We consider scenarios with distributed decision processes, e.g., coupled majorities and personal union in parliament chambers, supranational decisions and supervisory boards. When computing the adoption rate for reaching a decision in these scenarios, multiple linear inequality restrictions in combinatorial countings are present. These rates cannot be computed in closed form. We introduce a general method for incorporating multiple inequality conditions in multiple majority decisions, which significantly reduces the number of involved summations and removes restrictions on the summation indices. Exact solutions (...) are provided through integral representations which can be evaluated numerically, and unrestricted, contracted sums over discrete events. Further, we provide methods to reduce the number of necessary summations by splitting or recurring the original problem to easier sub-problems. For five dedicated scenarios, full results are given which indeed require a single unrestricted summation only. (shrink)

Ockham’s razor is the principle that, all other things being equal, scientists ought to prefer simpler theories. In recent years, philosophers have argued that simpler theories make better predictions, possess theoretical virtues like explanatory power, and have other pragmatic virtues like computational tractability. However, such arguments fail to explain how and why a preference for simplicity can help one find true theories in scientific inquiry, unless one already assumes that the truth is simple. One new solution to that problem is (...) the Ockham efficiency theorem, which states that scientists who heed Ockham’s razor retract their opinions less often and sooner than do their non-Ockham competitors. The theorem neglects, however, to consider competitors following random strategies and in many applications random strategies are known to achieve better worst-case loss than deterministic strategies. In this paper, we describe two ways to extend the result to a very general class of random, empirical strategies. The first extension concerns expected retractions, retraction times, and errors and the second extension concerns retractions in chance, times of retractions in chance, and chances of errors. (shrink)

El desarrollo de la actividad de estudio a partir de niveles de eficiencia cada vez mayores constituye un requisito indispensable para el tránsito de los estudiantes por la Educación Superior. De igual forma representa un reto para los docentes en el diseño del proceso enseñanza- aprendizaje. En este empeño es necesario prestar atención a los métodos, procedimientos y estrategias que permitan al estudiante la adopción de una posición reflexiva e independiente en la búsqueda del conocimiento, su actualización y aplicación en (...) la diversidad de tareas de estudio que como parte de su formación integral deben realizar. En ello resulta importante el análisis de las vías que favorecen un mejor funcionamiento de la memoria como proceso cognoscitivo fundamental. El presente artículo ofrece elementos teóricos y metodológicos esenciales que pueden servir de guía a docentes y estudiantes en la regulación y autorregulación de los procesos mnémicos desde la perspectiva del estudio eficiente, aspectos que no siempre son valorados en correspondencia con los aportes teóricos existentes. The development of the studying activity, based on ever growing efficiency levels, constitutes an indispensable requirement for the students' passing through higher education. Likewise, this fact represents a challenge for the professors to teach the students how to study. In doing so, it is necessary to pay attention to methods, procedures and strategies that allow the students to take a reflexive and independent position while searching for knowledge, its updating and application in the diversity of studying tasks which as a part of its integral formation the students have to accomplish. It is of uppermost importance the analysis of the ways that favor a better functioning of memory as a fundamental cognitive process. This article offers essential theoretical and methodological elements which may be guidelines to professors and students for regulating and self- regulating the memory processes from an efficient study perspective, which are not always valued in correspondence to the existing theoretical outcomes on the field. (shrink)

In coal mining technology systems, it is very important to acquire, store, and represent basic geological data comprehensively and accurately. Based on the current working mode and information level in mining geology at coal mines, this paper proposes a process of building basic geological database for modeling of coal mines by using existing results’ data of mining geology and develops the efficient program for getting the basic geological data from the important 2D plane drawings’ achievement at mines, such as (...) the contour maps of mine coal seam floors, geological cross-sections, underground drilling results, and geological survey results, based on AutoLISP, which is a programming language for the secondary development of AutoCAD. The obtained data in general text format is stored and managed by the MongoDB database, which realizes the storage, query, analysis, and correction of massive data of geological objects in the space of the underground coalmine. The application results show that compared with the previous data acquisition methods such as manual input and graphic transformation attribute, the extraction of spatial and attribute data from the existing mine 2D plane drawings by programming can effectively avoid the prominent problems such as artificial gross error, distortion of graph conversion, and different database structure, make the obtained spatial geological data more comprehensive, accurate, and effective, and, meanwhile, increase the rate by more than 60%, which plays an important role in data support for the construction of the geological modeling systems for transparent mines. (shrink)

In an era characterized by fast technological progress that introduces new unpredictable scenarios every day, working in the law field may appear very difficult, if not supported by the right tools. In this respect, some systems based on Artificial Intelligence methods have been proposed in the literature, to support several tasks in the legal sector. Following this line of research, in this paper we propose a novel method, called PRILJ, that identifies paragraph regularities in legal case judgments, to support (...) legal experts during the redaction of legal documents. Methodologically, PRILJ adopts a two-step approach that first groups documents into clusters, according to their semantic content, and then identifies regularities in the paragraphs for each cluster. Embedding-based methods are adopted to properly represent documents and paragraphs into a semantic numerical feature space, and an Approximated Nearest Neighbor Search method is adopted to efficiently retrieve the most similar paragraphs with respect to the paragraphs of a document under preparation. Our extensive experimental evaluation, performed on a real-world dataset provided by EUR-Lex, proves the effectiveness and the efficiency of the proposed method. In particular, its ability of modeling different topics of legal documents, as well as of capturing the semantics of the textual content, appear very beneficial for the considered task, and make PRILJ very robust to the possible presence of noise in the data. (shrink)

With the rapid and unbalanced development of industry, a large amount of cultivated land is converted into industrial land with lower efficiency. The existing research is extensively concerned with industrial land use and industrial development in isolation, but little attention has been paid to the relationship between them. To help address this gap, the paper creates a new efficiency measure method for industrial land use combining Subvector Data Envelope Analysis with spatial analysis approach. The proposed model has been verified by (...) using the industrial land use data of 30 Chinese provinces from 2001 to 2013. The spatial autocorrelation relationship between industrial development and industrial land use efficiency is explored. Furthermore, this paper examines the effects of industrial development on industrial land use efficiency by spatial panel data model. The results indicate that the industrial land use efficiency and the industrial development level in the provinces of eastern region are higher than those of the western region. The spatial distribution of industrial land use efficiency shows remarkable positive spatial autocorrelation. However, the level of industrial development has obvious negative spatial autocorrelation since 2009. The improvement of industrial development has a significant positive impact on the industrial land use efficiency. (shrink)

This study aims to examine the main determinants of efficiency of both conventional and Islamic Saudi banks and then choose the best fit model among machine learning prediction models, Chi-squared automatic interaction detector, linear regression, and neural network ). The data were collected from the annual financial reports of Saudi banks from 2014 to 2018. The Saudi banking sector consists of 11 banks, 4 of which are Islamic. In this study, the major financial ratios are subgrouped into the profitability ratios, (...) managerial practices, asset and loans, capital adequacy ratios, and liquidity. First, regression analysis is implemented with efficiency ratio as a dependent variable and the proxies of banks’ profitability, liquidity, asset quality, management ratios, and capital adequacy ratios as independent variables. Next, the feature selection is applied for different prediction models. Subsequently, 4 prediction models were developed to choose the best fit. The performance metrics have also been evaluated. Regression results exhibit that the efficiency of both conventional and Islamic banks is highly affected by profitability, liquidity, and managerial practices. Finally, we choose the best prediction model with the highest R2 in the training and the testing phases with/out feature selection that is the CHAID model. The best predictors of cost efficiency for Saudi banks are the capital ratios, namely, CAR total and CAR tier 1. Findings are theoretically and practically important to academics, investors, and policymakers. Policymakers can benefit from the novelty of this study in building an early warning system using the CHAID model to predict different financial distress scenarios. (shrink)

We contend that if efficiency and reliability are important factors in neural information processing then distributed, not localist, representations are “evolution's best bet.” We note that distributed codes are the most efficient method for representing information, and that this efficiency minimizes metabolic costs, providing adaptive advantage to an organism.

Rheumatoid arthritis is a progressive systemic autoimmune disease characterized by inflammation of the joints and surrounding tissues, which seriously affects the life of patients. The Sharp/van der Heijde method has been widely used in clinical evaluation for the RA disease. However, this manual method is time-consuming and laborious. Even if two radiologists evaluate a specific location, their subjective evaluation may lead to low inter-rater reliability. Here, we developed an efficient model powered by deep convolutional neural networks to solve these (...) problems and automated the overall scoring on hand X-rays. The depthwise separable convolution technique is used based on ResNet-50 due to the high resolution of hand X-rays. An inverted residual block is introduced to devise a ResNet-Dwise50 model to enhance the efficiency of the model. The model was trained and tested using bilateral posteroanterior images of 3818 patients. The experiment results show the ResNet-Dwise50 model achieved an MAE of 14.90 and RMSE of 22.01 while ensuring high efficiency. There was no statistical difference between the average scores given by two experienced radiologists and predicted scores from our model. (shrink)

This study employs the Porter hypothesis framework to test the moderating role of production cost in the relationship between resource-efficiency actions and financial performance for German small and medium-sized enterprises (SMEs). For this purpose, we employ the 2012, 2018, and 2021 Flash Eurobarometer surveys to analyze how consistently SMEs adopt resource-efficiency actions, and the impact of these actions on their performance and costs. We also conduct a generalized method of moments regression analysis (GMM). Among the seven resource-efficiency actions proposed, saving (...) water had a significant positive (negative) influence on financial performance in 2012, 2021, and (2018). Saving energy and using renewable energy had a positive and significant (insignificant) effect on financial performance in 2018, 2021, and (2012). Finally, selling scrap material to other companies had a positive and significant impact in all years. Furthermore, increased production costs negatively moderate the relationship between eco-efficiency action scores and financial performance. The results indicate that the “strong” version of the Porter hypothesis is not supported: It only holds when the implementation of eco-efficiency actions reduces production costs and increases financial performance. (shrink)

To improve the problems of inconvenient communication in the manufacturing industry, the ineffective use of resources, and the inability to efficiently complete manufacturing tasks, resource sharing has become an important model to promote the transformation and upgrading of the manufacturing industry. We used multiagent modeling to construct a resource-sharing model and take Baosteel as the micro background and the manufacturing industry as the macro background. Under this model, we discovered the effect of resource sharing on the efficiency of intelligent manufacturing (...) under network collaboration through system dynamics research. We built and simulated a dynamic model of system dynamics that couples the two backgrounds and have given policy suggestions according to the simulation result. (shrink)

Alasdair MacIntyre described the late modern West as driven by two moral values: efficiency and effectiveness. Regardless of whether you accept MacIntyre's overarching story, it seems clear that efficiency and effectiveness have achieved a zenith in institutional health care structures, such that these two aspects of care become the final arbiters of what counts as “good” care. At the very least, they are dominant in many clinical contexts and act as the interpretative lens for the judgments of successful health care (...) managers. The drive of efficiency can also be seen in “lean” management methods (originally imported from the automotive manufacturing industry) increasingly deployed in the intensive care unit. This drive gives us pause. The high stress of the ICU is exacerbated by the enormous complexity of technological interventions designed to maintain physiological functioning as the body heals, as well as the ever‐present concerns related to cost, effectiveness, and efficiency. The ICU, therefore, provides an illustrative view of the challenges facing clinicians, as well as resource managers, in terms of delivering care. In short, the goal of technocratic efficiency often ends up at odds with humane purposes. To better understand these contemporary health care dynamics, we conducted a limited series of focus group discussions and interviews with residents experienced in the challenges of delivering care in the ICU environment. In what follows, we highlight some narrative observations drawn from these focus groups. We found a recurrent and disconcerting refrain among our informants that has not been adequately described or addressed in the literature: technocratic management techniques have crept into and bifurcated clinical care strategies in the ICU. Specifically, we highlight the influence of concerns around efficiency and effectiveness and the ways in which these foci have contributed to a bifurcation in care in the ICU along two trajectories: either compassionate care or curative care. (shrink)

Benchmarking is the major reason for the widespread use of DEA models for efficiency analysis. Determining the closest targets for DMUs, DEA models play a key role in benchmarking their best performance. In fact, these models help develop certain performance enhancement plans that need fewer attempts made by DMUs. Therefore, this study proposes a novel method based on the network DEA to determine the most appropriate target for every stage in addition to benchmarking the DMUs. The proposed model differs from (...) those proposed by other studies in the fact that all DEA models of benchmarking consider input and output values to be linear. However, in real-world problems, many DMU inputs and outputs have nonlinear values, something which was taken into account in the modeling process in this study. The proposed model was employed to benchmark cement factories listed on the Tehran Stock Exchange. (shrink)

We propose an approach for texture segmentation based on weak supervised learning. The weak supervision implies that the user marks only a single small patch for each class in the input image. These patches are used for training. We employ the method of graph cuts for the segmentation task. Our work demonstrates that even under such weak training, texture segmentation can be achieved efficiently and with good accuracy via graph cuts. Moreover, our approach uses a simpler feature representation than that (...) in similar contemporary segmentation approaches. We also provide a brief discussion indicating the good performance of our approach. We validate our method on various standard texture mosaics and also on segmentation of natural images with large texture variations. (shrink)

In order to deal with high-dimensional distributed data, this article develops a novel and communication-efficient approach for sparse and high-dimensional data with the penalized quantile regression. In each round, the proposed method only requires the master machine to deal with a sparse penalized quantile regression which could be realized fastly by proximal alternating direction method of multipliers algorithm and the other worker machines to compute the subgradient on local data. The advantage of the proximal ADMM algorithm is that it (...) could make every parameter of iteration to have closed formula even in high-dimensional case, which greatly improves the speed of calculation. As for the communication efficiency, the proposed method does not sacrifice any statistical accuracy and provably improves the estimation error obtained by centralized method, provided the penalty levels are chosen properly. Moreover, the asymptotic properties of the proposed estimation and the convergence of the algorithm are convincible. Especially, it presents extensive experiments on both the numerical simulations and the HIV drug resistance data analysis, which all confirm the significant efficiency of our proposed method in quantile regression for distributed data by comparative and empirical analysis. (shrink)

Brain–machine interfaces are systems that allow the control of a device such as a robot arm through a person’s brain activity; such devices can be used by disabled persons to enhance their life and improve their independence. This paper is an extended version of a work that aims at discriminating between left and right imagined hand movements using a support vector machine classifier to control a robot arm in order to help a person to find an object in the environment. (...) The main focus here is to search for the best features that describe efficiently the electroencephalogram data during such imagined gestures by comparing two feature extraction methods, namely the continuous wavelet transform and the empirical modal decomposition, combined with the principal component analysis that were fed through a linear and radial basis function kernel SVM classifier. The experimental results showed high performance achieving an average accuracy across all the subjects of 92.75% with an RBF kernel SVM classifier using CWT and PCA compared to 80.25% accuracy obtained with EMD and PCA. The proposed system has been implemented and tested using data collected from five male subjects and it enabled the control of the robot arm in the right and the left direction. (shrink)

The constraint-handling methods using multiobjective techniques in evolutionary algorithms have drawn increasing attention from researchers. This paper proposes an efficient conical area differential evolution algorithm, which employs biased decomposition and dual populations for constrained optimization by borrowing the idea of cone decomposition for multiobjective optimization. In this approach, a conical subpopulation and a feasible subpopulation are designed to search for the global feasible optimum, along the Pareto front and the feasible segment, respectively, in a cooperative way. In particular, (...) the conical subpopulation aims to efficiently construct and utilize the Pareto front through a biased cone decomposition strategy and conical area indicator. Neighbors in the conical subpopulation are fully exploited to assist each other to find the global feasible optimum. Afterwards, the feasible subpopulation is ranked and updated according to a tolerance-based rule to heighten its diversity in the early stage of evolution. Experimental results on 24 benchmark test cases reveal that CADE is capable of resolving the constrained optimization problems more efficiently as well as producing solutions that are significantly competitive with other popular approaches. (shrink)

Day-to-day lives are affected globally by the epidemic coronavirus 2019. With an increasing number of positive cases, India has now become a highly affected country. Chronic diseases affect individuals with no time identification and impose a huge disease burden on society. In this article, an Efficient Recurrent Neural Network with Ensemble Classifier is built using VGG-16 and Alexnet with weighted model to predict disease and its level. The dataset is partitioned randomly into small subsets by utilizing mean-based splitting method. (...) Various models of classifier create a homogeneous ensemble by utilizing an accuracy-based weighted aging classifier ensemble, which is a weighted model’s modification. Two state of art methods such as Graph Sequence Recurrent Neural Network and Hybrid Rough-Block-Based Neural Network are used for comparison with respect to some parameters such as accuracy, precision, recall, f1-score, and relative absolute error. As a result, it is found that the proposed ERNN-EC method accomplishes accuracy of 95.2%, precision of 91%, recall of 85%, F1-score of 83.4%, and RAE of 41.6%. (shrink)

Religious education and religious services practices that emerged as spiritual/religious support and guidance in the context of social work in Turkey are carried out with the protocols between Presidency of Religious Affairs ( DIB) and Ministry of Health, Justice, Ministry Family and Social Services, Youth and Sports, Disaster and Emergency Management Presidency. This research is on the self-efficacy perceptions of religious officials assigned in various social work areas of the Ministry of Family and Social Services. Researching the self-efficacy perceptions of (...) religious officials is important in terms of revealing that it is necessary to work in a wide area from making identifications about their professional development to developing religious education and services training programs that will meet the needs of the target group. Qualitative research method has been used in this study. The research has been structured within the framework of interviews with religious officials assigned to provide religious education and service in the service areas of the Ministry of Family and Social Services in Kırıkkale province. The data obtained from religious officials working in the field with semi-structured interview questions are evaluated in two themes: The self-efficacy perceptions of officials and needs of the target audience. The main conclusion reached in this study is as follows: Needs- based and value-based training programs can be developed for religious workers in social service institutions. (shrink)

Workplace inspections are undertaken because they are believed to lead to better conditions In the workplace. It is therefore essential to know if inspections have the desired effects on working conditions. We introduce a theoretical framework for the evaluation of workplace inspections with respect to their effects on working conditions. Criteria of efficiency and priority-setting are discussed. Some empirical results concerning priority-setting in Swedish inspection agencies are presented. Further, we argue that in order to obtain reliable information about the effects (...) of different inspection methods, it is necessary to perform controlled comparative studies in which different methods are used in different workplaces. Given the facility with which such studies can be performed, it is surprising how few such studies have been made. We conclude by surveying some empirical studies that concern the issue of efficient inspections. (shrink)

In recent years, a multitude of datasets of human–human conversations has been released for the main purpose of training conversational agents based on data‐hungry artificial neural networks. In this paper, we argue that datasets of this sort represent a useful and underexplored source to validate, complement, and enhance cognitive studies on human behavior and language use. We present a method that leverages the recent development of powerful computational models to obtain the fine‐grained annotation required to apply metrics and techniques from (...) Cognitive Science to large datasets. Previous work in Cognitive Science has investigated the question‐asking strategies of human participants by employing different variants of the so‐called 20‐question‐game setting and proposing several evaluation methods. In our work, we focus on GuessWhat, a task proposed within the Computer Vision and Natural Language Processing communities that is similar in structure to the 20‐question‐game setting. Crucially, the GuessWhat dataset contains tens of thousands of dialogues based on real‐world images, making it a suitable setting to investigate the question‐asking strategies of human players on a large scale and in a natural setting. Our results demonstrate the effectiveness of computational tools to automatically code how the hypothesis space changes throughout the dialogue in complex visual scenes. On the one hand, we confirm findings from previous work on smaller and more controlled settings. On the other hand, our analyses allow us to highlight the presence of “uninformative” questions (in terms of Expected Information Gain) at specific rounds of the dialogue. We hypothesize that these questions fulfill pragmatic constraints that are exploited by human players to solve visual tasks in complex scenes successfully. Our work illustrates a method that brings together efforts and findings from different disciplines to gain a better understanding of human question‐asking strategies on large‐scale datasets, while at the same time posing new questions about the development of conversational systems. (shrink)

Chaos distributes with a covert method to condense the dynamic of complexity and satisfies the security requirements of a cryptographic system. This study gives an ability online/offline ID-based short signature scheme using conformable fractional chaotic maps. Furthermore, we establish its security under IBSS existential unforgeability of identity-based short signature under chosen message attack in the random oracle model. Some of the stimulating preparations of obtainable processes are that they give a multiperiod application of the offline storage, which licenses the agent (...) to recycle the offline pre-registered data in time series, rather than one-period usage in all past IBSS processes. (shrink)

Pluralism about scientific method is more-or-less accepted, but the consequences have yet to be drawn out. Scientists adopt different methods in response to different epistemic situations: depending on the system they are interested in, the resources at their disposal, and so forth. If it is right that different methods are appropriate in different situations, then mismatches between methods and situations are possible. This is most likely to occur due to method bias: when we prefer a particular kind (...) of method, despite that method clashing with evidential context or our aims. To explore these ideas, we sketch a kind of method pluralism which turns on two properties of evidence, before using agent-based models to examine the relationship between methods, epistemic situations, and bias. Based on our results, we suggest that although method bias can undermine the efficiency of a scientific community, it can also be productive through preserving a diversity of evidence. We consider circumstances where method bias could be particularly egregious, and those where it is a potential virtue, and argue that consideration of method bias reveals that community standards deserve a central place in the epistemology of science. (shrink)

The importance of the topic of the article lies in the fact that in the era of postmodernism, informatization of the elementary school allows you to improve the quality of the educational process, through the use of information and communication technologies (ICT) to simplify management of the educational process, to organize the exchange of teaching experience, to expand didactic capabilities of the lesson. The purpose of the article is the need to study and justify the importance of using new ICT (...) in primary school lessons, to expand the experience of e-learning in primary school. The article expands the concept of information and communication technologies and their benefits in primary school; given the rationale for conducting a lesson using ICT; the experience of e-learning in the primary school of the postmodern era is characterized. Thus, one of the priorities of the development of education in postmodern society is the professional application in all areas of information technology and e-learning, which can increase the interest of present students and improve the ability to adapt to current electronic information society. The formation of knowledge and skills in the field of computer literacy of teachers and students will be an indicator of compliance of its level with current requirements. (shrink)

The use of multimodal sensors for lane line segmentation has become a growing trend. To achieve robust multimodal fusion, we introduced a new multimodal fusion method and proved its effectiveness in an improved fusion network. Specifically, a multiscale fusion module is proposed to extract effective features from data of different modalities, and a channel attention module is used to adaptively calculate the contribution of the fused feature channels. We verified the effect of multimodal fusion on the KITTI benchmark dataset and (...) A2D2 dataset and proved the effectiveness of the proposed method on the enhanced KITTI dataset. Our method achieves robust lane line segmentation, which is 4.53% higher than the direct fusion on the precision index, and obtains the highest F2 score of 79.72%. We believe that our method introduces an optimization idea of modal data structure level for multimodal fusion. (shrink)

Musical performance is a multimodal experience, for performers and listeners alike. This paper reports on a pilot study which constitutes the first step toward a comprehensive approach to the experience of music as performed. We aim at bridging the gap between qualitative and quantitative approaches, by combining methods for data collection. The purpose is to build a data corpus containing multimodal measures linked to high-level subjective observations. This will allow for a systematic inclusion of the knowledge of music professionals (...) in an analytic framework, which synthesizes methods across established research disciplines. We outline the methods we are currently developing for the creation of a multimodal data corpus dedicated to the analysis and exploration of instrumental music performance from the perspective of embodied music cognition. This will enable the study of the multiple facets of instrumental music performance in great detail, as well as lead to the development of music creation techniques that take advantage of the cross-modal relationships and higher-level qualities emerging from the analysis of this multi-layered, multimodal corpus. The results of the pilot project suggest that qualitative analysis through stimulated recall is an efficient method for generating higher-level understandings of musical performance. Furthermore, the results indicate several directions for further development, regarding observational movement analysis, and computational analysis of coarticulation, chunking, and movement qualities in musical performance. We argue that the development of methods for combining qualitative and quantitative data are required to fully understand expressive musical performance, especially in a broader scenario in which arts, humanities, and science are increasingly entangled. The future work in the project will therefore entail an increasingly multimodal analysis, aiming to become as holistic as is music in performance. (shrink)

Business orientation toward sustainable development goals and the circular economy are relevant research topics today in business theory and practice. The waste recycling sector is a key industry in the circular economy framework for promoting clean production and environmental sustainability. This study analyzes business performance in the recycling sector, focusing on efficiency indicators. The associations between firm efficiency and risk variables were also evaluated. The study goes through several methodological stages, including a Data Envelopment Analysis (DEA) multistage method and multivariate (...) modeling: tobit regression, bootstrap models, and generalized method of moments (GMM). The main results indicate that the average efficiency of waste recycling firms is at a medium level. Large-sized firms achieve higher levels of efficiency than medium-sized and small firms, supporting the economies of scale hypothesis. The evidence also suggests that risk variables (rating score and Zscore) and capital structure are key determinants of firm efficiency in the waste recycling industry. (shrink)

As an important part of Chinese economy, the construction industry has a great contribution to the economy, and plays an important role in the Chinese economic development. Therefore, it has certain research significance for the quality acceptance supervision method of construction engineering. This article takes Shenzhen S project as an example, combined with cloud computing, discusses the quality acceptance and supervision methods of indoor construction projects. In the introduction to the technical part, this article first briefly introduces the definition (...) of cloud computing and then introduces the particle swarm algorithm and traditional genetic algorithm in the cloud computing task scheduling method. The algorithm is introduced into the quality acceptance of indoor construction projects to obtain the quality, most efficient method for acceptance supervision. The experimental part of this article takes S project as the research object and the residents’ satisfaction with the project as the experimental purpose. Finally, through statistical analysis, it is concluded that the residents’ satisfaction with S project reaches more than 70%. (shrink)

Law article prediction is a task of predicting the relevant laws and regulations involved in a case according to the description text of the case, and it has broad application prospects in improving judicial efficiency. In the existing research work, researchers often only consider a single case, employing the neural network method to extract features for prediction, which lack the mining of related and common element information between different data. In order to solve this problem, we propose a law article (...) prediction method that integrates the characteristics of common elements. It can effectively utilize the co-occurrence information of the training data, fully mine the relevant common elements between cases, and fuse local features. Experiments show that our method performs well. (shrink)

Compared the use of unit regression weights with least squared error multiple regression weights. 100 sample correlation matrices computed from randomly drawn samples from a multivariate normal distribution were employed, with the sample size varying from 25-1,000 and number of variables from 2-10. In addition, correlation matrices were also sampled from published data. The results of comparing the efficiency of the 2 methods of weighting are presented for correlation matrices with and without the effect of suppressor variables. Use of (...) these findings is discussed. (shrink)

The economic importance of optimizing the environmental situation from the perspective of an entrepreneur are assessed in the article. The classification of administrative decisions taken in the course of the business activities is proposed. The authors identified a group of solutions directly providing optimization of environment external to the enterprise, solutions that have an indirect positive impact on the environment and solutions that improve ecology of industrial premises. The nature of economic effect of resulting solutions of various types is taken (...) into account. Vectors of influence of working conditions on the economic results of business activities are described. The nature and strength of the impact of model management decisions results of business activities are defined. Key performance indicators of entrepreneurial activity are identified: employee productivity, the amount of revenue and profitability, solvency, staff stability, the competitiveness of enterprises. Grouping the costs of ecological parameters optimization of the production environment is proposed. Relationship between level of working conditions and socio-psychological climate in the collective enterprise is disclosed. The methods of motivation of entrepreneurs in solving of environmental, production problems are considered. The role of training entrepreneurs engaged of medium and small businesses are underlined especially. Thus, in the article the relationship between environmental and economic problems of entrepreneurial activity is investigated. Role and opportunities of entrepreneurs in solving these problems are defined and structured. (shrink)