bluuebunny/crossref_metadata_2025 huggingface dataset:
Hypothesis testing of Geographically weighted bivariate logistic regression
Authors: Fathurahman M , Purhadi  , Sutikno  , Ratnasari V
Published: December 2019

In this study, the hypothesis testing of geographically weighted bivariate logistic regression (GWBLR) procedure is proposed. The GWBLR model is a bivariate logistic regression (BLR) model which all of the regression parameters depend on the geographical location in the study area. The geographical location is expressed as a point coordinate in two-dimensional geographic space (longitude and latitude). The response variables of BLR model are constructed from a (2 × 2) contingency table and it follows the multinomial distribution. The purpose of this study is to test the GWBLR model parameters. There are three hypothesis tests. The first is a parameters similarity test using the Vuong test method. The test is to obtain a significant difference between GWBLR and BLR. The second is a simultaneous test using the likelihood ratio test method. The simultaneous test is to obtain the simultaneous significance of the regression parameters. The last is a partial test using Wald test method. The result showed that the Vuong statistic and Wald statistic have an asymptotic standard normal distribution, whereas the likelihood ratio statistic has an asymptotic chi-squared distribution.
The Optimal Implementation of Chlorination, Treatment, and Education Controls in Reducing the Transmission of Cholera Disease
Authors: Fitria I , Hasanah S M , Subchan  , Pratama A P
Published: December 2019

Cholera is an acute disease caused by the bacteria Vibrio Cholerae. Cholera is a contagious and deadly disease that requires immediate medical treatment. The mathematical studies are conducted to create models of cholera transmission. The cholera transmission models are carried out by implementing the optimal controls, namely the chlorination for bacteria, control treatment for quarantined individuals and education campaigns for susceptible and infected individuals. The optimal control efforts are given to minimize the spreading of cholera disease. The method used to solve this optimal control problem is Pontryagin Minimum Principle. Based on the simulation, the provision of optimal controls in forms of education and treatment in individuals and chlorination can minimize the concentration of bacteria and the number of infected humans.
Forecasting Surabaya Rainfall in 2017 Using First Order Autoregressive Model through INLA Bayesian Approach
Authors: Sutanto Hery Tri
Published: December 2019

Water is one of the natural factors which affects the life of organisms on earth. If in one area, there is a sufficient amount of rain, then it will support the life of organisms in that area. However, if an area has an excessive amounts of rain, flooding will occur and it will damage the infrastructure, the agricultural land and some existing ecosystems. One way to reduce unwanted floods is by predicting accurate flood discharge. It can be used not only to design water buildings but also to manage water flow. Flood discharge can be predicted using the time series method, namely the First Order Autoregressive model, also known as the AR model (1). Estimating parameters in the AR model (1) can be done using the Moment, least Square and Maximum Likelihood methods. However, because the sample size used in this study is small then the Bayesian method can be used to estimate the AR model parameters (1). It has some advantages such as: 1. It can produce logical interpretations to conclude statistically in time series analysis 2. The output can always be updated based on the latest information. The Markov Chain Monte Carlo method is one method that can be used for Bayesian inference calculations, specifically the Gibbs sampler and Metropolis-Hastings algorithms. Both of these algorithms are more flexible and easily adapted to estimate complex models with many parameters or characterized by posterior nonstandard distributions. The MCMC theory states that the convergence distribution of the simulation value to the posterior distribution has a number of iterations to infinity, the posterior distribution will not be feasible. So that the processing of data consume a lot of time to reach convergence, then if it is not stopped then it will give suggestions about how some MCMC iterations become convergent. If the model is more complex then the MCMC algorithm is slower and the calculation becomes not feasible. Therefore, Rue et al. (2009) proposed a fast and accurate algorithm called the Integrated Nested Laplace Approximation Algorithm (INLA).
Oscillation Phenomena of Rayleigh Equation Disturbed by Superposition of Two Harmonic Excitation
Authors: Alfan A , Dewi N A C
Published: December 2019

The Rayleigh Nonlinear Oscillation Equation Phenomenon disturbed by two external harmonic forces. One of which is small, will be discussed. Using the Multiple Scales method to obtain analytical solutions, several cases of resonance are determined. Steady-state solutions and their stabilities will be investigated. Depending on the value of amplitudes and frequencies of the external forces given, for a non-trivial steady-state solution, there are two possibilities, namely a periodic solution, and a non-periodic solution that raises the beating phenomenon.
Multiclass Classification of Brain Cancer with Multiple Multiclass Artificial Bee Colony Feature Selection and Support Vector Machine
Authors: Kharis S A A , Hadi I , Hasanah K A
Published: December 2019

A World Health Organization reported that the mortality rate due to brain cancer is the highest in the Asian continent. It is critical importance that brain cancer can be detected earlier so that the treatment process can be carried out more precisely and will be able to extend the life expectancy of brain cancer patients. Taking advantage of microarray data, machine learning methods can be applied to help brain cancer prediction according to its type. This problem can be referred to as a multiclass classification problem. Using the one versus one approach, there will be as many as

k
(
k
−
1
)

2

two-class problems, where k indicates the number of classes. In this paper, Multiple Multiclass Artificial Bee Colony (MMABC) implemented as a feature selection method and Support Vector Machine (SVM) as a classification method. ABC algorithm proved successful in solving optimisation problems with high dimensionality, and SVM can produce accurate and robust classification results. The data obtained from Broad Institute data. The data consist of 7129 features and 42 samples. From the experiment, the accuracy of Multiple SVM using a feature selection based MMABC method reached 95.24% accuracy in usage 300 best features; this percentage slightly more superior than SVM method without feature selection.
The Global Kernel k-means Clustering Algorithm for Cerebral Infarction Classification
Authors: Rustam Z , Fitri S G , Selsi R , Pandelaki J
Published: December 2019

Cerebral infarction is the death of neurons, glia cells and blood vessel systems caused by a lack of oxygen and nutrients. This situation is often called storke. Common causes of neuron damage are hypoxia, which is caused by impaired blood flow, reduced oxygen pressure in blood circulation, toxins, and hypoglycemia which can result in the same morphological changes as morphological changes in hypoxia. Hypoxia is reduced oxygen pressure in the alveoli, resulting in hypoxemia which can cause hypoxic brain tissue. The initial stage of ischemic neurons is characterized by the formation of micro vacuolization, which is characterized by the size of the cells that are still normal or slightly reduced, the nucleus shrinks slightly, vacuoles occur in the perikaryon region. This micro vacuole can be found in neurons in hippokamus and cortical 5-15 minutes after hypoxia. The final sign of cell damage due to ischemia is characterized by the nucleus becoming pyknotic and fragmented. To classify cerebral infarction, the author uses the global k-means clustering algorithm as a classification method that shows that the method has good accuracy, good memory, and good precision in classifying cerebral infarction. In this proposed method, the global kernel k-means clustering algorithm is an extension of the standard k-means clustering algorithm and has been used to identify or classify clusters that are non-linearly separated in space input. This method adds one cluster at each stage through a global search process consisting of several k-means kernel executions from the appropriate initialization. Therefore, this method can make good classification accuracy. In particular, this achieves classification accuracy of up to 78% for the highest accuracy.
The Effect of Local Micro Organism and Mycorrhizal Fungi on Anatomical and Morphological Responses of Red Chili (Capsicum annuum L.) at Different Soil Water Level
Authors: Naafi T N , Rahayu Y S
Published: December 2019

Red chilli as a vegetable commodity plays an important role for Indonesian people and its cultivation depends on the level of water availability, which is still a problem in certain area in Indonesia. This study aimed to describe the effect of local microorganism (LMO) concentration and different soil water levels on the anatomical and morphological responses of red chilli by adding the mycorrhizal fungi in all treatments during the cultivation. This experimental study used Randomized Block Design (RBD) with two factors, namely the concentration of LMO (0mL/L, 25 mL/L, 50 mL/L, 75 mL/L) and different soil water levels based on field capacity measurement (100%, 75%, 50%, and 25%) with 3 replications. The parameters obtained included anatomical parameters (stomatal density and trichome density) and morphological parameters (plant height, leaf number, wet biomass, root length, mycorrhizal infection and relative water content of leaves). Data obtained from this study was in the form of morphological response of red chilli and anatomic parameters. Data obtained in this study were analyzed by two-ways ANAVA and continued by the Duncan test. The results showed that there was an effect of LMO concentration and different soil water levels by the addition of mycorrhizal fungi on plant height, wet biomass, relative water content of leaves with the highest effect of LMO concentration at 75 ml/L with water level of 25%. In the stomatal density, the LMO concentration and water levels that significantly effect was 25 ml/L with water level of 25%. Although there was no significant effect on leaf number, root length, mycorrhizal infection and trichome density parameters due to the treatments. These findings recommended that red chilli could be cultivated better in the interaction of 75 mL/L of LMO concentration and soil water level of 25%.
The Effect of Gibberellin Extracted from Eichhornia crassipes Root on the Viability and Duration of Hard Seed Germination
Authors: Ummah K , Rahayu Y S
Published: December 2019

The germination process is influenced by external and internal factors including the type of seed. Hard seeds require special treatment in stimulating the germination process such as scarification and stratification (for example applying exogenous hormones to seeds during the germination process). This study aimed to describe the effect of exogenous gibberellin hormone extracted from Eichhornia crassipes root on the viability and duration of germination of three different hard seeds. This study used RBD (Randomized Block Design) with two treatment factors, namely root extract concentration from Eichhornia crassipes (0 ppm, 200 ppm, 300 ppm, 400 ppm, and 500 ppm) and hard seed types (sapodilla seeds =Annona muricata, soursop seeds =Manilkara kauki, and longan seeds = Dimocarpus longan) with three replications. The observed parameters for seed viability were germination percentage and vigour index, while duration of germination parameters was germination index. Data were analyzed using ANOVA and followed by Duncan Test. The results showed that there was a significant effect of the root-extracted gibberellin concentrations and types of seeds on viability and duration of germination seeds. The optimal concentration of root-extracted from Eichhornia crassipes was 500 ppm, with the highest germination percentage, vigour index, and germination index were 80.55%, 387.33%, and 0.254%/etmal respectively. The longan seeds revealed the best viability and shortest duration of germination due to applying the exogenous gibberellin hormone extracted from Eichhornia crassipes root. The findings revealed that there was a positive synergism between exogenous and endogenous gibberellin on the effect of germination process in three different hard seeds tested.
Students’ procedural and conceptual Fraction knowledge based on cognitive style
Authors: Novianggraeni T D , Masriyah  , Lukito A
Published: December 2019

Recent research on children’s procedural conceptual knowledge has suggested that there are individual differences. Some children have more conceptual knowledge, some children have more procedural knowledge, and some children have an equal level of both. In this study we compared and investigated individual differences knowledge of procedural and conceptual fraction among cognitive style of seventh (n=40) graders in Surabaya, East Java. Data collection in three sessions; all participants answered the same tasks. In the first session, students completed the Group Embedded Figures Test (GEFT) in 12 minutes to investigate their cognitive style (Field Dependence cognitive (FD) or Field Independence cognitive (FI) styles). In the second session, students completed three written measures (procedural and conceptual fraction knowledge test in 45 minutes) individually in a classroom. In the third session, students were individually interviewed for approximately 30 minutes. They answered questions on how they would solve fraction tasks. Students of the FI group performed significantly better than the FD group, on a measuring fraction and estimating number line. Overall, these results provide a more detailed picture of individual differences in procedural and conceptual knowledge in cognitive style.
Students’ Problem Solving Behavior On Multiplicative Word Problem
Authors: Auliatullah S R , Fuad Y , Ekawati R
Published: December 2019

Students in junior high school frequently erroneously solving multiplicative word problems. Students in this stage should be able to understand the known and what is asked, what the strategies properly, and how to execute it become the right one. It has close related with student problem solving behavior, it is given provided description of the students’ behaviour. The purpose is to investigate students’ problem solving behavior on solving multiplicative word problem. This study conducted on a class of 7Ath class in SMPN 39 Surabaya, consist of 27 girls and 15 boys, and had chosen purposively from ninth classes. Students had to answer multiplicative word problem, based on result show that there are three category students when solve the task. Three volunteer students were selected as research subject which have different ability that had interpreted as context this study, subjects needed for deep interview. The problem solving behavior of subject who solve the tasks multiplicative properly tend to Meaning Based Approach-justification (MBA-j), the problem solving behavior of subjects who solve exactly one task multiplicative additively tend to Meaning Based Approach-full context (MBA-fc), and the problem solving behavior of subjects who solve at least two task multiplicative additively tend to Direct Translation Approach-not proficient (DTA-np).
Analysis of the Number of Seventh Grade Student Error Type in Solving Two-Dimensional Figure Problems
Authors: Iqlima S F D , Sofro A
Published: December 2019

Solving the problem is one of the goals in learning. In reality, there are still many students who make an error in the two-dimensional figure. The style of students in absorbing, processing, and managing information is called learning style. In some studies, the mathematical abilities boys and girls are different. The investigation of the types of student errors based on learning styles and sex has developed massively. Thus, this study will investigate variables that affect the number of types of errors in solving the problem of a two-dimensional figure. The population in this study is a seventh-grade student, and the sample in this study is 32 seventh grade students. Data obtained from questionnaires and tests. There are two variables in this study, the independent variable is learning styles and gender, and the dependent variable is the number of error types. Hence, the appropriate approach is using Poisson regression due to a discrete response variable. The results show that the coefficient of learning style has substantial evidence to reject the null hypothesis with alpha 0.05. It means that the learning style has a significant impact on the number of error types.
The Model of Visual Thinking of Prospective Math Teacher in Understanding the Formal Definition of Convergent Sequences Based on Gender Differences
Authors: Darmadi
Published: December 2019

The model of visual thinking is interesting to learn because the concepts are organized based on the meaning of forming mental imagery in the mind. Thinking by using mental imagery (visual information) is called visual thinking. This paper discusses the model of visual thinking of prospective mathematics teachers in understanding formal definition of convergent sequences based on gender differences as a result of descriptive-explorative research with a qualitative approach. The visual thinking activities of male and female students are found around three aspects: bringing up mental imagery, processing mental imagery (determining mental imagery, improving mental imagery), and utilizing mental imagery. To bring up mental imagery, the mind summons mental imagery or makes mental imagery. To determine mental imagery, the mind collects mental imagery and selects mental imagery. To improve mental imagery, the mind justifies mental imagery or completes mental imagery. To utilize mental imagery, the mind uses mental imagery or represents mental imagery. Processing mental imagery has done according to the needs and purpose of the activity in understanding the formal definition of the convergent sequence.
Recitation program to improve students’ conceptual understanding of Thermodynamics
Authors: Adila A S D , Sutopo  , Wartono
Published: December 2019

The purpose of this research was to analyze the improvement of students’ mastery of thermodynamics concepts after they learn three packages of recitation program that cover state equation of ideal gas, The First Law of Thermodynamic, and The Second Law of Thermodynamic. The subjects consisted of 21 undergraduate students enrolling in the fundamental physics course. The results showed that the recitation program improved students’ conceptual understanding of thermodynamic with the d-effect size of 2.51 and N-gain of 0.365. The program effectively helps the students in constructing P-V diagrams and understanding the relationship between the average particle’s kinetic energy and temperature of the gas. However, some contents need to be improved to help the students more fluent in determining total work and heat involved in any cyclic process.
Deterministic Dual-stack Query Tree RFID tag anti-collision algorithm
Authors: Zhou Yanling , Clemen Thomas
Published: December 2019

Tag collision problems are a major issue affecting the performance of RFID systems. The probabilistic tag anti-collision algorithm has tag starvation and cannot identify some tags. This paper proposes a deterministic dual-stack query tree algorithm (DDQT). It successfully implements the anti-collision algorithm of tags by generating new query codes and tag identification functions. At the same time, the DDQT algorithm greatly saves memory space by adding a prefix code stack and a suffix code stack. The DDQT algorithm is simple, and there is no limit on the length of the electronic tag to be queried. Compared with the previous query-tree algorithms, the DDQT algorithm has obvious improvements in query comparison times, empty query times, and occupied memory space. It can effectively remove idle nodes, shorten recognition time and save memory resources, thus improving the speed and accuracy of label recognition to some extent.
Seeking for optimum culture medium for chlorella pyrenoidosa and analysis of the amino acid component
Authors: Li Wei , Chen Xiaojiang , Zheng Mengmeng , Li Zhicheng , Li Haiyang
Published: December 2019

Chlorella Pyrenoidosa is one of the widely used algae in aquaculture. In order to find out a proper culture medium for high-density culturing to meet the demand of fish reproduction and water quality control, five normal algae culture media were test via multiple comparisons. The densities of the five groups, with six parallel samples each, which were cultured in corresponding medium, were determined by blood counting chamber on the beginning (0d), the 3rd day (3d), the 6th day (6d) and 9th day (9d). Then the growth curves were described and the growth radio were calculated and compared by One-Way ANOVA (Turkey method) using the SPSS 21.0 software. The multiple comparisons results revealed that HGZ group could reproduced a rapid and stable speed at high density, while SE group and Aquatic 4# reproduced faster than the HGZ group. Amino acid component results revealed that C. Pyrenoidosa contains 18 kinds of amino acid (42.19 ∼ 43.14% of the body mass). There are significant differences on total amino acid, fish essential amino acid and non-essential amino acid between groups based on the multiple comparisons. However, the amino acid could not meet the demand of fish or shellfish. Thus, extra amino acid, such as tryptophan and methionine should be added and the HGZ medium was the best choice for producing C. Pyrenoidosa to satisfy the aquaculture.
Research on the acute toxicity and teratogenicity of the feeding L-tryptophan
Authors: Hao Fuxing , Liu Li , Xu Yaya , Han Guilin , Zhang Yumei
Published: December 2019

In order to evaluate the safety of the feeding L-tryptophan, we conducted acute toxicity test and teratogenicity test in rats. Rats were fed with L-tryptophan by gavage. The oral LD50 was more than 20.0g/kg b.w. In the teratogenicity test, the doses of L-tryptophan were 5.0g/Kg b.w., 2.5g/Kg b.w. and 1.25g/Kg b.w. We set up a normal control group. The rats were fed by gavage once a day from the 7th to 17th day of pregnancy. At the 20th day of pregnancy, we counted and measured the litter size, placenta weight, live baby weight, body length, tail length, fetus malformation rate, live fetus average malformation rate, maternal fetus malformation rate, fetus death rate, absorptive fetus rate and other indicators. Then we use SPSS12.0 software to carry out data statistical analysis, and One-Way ANOVA and t-test for comparison between groups. The results showed that, when each dose group compared with the control group, there was no significant difference in average body weight, body length, tail length, placenta weight, fetus live rate, fetus death rate and absorptive fetus rate when compared to the normal control group(P>0.05), and there was no significant difference in the common deformity indexes, such as fetus malformation rate, live fetus average malformation rate and maternal fetus malformation rate between each dose group and the normal control group(P>0.05). The oral LD50 of L-tryptophan to Wistar rats was more than 20.0g/kg b.w., and the traditional teratogenicity test was negative, indicating that the feed additive belongs to the actually non-toxic level and has no obvious teratogenicity.
The heterogeneity of village cadres and poverty reduction-Based on the survey data of 757 administrative villages in western minority areas
Authors: Luo Yuke , Ma Degong
Published: December 2019

By using the data of 7 provinces, 757 administrative villages and 31615 famers in the minority regions of the Midwest, this paper investigates the relationships between heterogeneity of village cadres and poverty reduction. And we find that the age of the village cadres, ethnic identity, investment promotion, income and the education background have a significant positive impact on farmer poverty reduction. Using village collective financial income as the instrumental variable, we find that village cadres of every 1% increase in wage income, the poverty rate will be reduced by 0.007%. Therefore, we table four proposals: the choice of the village and village officer should follow the principle of “young and old”; encouraging to choose village cadres of ethnic minorities; encouraging investment promotion and investment stay in the village; setting income of village cadres within a reasonable range. The conclusions above is of great political significance to solve the problem of poverty reduction of the heterogeneity of village cadres.
Development of on-line monitoring system for insulation of high voltage electrical equipment
Authors: Li Hang , Luo Yaoyao , He Yang , Li Fangying , Wu Ting
Published: December 2019

The development of on-line monitoring technology for high-voltage electrical equipment insulation, the working principle of online monitoring device, and the problems in operation were comprehensively expounded. The on-site verification technology of high-voltage electrical equipment insulation online monitoring system was studied, and online monitoring was analyzed. Management and technical issues with the device were found. On this basis, the on-site calibration device for the on-line monitoring system of high-voltage electrical equipment insulation was developed. The results of on-site non-power-off verification of high-voltage electrical equipment insulation online monitoring system produced by several manufacturers were introduced. Analysis and elaboration of its key technologies.
Watermarking in halftone image with maximal child node dependence coefficients in wavelet domain
Authors: Gong Hangyu , He Zifen
Published: December 2019

To achieve high image quality, this paper proposes a novel approach but efficient algorithm for halftoning watermarking. Wavelet coefficients of edge details have strong relations, while the dependence of coefficients of texture is more weak. On the other hand, large wavelet coefficients contain the information of image brink. Considering the relationship of intra-scale and maximal coefficients, the boundary error measure is built. While the gray image turns to halftone image using proposed algorithm, binary watermark is embedded in the edge position. In order to enhance the ability to resist cropping and smearing attack, the watermark image is pre-treated with Arnold transformation processing. The proposed method is effective, because the halftone image is embedded as a watermark sequence during the halftone process. Experiment results show that this algorithm does not cause significant distortion of the image and is good resistance to cropping, daub, JPEG compression and noise attacks.
Evaluation of the experimental project performance assessment mode with the application of descriptive statistical analysis method
Authors: Liu Renbao
Published: December 2019

In order to solve the problem that currently, the performance assessment mode of most experimental projects only adopts the individual assessment while neglecting teamwork, puts forward the experimental project performance assessment mode based on team communication, which takes all the students participating in the project as a team, and divides the team into several groups according to project contents and tasks. Team members complete the project tasks jointly through team communication and group and individual quantitative scoring will be carried out according to the completion of tasks. After conducting the descriptive statistical analysis of an experimental project assessment performance of 223 students from 8 classes of 4 undergraduate majors in a university through Stata15.1, the results show that the results of the project assessment performance data all show a normal distribution by major, class, group and individual, the assessment results are ideal, and the assessment mode is feasible. The innovation is to use the Stata, and use the descriptive statistical analysis method to make an in-depth and careful statistical analysis of the experimental project performance assessment mode based on the team communication proposed. And the normality test is carried out to make an objective evaluation to the assessment results.
The design of micropower field data collector based on MSP430 microcontroller
Authors: Jiao Chun , Tang Ming
Published: December 2019

Field data collectors are widely used in industrial control and information monitoring. According to the design requirements of micropower consumption and reliability, combined with MSP430 microcontroller, this paper expounds the design scheme of a new type of micropower field data collector, and discusses the overall design of the system and the implementation method of main functional units.
An improved SNIP denoising algorithm applied in EDXRF
Authors: Ge Liangquan , Li Hui , Tang Chuanfeng , Li Fei , Zhu Kai , Yang Jin
Published: December 2019

Based on the phenomenon of peak height reduction in existing denoising algorithms, this paper modifies the traditional SNIP algorithm, proposes an improved SNIP algorithm and applies it to EDXRF denoising. Two evaluation parameters RMSE and PCC are used to compare the improved SNIP algorithm with the traditional SNIP algorithm. The experimental results show that the improved SNIP algorithm has great advantages both in similarity and relevance, and the results of the improved SNIP algorithm are more consistent with the characteristics of the original data peak than the original SNIP algorithm, which is beneficial to the qualitative and quantitative analysis of the energy dispersive X-ray fluorescence spectrum.
BP neural network study on the quality evaluation system of innovation and entrepreneurship education in local universities
Authors: Huang Wenfeng , Liu Bowen , He Xingjie , Zhou Yan , Ning Binbin , Wang Liang
Published: December 2019

When the country vigorously advocates the goal of cultivating innovative and entrepreneurial engineering talents, the quality evaluation of innovation and entrepreneurship education has naturally become a part of the higher education system. However, there are few studies on the quality evaluation of innovation and entrepreneurship education in engineering majors in China. Firstly, through literature research, combined with the current development trend of quality evaluation of innovation and entrepreneurship education at home and abroad, BP neural network-based evaluation method was selected. Secondly, according to the three-element theory of education, namely, the three factors of educators, educators and education, and comprehensive research, the content of quality evaluation of innovation and entrepreneurship education in engineering majors in colleges and universities is determined, that is, from professional links, teaching links and students. Levels to build evaluation indicators. After establishing the evaluation index system, this paper uses Chengdu University of Technology as a research sample to issue questionnaires for engineering students in Chengdu University of Technology to obtain data for use, and to analyze and analyze the data by AHP, so as to obtain the weight of each indicator. Finally, based on the data collected by the questionnaire, the BP neural network data fitting and model training and optimization are carried out to determine the feasibility of the quality evaluation index of innovation and entrepreneurship education in engineering majors in colleges and universities, and to establish BP neural network evaluation model for engineering majors. The innovation and entrepreneurship education quality evaluation system provides new research methods and research ideas, enriches the connotation and breadth of the quality evaluation system of innovation and entrepreneurship education in engineering majors, and makes up for the shortcomings and vacancies in related fields.
A method for converting entropy to inclusion measure of interval type-2 fuzzy sets
Authors: Zheng Gao , Wang Jing
Published: December 2019

As tools for dealing with universal fuzziness in human thinking, traditional fuzzy sets, namely type-1 fuzzy sets, are not able to directly model uncertainties about membership functions, however type-2 fuzzy sets can make up for this deficiency. Interval type-2 fuzzy sets, the simplified cases of general type-2 fuzzy sets, are practical because its membership functions and operations are greatly simplified. The inclusion measure and entropy of fuzzy sets are two important parameters with application prospects, the former describes the degree to which a fuzzy set is included in another, the latter shows the quantity of fuzzy information in a fuzzy set. It is important to make in-depth research on the two measures. In this paper, we mainly discuss the relationship of the inclusion measure and entropy of interval type-2 fuzzy sets proposed by Zheng et al., and present a theorem that converts the entropy to the inclusion measure of interval type-2 fuzzy sets. The conclusion provides the basis for further research.
Density-dependent quantized kernel least mean square with desired smoothing
Authors: Lin Qing , Huang Yulei , Li Yan
Published: December 2019

Kernel least mean square algorithm is a simple and effective adaptive algorithm, but it is constrained by its infinite network size. Many schemes have been proposed to reduce the size of the network, but the distribution of input data and the desire output are seldomly considered together. In this paper, we present a density correlation quantization scheme in input space and a method of smoothing the desired output by using the average value of the neighbourhood in output, and call it the DQKLMS-S algorithm. The good performance of DQKLMS-S is verified by experiments.
Using supply chain data to monitor zero deforestation commitments: an assessment of progress in the Brazilian soy sector
Authors: zu Ermgassen Erasmus K H J , Ayre Ben , Godar Javier , Bastos Lima Mairon G , Bauch Simone , Garrett Rachael , Green Jonathan , Lathuillière Michael J , Löfgren Pernilla , MacFarquhar Christina , Meyfroidt Patrick , Suavet Clément , West Chris , Gardner Toby
Published: December 2019

Zero deforestation commitments (ZDCs) are voluntary initiatives where companies or countries pledge to eliminate deforestation from their supply chains. These commitments offer much promise for sustainable commodity production, but are undermined by a lack of transparency about their coverage and impacts. Here, using state-of-the-art supply chain data, we introduce an approach to evaluate the impact of ZDCs, linking traders and international markets to commodity-associated deforestation in the sub-national jurisdictions from which they source. We focus on the Brazilian soy sector, where we find that ZDC coverage is increasing, but under-represents the Cerrado biome where most soy-associated deforestation currently takes place. Though soy-associated deforestation declined in the Amazon after the introduction of the Soy Moratorium, we observe no change in the exposure of companies or countries adopting ZDCs to soy-associated deforestation in the Cerrado. We further assess the formulation and implementation of these ZDCs and identify several systematic weaknesses that must be addressed to increase the likelihood that they achieve meaningful reductions in deforestation in future. As the 2020 deadline for several of these commitments approaches, our approach can provide independent monitoring of progress toward the goal of ending commodity-associated deforestation.
Water rights, river compacts, and legal-policy stationarity in the American West*
Authors: Perramond Eric P
Published: December 2019

This article examines static-data assumptions trapped in water rights and, separately, in larger interstate river compacts in the American West. These reflect assumptions of scalar stationarity embedded in water codes in western states. State water adjudications sort how much water is being used, but the resulting data are often publicly unavailable and unchanged. Interstate river compacts often divide fixed, erroneous river flow data. River compact data, based on early 20th century optimistic estimates of river flow, have not changed in policy language. At both the micro- and the macro-scale, these separate data remain fixed, complicating water management in the American West.
Simulation tests of new solution of the longwall shearer haulage system
Authors: Kotwica K , Stopka G , Gospodarczyk P
Published: December 2019

The article presents the idea of a new solution for KOMTRACK longwall shearer haulage system. Based on the analysis of test results of an earlier version of the FLEXTRACK haulage system, a new version of the KOMTRACK system was developed. Using the ANSYS LS-Dyna program, simulations of the longwall shearer’s drive wheel mating with the selected elements of the toothed haulage segment were performed. The purpose of the analyzes was identification of contact stress value of the elements of the feed system as a function of geometrical parameters of various solutions of the toothed bar. The result of the simulation was the selection of the rack solution for further field and industrial tests.
Analysis of magnetic pull effect in disk induction motor with symmetrical/asymmetrical air-gap
Authors: Wolnik T , Będkowski B
Published: December 2019

Disk induction motor presents an interesting alternative to standard machine on account of its limited axial dimension. Its application may be contemplated for mine industry machines. However, in case of the design presented in this paper, a most significant drawback lies in magnetic pull axial forces appearing during normal operation of the machine and affecting bearing performance. This is why such forces should be considered at the design stage; this is particularly true, when design of magnetic circuit does not counterbalance those forces. The issue of magnetic pull occurring in disk induction motor with a single air-gap is presented in the paper for both symmetrical and asymmetrical air-gap. Results of calculations and measurements of axial forces under differing operating conditions of the motor are demonstrated. Particular attention is paid to analysis of axial force waveforms and their variations for different motor operating conditions.
Analysis of the process of loosening the rocks with different strength properties using the undercutting bolts
Authors: Siegmund M , Jonak J
Published: December 2019

The process and the test results of the solid rock loosening by use of the fixed undercutting bolt are described. The tests were carried out within the RODEST project, OPUS 10 competition No. 2015/19/B/ST10/02817, financed by the National Science Centre, where a series of numerical modelling as well as laboratory and in-situ tests were planned. The test stand equipment as well as methodology for conducting the in-situ tests are presented. The tests were conducted in four mines. In each mine tens of solid rock loosening tests were conducted, during which the process parameters were recorded. Additionally, the loosened area outline in each successful test was recreated using 3D scanner. Data collected during in-situ tests as well as strength properties of the tested rocks enabled analysing the loosening process (forces, ranges) in relation to the rock type.
The method of determining the optimal life cycle of the mining machine
Authors: Kowalski A , Blichtarski M
Published: December 2019

One of the significant components of production costs are the purchase and operating costs of machinery and equipment; according to Sandvik Coromant, they can account for approx. 30% of manufacturing costs. In the mining industry, the share of purchase and operation costs of machinery and equipment in the mining cost is certainly even greater. Such a large share of machine and tooling costs in manufacturing costs determines the significance of the issue of minimizing these costs, which is connected with the problem of determining the moment when further operation of a worn machine becomes unprofitable. One of the currently available ways to determine the length of the operation lifecycle is to register and compare the total costs of machine maintenance and its annual maintenance costs. This method is easy to apply, unfortunately it is not possible to use it at the machine purchase planning stage and thus it does not allow for prior determination of a viable life cycle length. The aim of the article is to propose a method for determining a profitable life cycle of a mining machine, taking into account the economic factors of macroenvironment. The costs related to operation, including failure costs, were also considered. Determining the duration of the operation cycle is based on determining the payback time of investment for the purchase of a new machine or on minimizing the average cost of monthly use and purchase of the machine in several operating cycles for a longer period of operation. The differences in operating costs between used and new machines are taken into account in calculating the payback period. Sample calculations were carried out using the example of the self-propelled Getman S330 scaler.
Mindfulness Versus Distraction to Improve Affective Response and Promote Cardiovascular Exercise Behavior
Authors: Gillman Arielle S , Bryan Angela D
Published: December 2019

Background

Variation in affective response to exercise partially explains high levels of inactivity. Examining ways to improve affective responses to physical activity is, therefore, an important direction for research aiming to promote exercise behavior.

Purpose

This study compares three strategies: mindfulness, distraction, and an associative focus comparison group as potential strategies to improve affective response to exercise and promote exercise behavior.

Methods

Seventy-eight insufficiently active individuals (M age 26.82, 74% female) were randomly assigned to one of the following three conditions: (a) mindfulness, (b) distraction, or (c) associative attentional focus. The study was divided into two phases, a laboratory session in which participants learned their assigned strategy and completed a 30 min supervised exercise bout and an at-home intervention in which participants used their assigned strategy while exercising on their own for 2 weeks and filled out daily surveys.

Results

Seventy-five participants completed the study. The central hypotheses were partially supported. Participants in the mindfulness and distraction conditions maintained more positive affective response to exercise over time compared to participants in the associative focus condition, whose affect became less positive over time (p = .04). Participants in the distraction condition experienced lower perceived exertion during exercise (p = .01). There were no condition differences in self-reported minutes exercised during follow-up, but participants in the mindfulness condition reported exercising for more days during the follow-up compared to the associative focus condition (p = .01).

Conclusions

These findings suggest individuals wishing to increase their cardiovascular exercise could engage in mindfulness or distraction in order to make exercise feel less difficult and/or more affectively pleasant.
Using Evidence Factors to Clarify Exposure Biomarkers
Authors: Karmakar Bikram , Small Dylan S , Rosenbaum Paul R
Published: December 2019

A study has 2 evidence factors if it permits 2 statistically independent inferences about 1 treatment effect such that each factor is immune to some bias that would invalidate the other factor. Because the 2 factors are statistically independent, the evidence they provide can be combined using methods associated with meta-analysis for independent studies, despite using the same data twice in different ways. We illustrate evidence factors, applying them in a new way in investigations that have both an exposure biomarker and a coarse external measure of exposure to a treatment. To illustrate, we consider the possible effects of cigarette smoking on homocysteine levels, with self-reported smoking and a cotinine biomarker. We examine joint sensitivity of 2 factors to bias from confounding, a central aspect of any observational study.
Efficacy of JAK inhibitors in Ulcerative Colitis
Authors: Ferrante Marc , Sabino João
Published: December 2019

Janus kinase [JAK] inhibitors are a completely novel therapy for the treatment of patients with immune-mediated inflammatory disorders. The oral formulation of tofacitinib has recently been approved for the treatment of moderate-to-severe ulcerative colitis. In the placebo-controlled OCTAVE programme, tofacitinib proved to be efficacious for both inducing and maintaining clinical remission, and this both in anti-tumour necrosis factor-naïve and exposed patients. Several other anti-JAK inhibitors are currently explored. This review summarises the available efficacy data from all anti-JAK inhibitors in ulcerative colitis.
Partial identification in nonseparable count data instrumental variable
models
Authors: Kim Dongwoo
Published: December 2019

This paper investigates undesirable limitations of widely used count data instrumental variable models. To overcome the limitations, I propose a partially identifying single-equation model that requires neither strong separability of unobserved heterogeneity nor a triangular system. Sharp bounds (identified sets) of structural features are characterised by conditional moment inequalities. Numerical examples show that the size of an identified set can be very small when the support of an outcome is rich or instruments are strong. An algorithm for estimation and inference is presented. I illustrate the usefulness of the proposed model in an empirical application to effects of supplemental insurance on healthcare utilisation.
Developing Traps for the Spotted Lanternfly, Lycorma delicatula (Hemiptera: Fulgoridae)
Authors: Francese Joseph A , Cooperband Miriam F , Murman Kelly M , Cannon Stefani L , Booth Everett G , Devine Sarah M , Wallace Matthew S
Published: December 2019

The spotted lanternfly, Lycorma delicatula (White), an invasive, phloem-feeding fulgorid generalist, was recently discovered in the United States. Current trapping methods include placing glue-covered sticky bands around trunks of host trees to exploit the lanternfly’s behavior of climbing up tree trunks. These bands are messy and need to be replaced often as they become covered in both target and nontarget insects and debris. Fourth instar nymphs and adults have also shown an ability to escape from traditional tree bands or avoid capture. A promising commercially available tree band (BugBarrier) design that faces inward to the trunk and targets larger developmental stages was tested. A modified pecan weevil trap (circle trunk trap) was also compared with tree bands. This design does not require the use of insect-trapping adhesive. Circle trunk traps caught more third and fourth instar and adult L. delicatula than BugBarrier bands. Flight intercept traps caught fewer adult L. delicatula than trunk-based tree bands. In a separate comparison, more spotted lanternflies were caught on adhesive-coated ‘tree mimicking’ traps placed along the edges of Ailanthus altissima Swingle (Sapindales: Simaroubaceae) stands than away from hosts in an open field. Circle trunk traps are recommended for their effectiveness at capturing L. delicatula as well as their relative ease-of-use and reusability.