bluuebunny/crossref_metadata_2025 huggingface dataset:
Experimental Campaign Tests on a Tesla Micro-Expanders
Authors: Renuke Avinash , Traverso Alberto , Pascenti Matteo
Published: August 2019

This paper presents the experimental campaign on Tesla turbo expanders carried out at Thermo-chemical Power group (TPG) of University of Genoa, Italy. An experiment system is established using compressed air as a working fluid. A 200 W turbine is tested with rotational speed up to 40000 rpm. Experimental analysis focused mainly on the efficiency features of this expander, showing the impact on performance of different disk gaps, disk thickness, discharge holes, exhaust geometry, as a function of speed and mass flow. An improved version of 3 kW air Tesla turboexpander is built. Preliminary experimental results are discussed along with the effect of number of nozzles on the performance of the turbine.
Two-phase flow expansion: development of an innovative test-rig for flow characterisation and CFD validation
Authors: Traverso Alberto , Reggio Federico , Silvestri Paolo , Rizzo Sergio , Engelbrecht Geoff , Chasoglou Alexandros
Published: August 2019

The aim of this work is to describe the design of an innovative test rig for investigating the expansion of saturated fluids in the two-phase region. The experimental test rig was thought up and built by TPG of the University of Genoa. It will be equipped by probes and some optical accesses that permit high speed video recording and laser measurements. It will be useful for the study of the quality ratio, vapour and liquid droplet thermodynamic properties and their speed.
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.
Simulation of the rising of gas bubbles in a pilot-scale external loop airlift photobioreactor
Authors: Bagnerini Patrizia , Neviani Matteo , Paladino Ombretta
Published: August 2019

Air-lift reactors offer an interesting option as a microalgae cultivation system, especially for biorefineries. To optimize this application, a precise description of the moving interfaces formed by the liquid and gas phase is critical. In this paper, a coupled Level Set Method (LSM) and finite difference method is used to simulate gas bubbles dynamics in a pilot-scale external loop air-lift photobioreactor in which microalgae are used to capture CO2 from flue gas and to treat wastewater. Numerical simulations are carried out on a rectangular domain representing the section on the vertical axis of the riser. The data employed were either acquired from previous experimental campaigns carried out in the ALR or found in the literature. The rise, shape dynamics and coalescence process of the bubbles of flue gas are studied. The issue of volume loss characteristic of standard LSM is dealt with the conservative level set method. Computation results show good correspondence with the experimental ones.
Prospective teachers' understanding of environmental ethics approach: A qualitative study
Authors: Temel Senar
Published: August 2019

This study aims to determine prospective teachers' understanding of environmental ethics approach. The study employed qualitative research method. 20 prospective teachers were included in the research. The participants were chosen in purposeful sampling method. The research data were collected through a test of two open-ended questions developed by the researcher. The prospective teachers were asked questions on what environmental ethics approach meant, what the importance of environmental ethics in a globalizing world is and they were required to answer the questions in writing. The written answers were analyzed via content analysis. The findings obtained through content analysis were divided into categories related to the environmental ethics approach and then the themes were defined. After the analysis of the themes and categories, prospective teachers' understanding about the environmental ethics approach was revealed and then the findings were discussed in details.
Technological approach to development of adaptive e-learning system
Authors: Shershneva Victoria , Vainshtein Yulia , Kochetkova Tatiana , Esin Roman
Published: August 2019

Adaptation of learning process for students with regard to their individual characteristics has currently become topical. The article proposes a technological approach to development of adaptive e-learning system, principles of its elaboration and description its structure and components. The scientific novelty of the study consists in structuring the educational content as a hierarchy of terms, original methods and algorithms of adapting learning material, and the learning outcomes assessment model which provides for the assessment of the level of subject competence development. The structure of the system which includes the educational content model, the user model, the adaptation model, and the learning outcomes assessment model is presented in the article. The proposed approach to development the educational content model is based on the integration and development of the methods of logical-andgnoseological concept analysis with graph theory methods. The adaptive elearning course of a mathematical discipline is developed and implemented into educational process. System of web-based teaching includes a set of organizational and pedagogical conditions contributing for student to acquire knowledge and experience, to develop the skills which result in developing competence required for his or her professional activities. Materials of this study are of interest for both teachers who develop electronic educational courses and managers of educational institutions interested in implementing such courses into educational process
Continuity: The relation between concept image and procedural understanding
Authors: Coşkun Meltem , Turanlı Necla
Published: August 2019

The current study aims to examine the relation between concept images and procedural understanding of prospective Mathematics teachers (PMTs) related to ‘continuity’ in Math. The participants (n=9) study Mathematics Education at a state university during spring 2018; they are third, fourth and fifth grade students. The data come from interviews and open-ended tests developed by the researchers. More specifically, the data of concept images were collected through interviews and the data of procedural understanding were gathered via open-ended tests. The methodological approach used in the current study is descriptive analysis. The results of the study revealed that in addition to the presence of the PMTs whose understanding of concept images and procedural understanding are in accordance with each other, there are those whose understanding of these two concepts are not compatible with each other. Moreover, it has been observed that while PMTs who hold a concordant understanding between concept image and procedural understanding tend to express the concept of ‘continuity’ as rooted in their images, PMTs who have an incompatible understanding between these two concepts tend to provide formal definitions for the notion of ‘continuity’, as different from their own images.
Analysis of student performance through the use of two different active strategies
Authors: Sandoval Hamón Leyla Angélica , Casani Fernando , Rodriguez-Promeda Jesus , Olmos Albacete Ricardo
Published: August 2019

In the European Higher Education Area (EHEA), official degree studies should promote the competences and knowledge of students. This work is based on active strategies (conceptual maps and discussion panels) where students analyse and summarize the topics proposed in class, to improve their knowledge and skills. Therefore, the objective of this paper is to analyse the performance of business students by using the mentioned strategies in two different groups during the academic year 2018-2019. The implementation of this research was carried out using a quantitative approach, with mixed models (SPSS v20 software) of three dependent variables (two of knowledge and one for competences). The conclusions indicate that the group that used the panel discussion methodology increases more the acquired competences and the understanding of the basic concepts that are taught on the subject, than the group of the conceptual maps strategy.
Cooperative and Collaborative Knowledge Management, so how we should manage the most important resource of the organization − case study
Authors: du Vall Marta , Majorek Marta
Published: August 2019

The aim of the study is to analyze contemporary management systems and knowledge sharing, based on the analysis of existing materials and qualitative research − case studies. First it was necessary to solve dictionary concerns. In many languages, the words cooperation and collaboration are usually used as synonyms, and in some countries, collaborations are often pejoratively associated, so it is necessary to analyze the existing materials and present an adequate and precise definition of the title concepts. Then, the authors focused on a practical approach to working with intellectual capital throughout the organization and presented examples that can serve as role models.
Die Senkniere
Authors: Corts Magga
Published: August 2019

Die 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.
Wasser
Authors: Schmid Eva C.
Published: August 2019

In dieser Ausgabe beschäftigen sich alle Prüfungsfragen mit dem Heftthema Wasser.
Im Klartext: Der Hygieneplan
Authors: Handke Denis
Published: August 2019

Mit 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.
Study on voltage characteristics of short air arc with high current density arc root
Authors: Zhu Tiansheng , Liu Hongwu , Guan Ruiliang , Jia Shenli , Yin Nairui
Published: August 2019

In this paper, the voltage characteristics of short air arc with high average current density arc root were studied at atmospheric pressure. Cu-W electrodes with diameter of 5-14mm and gap length of 0.2-3 mm were used in the experimental study. The experimental current varies from 1,000A to 16,600 A. The average current density of the arc roots in the experiment was up to 245 A/mm2. In the scope of this study, the arc voltage is a function of the average current density of arc root when the electrode gap length is fixed. For same average current density of arc root, the arc voltage is approximately the same even if the experimental currents are different. And the arc voltage increases with the increment of the average current density of arc root. Theoretical analysis and experimental results show that the electrode fall voltage almost doesn’t change with the average current density of arc root. However the arc column voltage increases with the increment of the average current density of arc root.
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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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.
Position and Velocity Estimation Using TOA and FOA Based on Lagrange Programming Neural Network
Authors: Jia C , Yin J , Yang Z , Zhang L
Published: August 2019

This paper addresses the problem of estimating the position and velocity of a moving source utilizing the time-of-arrival (TOA) and frequency-of-arrival (FOA) measurements. Since the concerned estimation problem is highly non-linear and non-convex, we propose to utilize a novel neural circuit, namely the Lagrange programming neural network (LPNN) framework, to solve this problem. LPNN equips the abilities of fast convergence and the robustness of resisting high noise level, and thus these two advantages have drawn much attention for it recently. Since LPNN is able to solve the optimization problem with constraint, we first reformulate the original non-linear and non-convex maximum likelihood (ML) problem by introducing additional variables and constraints, and thus a neural network is built up based on the LPNN framework. Subsequently, the convergence and stability of the proposed neural network is mathematically proved and then verified by the results of numerical experiments. Different from the conventional numerical algorithms, the analog neural network can be utilized to fulfil the task of real-time calculation, especially when there are limited computation resources in some applications. The simulation results demonstrate that the proposed LPNN model equips the basic properties of convergence and stability, and also show the superior localization accuracy of the proposed method than other numerical algorithms.
Network Traffic Anomaly Detection Based on Incremental Possibilistic Clustering Algorithm
Authors: Tian-yi Yang , Shi-yue Liu , Jun-yi Liu
Published: August 2019

This paper proposed a Mahalanobis distance based Incremental Possibilistic Clustering (IPC) algorithm to detect abnormal flow. Firstly, the attributes of network flow is extracted by damped incremental statistics. Then the model of normal traffic will be generated by IPC algorithm. To extract the model of high-dimensional data without pre-known number of cluster centers, the algorithm gradually choose outliers as new clustering centers and merges the overlapping clustering centers. Finally, the data that doesn’t belong to any normal model is regarded as abnormal data. By using the Mahalanobis distance instead of the traditional Euclidean distance, the defect that the possibilistic clustering tends to find the features of hypersphere is solved. The experiments show that this method can distinguish normal flow and abnormal flow effectively and reaches the detection rate of 98%.
An Approach Combined the Faster RCNN and Mobilenet for Logo Detection
Authors: Mudumbi Terry , Bian Naizheng , Zhang Yiyi , Hazoume Florian
Published: August 2019

Although deep learning object detection tools such as Faster Recurrent Convolution Neural Network (Faster R-CNN) has demonstrated good performances in object detection, they also have a limited success rate for some applications. It is due to the lack of refinedness of feature maps for accurate localization, the insensitivity for small scale objects and fixed-window feature extraction in Region Proposal Network (RPN). In this paper, we performed a meticulous examination of both the proposal and the classification process by evaluating the adequacy of feature representations from different stages of the feature sequencing. We presented an approach to improve the Regional Proposal Network (RPN) by appropriate anchors selection, and proposed a modification by combining Faster R-CNN and MobileNet which influences higher-resolution feature maps for mobile devices. The results demonstrate that Faster R-CNN architecture with MobileNet has the best detection accuracy. The experiment result showed that we managed to achieve a final accuracy of 92.4% on a NVIDIA GeForce Gtx 1070 compare to previous work that achieved 90.8% of accuracy and found that our models performed well at the detection, with very low false positive rates possible for a fairly reasonably.
Improved Fast Adaptive IDW Interpolation Algorithm based on the Borehole Data Sample Characteristic and Its Application
Authors: Sun Liming , Wei Yingqi , Cai Hong , Yan Jun , Xiao Jianzhang
Published: August 2019

The inverse distance weighted algorithm (IDW) is one of the most widely used algorithms in geoscience calculation based on its university and simple theory. However, in the practical application based on borehole sampling data, the distance between boreholes is further than the sampling distance along the bedding direction of one borehole, and it needs to search all the near points through a large number of distance calculation, and the process is very slow, so this lacks practicality in the spatial interpolation of the large amount and non-uniform distribution data. Based on the special features of the borehole sampling data, this paper presents a fast adaptive and improved inverse distance weighted interpolation method. And firstly the sample point position could be indexed by the adaptive cube grid raster, then determine the index grid in the horizontal and vertical directions of the interpolation point, and combine these grids for the finally IDW calculation, which significantly improves the search speed of the adjacent interpolation calculation points. It can improve the engineering applicability of the IDW method, especially the three-dimensional spatial interpolation and computing has a good application prospect.
Reducing deforestation and improving livestock productivity: greenhouse gas mitigation potential of silvopastoral systems in Caquetá
Authors: Landholm David M , Pradhan Prajal , Wegmann Peter , Sánchez Miguel A Romero , Salazar Juan Carlos Suárez , Kropp Juergen P
Published: August 2019

Colombia's agriculture, forestry and other land use sector accounts for nearly half of its total greenhouse gas (GHG) emissions. The importance of smallholder deforestation is comparatively high in relation to its regional counterparts, and livestock agriculture represents the largest driver of primary forest depletion. Silvopastoral systems (SPSs) are presented as agroecological solutions that synergistically enhance livestock productivity, improve local farmers’ livelihoods and hold the potential to reduce pressure on forest conversion. The department of Caquetá represents Colombia’s most important deforestation hotspot. Targeting smallholder livestock farms through survey data, in this work we investigate the GHG mitigation potential of implementing SPSs for smallholder farms in this region. Specifically, we assess whether the carbon sequestration taking place in the soil and biomass of SPSs is sufficient to offset the per-hectare increase in livestock GHG emissions resulting from higher stocking rates. To address these questions we use data on livestock population characteristics and historic land cover changes reported from a survey covering 158 farms and model the carbon sequestration occurring in three different scenarios of progressively-increased SPS complexity using the CO2 fix model. We find that, even with moderate tree planting densities, the implementation of SPSs can reduce GHG emissions by 2.6 Mg CO2e ha−1 yr−1 in relation to current practices, while increasing agriculture productivity and contributing to the restoration of severely degraded landscapes.
Tropical deforestation drivers and associated carbon emission factors derived from remote sensing data
Authors: De Sy V , Herold M , Achard F , Avitabile V , Baccini A , Carter S , Clevers J G P W , Lindquist E , Pereira Maria , Verchot L
Published: August 2019

Reducing emissions from deforestation and forest degradation, and enhancing carbon stocks (REDD+) is a crucial component of global climate change mitigation. Remote sensing can provide continuous and spatially explicit above-ground biomass (AGB) estimates, which can be valuable for the quantification of carbon stocks and emission factors (EFs). Unfortunately, there is little information on the fate of the land following tropical deforestation and of the associated carbon stock. This study quantified post-deforestation land use across the tropics for the period 1990–2000. This dataset was then combined with a pan-tropical AGB map at 30 m resolution to refine EFs from forest conversion by matching deforestation areas with their carbon stock before and after clearing and to assess spatial dynamics of EFs by follow-up land use. In Latin America, pasture was the most common follow-up land use (72%), with large-scale cropland (11%) a distant second. In Africa deforestation was often followed by small-scale cropping (61%) with a smaller role for pasture (15%). In Asia, small-scale cropland was the dominant agricultural follow-up land use (35%), closely followed by tree crops (28%). Deforestation often occurred in forests with lower than average carbon stocks. EFs showed high spatial variation within eco-zones and countries. While our EFs are only representative for the studied time period, our results show that EFs are mainly determined by the initial forest carbon stock. The estimates of the fraction of carbon lost were less dependent on initial forest biomass, which offers opportunities for REDD+ countries to use these fractions in combination with recent good quality national forest biomass maps or inventory data to quantify emissions from specific forest conversions. Our study highlights that the co-location of data on forest loss, biomass and fate of the land provides more insight into the spatial dynamics of land-use change and can help in attributing carbon emissions to human activities.
1. What is secularism?
Authors: Copson Andrew
Published: August 2019

The British social reformer George Jacob Holyoake (1817–1906) coined the word ‘secularism’ to describe his this-worldly approach to personal morals, to philosophy, and to the of society and politics. A modern definition, provided by scholar Jean Baubérot, sees secularism made up of three parts: separation of religious institutions from the institutions of the state and no domination of the political sphere by religious institutions; freedom of thought, conscience, and religion for all; and no state discrimination against anyone on grounds of their religion or non-religious worldview. ‘What is secularism?’ considers these three parts in more depth and also explains that the idea of secularism is much older.
6. Conceptions of secularism
Authors: Copson Andrew
Published: August 2019

Jean Baubérot’s ideal secularism is not a political reality anywhere and never has been. There are a variety of configurations even in states that describe themselves officially as secular. They do not have identical laws, constitutions, or ways of relating to religious institutions. There are also some states that are not officially secular, but are in many ways secular in practice. ‘Conceptions of secularism’ discusses the continuing debate that rages over the definition of ‘secularism’ between philosophers, sociologists, political scientists, campaigners, politicians, and lawyers who all disagree with each other about what it should and should not mean. All these conceptions of secularism influence each other and all have their partisans and their critics.
Socratic literature and the Socratic problem
Authors: Taylor C. C. W.
Published: August 2019

‘Socratic literature and the Socratic problem’ asks what access sources give us to the historical Socrates. The only Socratic literature known to have been written before Socrates’ death is comedy, which provides a contemporary caricature. Various authors produced ‘Socratic conversations’, commemorating Socrates and defending his memory against the charges made at the trial and against hostile accounts. The Socratic writings of Xenophon and Plato’s Socratic dialogues are the only bodies of Socratic literature to have survived complete. In Plato’s portrayal of Socrates there is no sharp line to be drawn between ‘the historical Socrates’ and ‘the Platonic Socrates’ who assumes the depersonalized role of spokesman for Plato’s philosophy.
Eyes in the Sky, Boots on the Ground: Assessing Satellite‐ and Ground‐Based Approaches to Crop Yield Measurement and Analysis
Authors: Lobell David B , Azzari George , Burke Marshall , Gourlay Sydney , Jin Zhenong , Kilic Talip , Murray Siobhan
Published: August 2019

Understanding the determinants of agricultural productivity requires accurate measurement of crop output and yield. In smallholder production systems across low‐ and middle‐income countries, crop yields have traditionally been assessed based on farmer‐reported production and land areas in household/farm surveys, occasionally by objective crop cuts for a sub‐section of a farmer's plot, and rarely using full‐plot harvests. In parallel, satellite data continue to improve in terms of spatial, temporal, and spectral resolution needed to discern performance on smallholder plots. This study evaluates ground‐ and satellite‐based approaches to estimating crop yields and yield responsiveness to inputs, using data on maize from Eastern Uganda. Using unique, simultaneous ground data on yields based on farmer reporting, sub‐plot crop cutting, and full‐plot harvests across hundreds of smallholder plots, we document large discrepancies among the ground‐based measures, particularly among yields based on farmer‐reporting versus sub‐plot or full‐plot crop cutting. Compared to yield measures based on either farmer‐reporting or sub‐plot crop cutting, satellite‐based yield measures explain as much or more variation in yields based on (gold‐standard) full‐plot crop cuts. Further, estimates of the association between maize yield and various production factors (e.g., fertilizer, soil quality) are similar across crop cut‐ and satellite‐based yield measures, with the use of the latter at times leading to more significant results due to larger sample sizes. Overall, the results suggest a substantial role for satellite‐based yield estimation in measuring and understanding agricultural productivity in the developing world.