cucumber from 2010 to 2017 was deeply explored based on the empirical analysis of the price fluctuation law of vegetables. Most of the existing literatures use linear regression models to analyze the influence degree of various factors, but there are problems of multicollinearity among multiple variables and small influence degree of some variables, which affect the fitting accuracy. Lasso regression model is introduced to model and solve cucumber price data, and the influencing factors of price with smaller correlation are eliminated to obtain the main factors and their correlation. Compared with the least square method, the multicollinearity determination condition value is only 19.66 and the fitting coefficient reaches 0.8448, which proves that lasso regression model is suitable for vegetable price cause analysis and has better performance than traditional methods. It also provides basis for further vegetable price prediction.
Artificial Neural Networks for Urban Water Demand Forecasting: A Case Study
Authors: Lorente-Leyva Leandro L , Pavón-Valencia Jairo F , Montero-Santos Yakcleem , Herrera-Granda Israel D , Herrera-Granda Erick P , Peluffo-Ordóñez Diego H 
Published: August 2019

Abstract
This paper presents an application of an artificial neural network model in forecasting urban water demand using MATLAB software. Considering that in any planning process, the demand forecast plays a fundamental role, being one of the premises to organize and control a set of activities or processes. The versatility of the short, medium and long-term prediction that is provided to the company that offers the water distribution service to determine the supply capacity, maintenance activities, and system improvements as a strategic planning tool. Shown to improve network performance by using time series water demand data, the model can provide excellent fit and forecast without relying on the explicit inclusion of climatic factors and number of consumers. The excellent accuracy of the model indicates the effectiveness of forecasting over different time horizons. Finally, the results obtained from the Artificial Neural Network are compared with traditional statistical models.
Using Shopping and Time Attitudes to Cluster Food Shoppers: An Empirical Finding from Indonesia
Authors: Utami A A , Ginanjar A R , Fadlia N , Lubis I A , Ulkhaq M M 
Published: August 2019

Abstract
Retail market is claimed to be an important interface in channel management as it bridges the manufacturers and consumers. In Indonesia, retail industry has increased significantly. One of the main characteristics of this market is its heterogeneity. This heterogenous market could be segmented into different segments of consumers which have different characteristics, behaviours, and needs. This requires retail market to set proper marketing strategies by analyzing each segment. This research attempted to conduct market segmentation for food shoppers in Indonesia based on attitudes to shopping and time. Four clusters have been constructed, namely, apathetic but regular, convenience seekers, hedonist, and time-pressured convenience seekers. The ANOVA test confirmed that those four clusters were appropriate as it created more differentiated and consistent clusters. This research could give contributions to the theoretical perspective and empirical point of view on market segmentation where different marketing strategies could be generated for each segment.
Technology and Application for Substation Automatic Inspection Based on “Robot +” Mode
Authors: Bincai Zhao , Feifei Wang , Fucheng Han 
Published: August 2019

Abstract
Daily substation equipment inspection is important for safety production of the power grid. To improve the safety and reliability of the traditional substation instrument inspection mode, this paper aims on the technology and application for substation automatic inspection based on “robot +" mode. Upon the foundation of substation inspect robot, we expand the cover range and types of monitoring devices. We first introduce the system architecture and inspect data type of the proposed “robot+” mode, and then show the data access architecture of all the monitoring devices related to the system. The processing strategies for two typical kinds of structured and unstructured data which are not from the robot are explained. For structured data, we adopt the ARIMA model to predict the time series data. Meanwhile for unstructured data, we take advantage the concept of sparse representation to recover the deformation of the monitoring object. With the newly automatic inspection mode, we can achieve an all-round three-dimensional inspection of substation equipment and environment, which can improve the coverage, the quality and efficiency of substation operation and maintenance. Through the work of this paper, we can reduce the working pressure of team members and enhance the condition control and operation inspection management penetration of substation equipment.
Research on Simulation Decision of Logistics in Flexible Factory
Authors: Wentao Luo , Yan Ren , Jianfu Zhang , Linjiang Du 
Published: August 2019

Abstract
Aiming at problems that the flexible scheduling capability of the production line in the existing factory is poor due to islanding effect and existing scheduling methods ignore non-cutting time and dynamic change of time when solve the minimum completion time, this paper studies the optimization of multi-variety and small batch workflow scheduling, and establishes an optimal job flow allocation model based on dynamic time parameters. Taking a flexible flow shop as an example, the model is applied to the implementation, and the EM-PLANT simulation software is used to make digital decision to realize the scientific scheduling of workpiece flow in cyber environment of production line. The simulation results show that the optimal allocation model can reduce the average completion time of workflow and improve production line efficiency.
Armature Optimization Design Based on Orthogonal Test
Authors: Rong Chen Qing , Shu Tao , Liu Ming , Yang Cui Meng 
Published: August 2019

Abstract
Armature is the core component of electromagnetic launcher. It not only plays the role of constituting current loop, but also provides launching power for projectile. Therefore, armature optimization is a key step to improve the comprehensive performance of six-pole orbital electromagnetic launcher. In this paper, the finite element simulation software Ansoft Maxwell is used to simulate and analyze the armature, and the influence of the main size of armature on the maximum current density and electromagnetic thrust of armature are obtained. At the same time, the optimal design of armature size is carried out by using matrix analysis method in orthogonal experiment. Finally, the optimized armature is verified by simulation. The results show that the optimized armature has the smallest maximum current density and the largest electromagnetic thrust in all size combinations.
An Improved RANSAC Surface Reconstruction Study
Authors: Li Ma , Jinming Zhang , Dongchao Ma , Yingxun Fu 
Published: August 2019

Abstract
Surface reconstruction technology has always been an important research area in graphic image. However, efficiently processing massive amounts of high-precision point cloud data is still a problem worth studying. Based on the characteristics of point cloud data and the existing research results, this paper proposes a RANSAC algorithm based on voxel segmentation and applies it to 3D surface reconstruction. By analyzing the characteristics of the original point cloud data, the method improves the reconstruction speed of the 3D model while retaining a large amount of effective feature information and ensuring high precision. The experimental results show that compared with the reconstruction algorithm based on the original RANSAC algorithm, the proposed algorithm can effectively reduce the surface reconstruction time of 47.51%, and the model error after processing is only one thousandth compared with the original model.
Virtual Simulation of Automatic Quality Measurement System for Tapered Roller Bearing Based on 3D Automate Software
Authors: Khlil Alhadi , Ma B , Shi Z 
Published: August 2019

Abstract
In present years, the simulation technique has been extensively used in manufacturing processes, solving complex problems with least time, effort and cost. This paper presented a virtual simulation of automatic quality measurement system for tapered roller bearing to aid the decision-making processes, observe system operation processes and provide an initial design for constructing processes using 3D modeling process and Python programming language, the proposed system was intended to check the tapered roller bearing dimensions and to achieve the prescribed goals, the 3D model was built, the virtual environment has been created and the motion control process was applied in 3DAutomate software.
Research on the Private Customized Information Retrieval based on Hadoop Cluster
Authors: Bo Li , Xiao Zhang , Jingyi Yan 
Published: August 2019

Abstract
With the development of science and technology, it is no longer a technical difficulty for users to find the answers they need from massive data of information retrieval. At present, with information retrieval methods, the most urgent need is how to find personalized search results that satisfy users and meet their needs. Therefore, private customized information retrieval technology has great research value. This paper builds a Hadoop distributed cluster search engine, improves the PageRank algorithm, adds classified attributes such as user tone, and further classifies and ranks the web pages. At the same time, the C4.5 algorithm is used to classify users, thus it provides private customized search service. Through comparative experimental analysis, it is proved that the improved method proposed in this paper is effective and has profound research value.
An Improved Distance Metric Clustering Algorithm for Association Rules
Authors: Futai Liang , Hongquan Li , Weifeng Zhang , Chenhao Zhang 
Published: August 2019

Abstract
By mining association rules in large data, we can reveal useful information contained in the data and find out the relationship between things or the law of motion. However, because of the huge transaction data, the association rules obtained by mining are complex and massive. It is difficult to find useful association relations, especially when the re-demand is uncertain. To solve this problem, this paper first uses Apriori algorithm to mine association rules from a data set, then defines similarity measure between association rules, and applies DBSCAN clustering algorithm to association rules analysis. The analysis results show that this method is effective in association rules analysis.
Application of Data Mining Technology in Evaluating Real Estate Investment Plan Based on GRA-AHP
Authors: Meier Zhuang , Pan Wen-Tsao , Zhuohong Shi , Yingying Zhou , Zuchang Zhong 
Published: August 2019

Abstract
Data mining and information technology is increasingly important in the era of big data. Many researches have been discussing the application of data mining and information technology in all walks of life. To further explore the practical value of data mining technology in economic and business field, this paper studies its application in evaluating real estate investment plans. R software is applied as the statistical computing console and relative program code is created to implement grey relational analysis-analytical hierarchy process(GRA-AHP), which establishes an improved evaluation model of decision-making. Firstly, the related data of the research is divided into several layers, namely the target layer, criteria layer and plan layer. In the criteria layer, the processing method is different from previous research because in this paper the indicator value of the plan layer to the criteria layer is calculated based on grey relational analysis rather than the pairwise comparison judgment matrix proposed by previous scholars, which makes this analysis more scientific and accurate. Then the plan layer single sort weight and the total sort weight of each plan can be calculated to provide reference for the final investment decision. This paper aims to propose a better evaluation method in the real estate investment and promote the application of data mining technology in economic fields.
Identifying Significant Components of Complex Software for Improving Reliability: Using Invocation Relationships and Component Characteristics
Authors: XUE Lixing , ZHANG Zhan , ZUO Decheng 
Published: August 2019

Abstract
The scales of software systems are getting larger and larger, which may make the system reliability become low. To improve their reliability, a set of important components that are able to strongly influence the system reliability are usually determined first. However, the existing determining approaches only consider the components which are often called by other components as significant ones, but overlook the components which often call others also have a strong effect on the system. Besides, the approaches all require component invocation probabilities which cannot be obtained easily in large-scale systems. To attack the problems, we propose a novel approach for identifying the significant components in complex systems. This approach includes two component ranking algorithms, which take into account not only the components that are frequently invoked, but also the components which often invoke others. The two algorithms, which do not require component invocation probabilities, can either make significant component ranking only based on the component invocation relationships or consider not only the component invocation relationships but also the component characteristics to achieve results. The significant components are selected according to the two ranking results. Extensive experiments are provided to evaluate the approach and draw comparisons with existing methods.
Analysis of Chinese Zither Modes Based on Finite Element Analysis
Authors: bing Hu , Haoran Li 
Published: August 2019

Abstract
This paper makes a modal analysis of Chinese zither by using the finite element analysis method. By combining traditional Chinese national musical instruments with computer simulation technology, it studies the modal structure of Chinese zither according to the method of “data model - establishing FEM model - assigning material parameters - establishing constraints - solving the case”. Through modal analysis, it not only verifies the validity of computer simulation method, but also provides data support and theoretical support for the improvement of Chinese zither structure and the structural research of traditional Chinese plucked instruments.
Multi-modulation Recognition Using Convolution Gated Recurrent Unit Networks
Authors: Jiyuan Tan , Limin Zhang , Zhaogen Zhong , Wenlong Yu 
Published: August 2019

Abstract
To solve the problems of long modulation and recognition time and complexity of convolutional neural networks, a modulation method based on CNN-GRU (Convolutional Neural Networks and Gated Recurrent Unit) is proposed. Firstly, the spatial features of the signal are extracted by CNN convolution operation, then the timing correlation of the signal is extracted by GRU and finally the recognition probability is output by using the softmax layer to achieve the purpose of multi-modulation recognition. The experimental results show that the recognition performance of the method is further improved under the condition of no prior information such as channel and noise, and 11 modulation categories such as 16QAM and 64QAM can be effectively identified, and the complexity of the method is low, which greatly saves. The training identification time has good engineering application value.
Mobility Analysis of Mobile VLC with Optical Zoom Antenna
Authors: Hu Shanshan , Chang Yuee , Wu Xingkui , Tang Yi 
Published: August 2019

Abstract
This paper specifically analyse the mobility performance in optical zoom receiving mobile VLC. Optical zoom antenna adjust the optical gain by changing the FOV and then effect the signal to noise ratio (SNR) at the receiver. Firstly, with same transmit power, we analysis the communicable area between fixed focus VLC systems at different FOV. Besides, we contrast the mobility between fixed-focus and optical zoom VLC. Comparing with fixed focus VLC, the mobility can be increased by 90% with optical zoom receiving at 800Mbps. As data rate increasing, fixed focus system is completely disrupted, while the optical zoom antenna still ensure well mobility. According to these analysis, optical zoom antenna can guarantee a stable and high speed communication over a wide range in mobile VLC.
Optimization Design of Networked Control System with Communication Interference
Authors: Niu Liangliang , Wei Haiping , Jin Lina 
Published: August 2019

Abstract
For network control systems with long delay and packet loss, firstly, it is based on the effectiveness of model-based control in network systems with long delay, and it also establish a feedback model that simulates delay as a system component. Considering the possible modeling errors of the feedback model, a design of the traditional linear system is proposed to design the controller by using the communication interference observer to compensate for the delay characteristics. Then, the steady-state error of the characteristic equation of the system is obtained and prove the feasibility and robustness of the method, and carried out the equivalent analysis of packet loss. Finally, the effectiveness of the controller is demonstrated by the simulation of communication interference data from comparing with the Smith predictor.