Data analysis has become most widespread field of research and it has extended in almost every field of study. Considering the recent trends and developments in the field of communication and information technology, there is a scope of combining the monitoring of substation equipment with big data analysis technology. That will result in an improved data analysis ability, information sharing and utilization rate of monitoring data. In the proposed work, the authors have introduced the big data analysis and its corresponding (...) application in the monitoring of substations. Basic concepts and the procedures of the typical data analysis for general problems are also discussed. As a main part of the paper, different types of distributed data analysis techniques have been proposed, in which two relational online analysis, namely Hive and Impala and one H Base multidimensional online analysis are important. These data analysis techniques are proposed considering the analysis efficiency, storage performance from the business development requirements point of view of the substation. The result obtained depicts that the proposed model has an advantage in storage overhead and roll-up performance, when compared with the traditional method, although the data loading speed is approximately 1.7–1.9 times of the traditional model. Some experiments are carried out in order to verify the validity of the model. (shrink)

The purpose of the study is to determine measures to improve the efficiency of the personnel management system in the civil service. The article highlights the issues of improving the personnel management system in the civil service, identifies the features of personnel management in the civil service, touches upon the moments of motivation and incentives for civil servants. The authors carried out a sociological study among the employees of the Ministry of Agriculture and Food of the Republic of Buryatia. (...) Scientific novelty lies in the proposed personnel management system, which, in contrast to the existing ones, reflects the specifics of the civil service and allows the most effective management decisions of personnel management. As a result, measures were identified that are aimed at efficient, fast and convenient work of the Ministry's employees, at retaining young specialists, effective motivation and interest of personnel in labor activities. (shrink)

Algorithmic software for mathematical modeling of structural stability is considered, which is reduced to solving a partial generalized eigenvalues problem of sparse matrices, with automatic parallelization of calculations on modern parallel computers with graphics processors. Peculiarities of realization of parallel algorithms for different structures of sparse matrices are presented. The times of solving the problem of stability of composite materialsusing a three-dimensional model of "finite size fibers" on computers of different architectures are given. In mathematical modeling of physical and technical (...) processes in many cases there is a need to solve problems of algebraic problem of eigenvalues with sparse matrices of large volumes. In particular, such problems arise in the analysis of the strength of structures in civil and industrial construction, aircraft construction, electric welding, etc. The solving to these problems is to determine the eigenvalues and eigenvectors of sparse matrices of different structure. The efficiency of solving these problems largely depends on the effectiveness of mathematical modeling of the problem as a whole. Continuous growth of task parameters, calculation of more complete models of objects and processes on computers require an increase in computer productivity. High-performance computing requirements are far ahead of traditional parallel computing, even with multicore processors. High-performance computing requirements are far ahead of traditional parallel computing, even with multicore processors. Today, this problem is solved by using powerful supercomputers of hybrid architecture, such as computers with multicore processors and graphics processors, which combine MIMD and SIMD architectures. But the potential of high-performance computers can be used to the fullest only with algorithmic software that takes into account both the properties of the task and the features of the hybrid architecture. Complicating the architecture of modern high-performance supercomputers of hybrid architecture, which are actively used for mathematical modeling means a significant complication of efficient use of these resources in creating parallel algorithms and programs. here are problems with the creation of algorithmic software with automatic execution of stages of work, which are associated with the efficient use of computing resources, ways to store and process sparse matrices, analysis of the reliability of computer results. This makes it possible to significantly increase the efficiency of mathematical modeling of practical problems on modern high-performance computers, as well as free users from the problems of parallelization of complex problems. he developed algorithmic software automatically implements all stages of parallel computing and processing of sparse matrices on a hybrid computer. It was used at the Institute of Mechanics named after S.P. Tymoshenko NAS of Ukraine in modeling the strength problems of composite material. A significant improvement in the time characteristics of mathematical modeling was obtained. Problems of mathematical modeling of the properties of composite materials has an important role in designing the processes of deformation and destruction of products in various subject areas. Algorithmic software for mathematical modeling of structural stability is considered, which is reduced to solving a partial generalized problem of eigen values of sparse matrices of different structure of large orders, with automatic parallelization of calculations on modern parallel computers with graphics processors. The main methodological principles and features of implementation of parallel algorithms for different structures of sparse matrices are presented, which ensure effective implementation of multilevel parallelism of a hybrid system and reduce data exchange time during the computational process. As an example of these approaches, a hybrid algorithm of the iteration method in subspace for tape and block-diagonal matrices with a frame for computers of hybrid architecture is given. Peculiarities of data decomposition for matrices of profile structure at realization of parallel algorithms are considered. The proposed approach provides automatic determination of the required topology of the hybrid computer and the optimal amount of resources for the organization of an efficient computational process. The results of testing the developed algorithmic software for problems from the collection of the University of Florida, as well as the times of solving the problem of stability of composite materials using a three-dimensional model of "finite size fibers" on computers of different architectures. The results show a significant improvement in the time characteristics of solving problems. (shrink)

Bergson’s philosophy marked a turning point in Western understanding of time by differentiating quantitative time—apprehended by intelligence—from qualitative time—duration, embedded in consciousne...

Environmentalists can convince others to adopt nature-friendly policies through appeal to commonly-held values. Efficiency and justice are such values in industrial societies, but these values are often considered at odds with each other and with policies that preserve land and reduce pollution. The present paper analyses the notion of efficiency and argues that transportation policies that environmentalists favour – substitution of intercity rail and urban mass transit for most automotive forms of transport – are both efficient and just.

Policy Interaction Graph Analysis is a Host-based Intrusion Detection tool that uses Linux MAC Mandatory access control policy to build the licit information flow graph and uses a detection policy defined by the administrator to extract illicit behaviour from the graph. The main limitation of this tool is the generation of a huge signature base of illicit behaviours; hence, this leads to the use of huge memory space to store it. Our primary goal in this article is to reduce this (...) memory space while keeping the tool’s efficiency in terms of intrusion detection rate and false generated alarms. First, the interactions between the two nodes of the graph were grouped into a single interaction. The notion of equivalence class was used to classify the paths in the graph and was compressed by using a genetic algorithm. Such an approach showed its efficiency compared to the approach proposed by Pierre Clairet, by which the detection rate obtained was 99.9%, and no false-positive with a compression rate of illicit behaviour signature database reached 99.44%. Having these results is one of the critical aspects of realizing successful host-based intrusion detection systems. (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)

The recent Supreme Court decision on several provisions of the Patient Protection and Affordable Care Act provides an opportunity to address two kinds of design flaws in the legislation whose correction would both improve economic efficiency and some important dimensions of equity. The Court's view that the mandate is a tax is consistent with the general economic view that defines a tax as “a compulsory payment for public purposes.” This was the viewpoint I took in my earlier work as (...) well. However, there is considerable difference, disagreement, and ambiguity about the public purpose sought by the ACA payment. The primary purpose of the mandate in my work and in arguments for the mandate in Massachusetts was to try to get as many people as possible to have at least some insurance coverage. A secondary consequence of a mandate is to shore up community rating, although community rating per se does not contribute (and generally is harmful) to the goal of covering a greater proportion of the population. (shrink)

This paper is motivated by the increasing popularity of efficient designs for stated choice experiments. The objective in efficient designs is to create a stated choice experiment that minimizes the standard errors of the estimated parameters. In order to do so, such designs require specifying prior values for the parameters to be estimated. While there is significant literature demonstrating the efficiency improvements of employing efficient designs, the bulk of the literature tests conditions where the priors used to generate the (...) efficient design are assumed to be accurate. However, there is substantially less literature that compares how different design types perform under varying degree of error of the prior. The literature that does exist assumes small fractions are used, which is in contrast to computer-aided surveys that readily allow for large fractions. Further, the results in the literature are abstract in that there is no reference point to provide clear insight on the magnitude of any issue. Our objective is to analyze the robustness of different designs within a typical stated choice experiment context of a trade-off between price and quality. We use as an example transportation mode choice, where the key parameter to estimate is the value of time. Within this context, we test many designs to examine how robust efficient designs are against a misspecification of the prior parameters. The simple mode choice setting allows for insightful visualizations of the designs themselves and also an interpretable reference point for the range in which each design is robust. Not surprisingly, the D-efficient design is most efficient in the region where the true population VOT is near the prior used to generate the design: the prior is $20/h and the efficient range is $10–$30/h. However, the D-efficient design quickly becomes the most inefficient outside of this range, and the estimation significantly degrades above $50/h. The orthogonal and random designs are robust for a much larger range of VOT. The robustness of Bayesian efficient designs varies depending on the variance that the prior assumes. Implementing two-stage designs that first use a small sample to estimate priors are also not robust relative to uninformative designs. Arguably, the random design performs as well as any design, and it will perform even better if data cleaning is done to remove choice tasks where one alternative dominates the other. (shrink)

Almost all representations have both distributed and localist aspects, depending upon what properties of the data are being considered. With noisy data, features represented in a localist way can be detected very efficiently, and in binary representations they can be counted more efficiently than those represented in a distributed way. Brains operate in noisy environments, so the localist representation of behaviourally important events is advantageous, and fits what has been found experimentally. Distributed representations require more neurons to perform as efficiently, (...) but they do have greater versatility. (shrink)

The efficiency of distribution networks is hugely affected by active and reactive power flows in distribution electric power systems. Currently, distributed generators (DGs) of energy are extensively applied to minimize power loss and improve voltage deviancies on power distribution systems. The best position and volume of DGs produce better power outcomes. This work prepares a new hybrid SSA–GWO metaheuristic optimization algorithm that combines the salp swarm algorithm (SSA) and the gray wolf optimizer (GWO) algorithm. The SSA–GWO algorithm ensures generating (...) the best size and site of one and multi-DGs on the radial distribution network to decrease real power losses (RPL) (kW) on lines and resolve voltage deviancies. Our novel algorithm is executed on IEEE 123-bus radial distribution test systems. The results confirm the success of the suggested hybrid SSA–GWO algorithm compared with implementing the SSA and GWO individually. Through the proposed SSA–GWO algorithm, the study decreases the RPL and improves the voltage profile on distribution networks with multiple DGs units. (shrink)

The article highlights the problem of the effectiveness of the learning process in higher education institutions in the post-pandemic. Today there are changes in the labor market, and more and more professions need to be updated. This affects the quality of higher education both in Europe and elsewhere, so many higher educational institutions have appeared, which primarily care about the number of students, and not about quality. In an environment where the pandemic has significantly changed the learning process, it is (...) very important to find new ways to improve its effectiveness. Now there is a transition from an industrial society to a society of obtaining knowledge in conditions of post-pandemic development; This means that there is a transition to mass education, and then to general higher education and the need to train a large number of people with average abilities. In addition, in higher educational institutions, in particular in universities, there are still imperfect academic programs in the basics of science, compiled by teachers with different levels of training in the context of post-pandemic development. (shrink)

As humans, we constantly change our movement strategies to adapt to changes in physical functions and the external environment. We have to walk very slowly in situations with a high risk of falling, such as walking on slippery ice, carrying an overflowing cup of water, or muscle weakness owing to aging or motor deficit. However, previous studies have shown that a normal gait pattern at low speeds results in reduced efficiency and stability in comparison with those at a normal (...) speed. Another possible strategy is to change the gait pattern from normal to step-to gait, in which the other foot is aligned with the first swing foot. However, the efficiency and stability of the step-to gait pattern at low speeds have not been investigated yet. Therefore, in this study, we compared the efficiency and stability of the normal and step-to gait patterns at intermediate, low, and very low speeds. Eleven healthy participants were asked to walk with a normal gait and step-to gait on a treadmill at five different speeds, ranging from very low to normal walking speed. The efficiency parameters and stability parameters were analyzed from the motion capture data and then compared for the two gait patterns. The results suggested that step-to gait had a more efficient gait pattern at very low speeds of 10–30 m/min, with a larger percent recovery, and was more stable at 10–60 m/min in comparison with a normal gait. However, the efficiency of the normal gait was better than that of the step-to gait pattern at 60 m/min. Therefore, step-to gait is effective in improving gait efficiency and stability when faced with situations that force us to walk slowly or hinder quick walking because of muscle weakness owing to aging or motor deficit along with a high risk of falling. (shrink)

The energy sector contributes approximately two-thirds of global greenhouse gas emissions. In this context, the sector must adapt to new supply and demand networks for all future energy sources. The ongoing transformation in the European energy field is driven by the ambition of the European Union to reach the climate objectives set for 2030. The main actions are increasing renewable energy production, adapting transition fuels like natural gas to reduce emissions, improving energy efficiency across all economic sectors, prioritizing building, (...) transportation, and industry, developing Carbon Capture and Storage technologies, and ensuring universal access to clean and affordable energy. The significant changes envisaged in the energy sector to increase renewable energy production and consumption require improved integration and more use of predictive tools to support stakeholders' decision-making processes. This article presents a case study to assess the performance of predictive models based on a Feed-Forward Neural Network architecture that employ Root Mean Squared Propagation as their optimization function in terms of choosing the most appropriate activation function for this kind of data input and output. The training and testing phases of the models use data about building energy consumption. The lowest training time and Root Mean Square Error values were similar for Rectified Linear Unit and Tanh activation functions. The model with the Rectified linear Unit activation function performed best. (shrink)

One of the most active areas of research in semi-supervised learning has been to study methods for constructing good ensembles of classifiers. Ensemble systems are techniques that create multiple models and then combine them to produce improved results. These systems usually produce more accurate solutions than a single model would. Specially, multi-view ensemble systems improve the accuracy of text classification because they optimize the functions to exploit different views of the same input data. However, despite being more promising than the (...) single-view approaches, document datasets often have no natural multiple views available. This study proposes an algorithm to generate a synthetic view from a standard text dataset. The model generates a new view from the standard bag-of-words approach using an algorithm based on hidden Markov models. To show the effectiveness of the proposed HMM-based synthetic view generation method, it has been integrated in a co-training ensemble system and tested with four text corpora: Reuters, 20 Newsgroup, TREC Genomics and OHSUMED. The results obtained are promising, showing a significant increase in the efficiency of the ensemble system compared to a single-view approach. (shrink)

Heterogeneous information networks can naturally simulate complex objects, and they can enrich recommendation systems according to the connections between different types of objects. At present, a large number of recommendation algorithms based on heterogeneous information networks have been proposed. However, the existing algorithms cannot extract and combine the structural features in heterogeneous information networks. Therefore, this paper proposes an efficient recommendation algorithm based on heterogeneous information network, which uses the characteristics of graph convolution neural network to automatically learn node information (...) to extract heterogeneous information and avoid errors caused by the manual search for metapaths. Furthermore, by fully considering the scoring relationship between nodes, a calculation strategy combining heterogeneous information and a scoring information fusion strategy is proposed to solve the scoring between nodes, which makes the prediction scoring more accurate. Finally, by updating the nodes, the training scale is reduced, and the calculation efficiency is improved. The study conducted a large number of experiments on three real data sets with millions of edges. The results of the experiments show that compared with PMF, SemRec, and other algorithms, the proposed algorithm improves the recommendation accuracy MAE by approximately 3% and the RMSE by approximately 8% and reduces the time consumption significantly. (shrink)

Of all the different types of public buildings, hospitals are the biggest energy consumers. Cooling systems for air conditioning and healthcare uses are particularly energy intensive. Forecasting hospital thermal-cooling demand is a remarkable and innovative method capable of improving the overall energy efficiency of an entire cooling system. Predictive models allow users to forecast the activity of water-cooled generators and adapt power generation to the real demand expected for the day ahead, while avoiding inefficient subcooling. In addition, the maintenance (...) costs related to unnecessary starts and stops and power-generator breakdowns occurring over the long term can be reduced. This study is based on the operations of a real hospital facility and details the steps taken to develop an optimal and efficient model based on a genetic methodology that searches for low-complexity models through feature selection, parameter tuning and parsimonious model selection. The methodology, called GAparsimony, has been tested with neural networks, support vector machines and gradient boosting techniques. Finally, a weighted combination of the three best models was created. The new operational method employed herein can be replicated in similar buildings with similar water-cooled generators. (shrink)

Categorical loudness scaling (CLS) measures provide useful information about an individual’s loudness perception across the dynamic range of hearing. A probability model of CLS categories has previously been described as a multi-category psychometric function (MCPF). In the study, a representative “catalog” of potential listener MCPFs was used in conjunction with maximum-likelihood estimation to derive CLS functions for participants with normal hearing and with hearing loss. The approach of estimating MCPFs for each listener has the potential to improve the accuracy of (...) the CLS measurements, particularly when a relatively low number of data points are available. The present study extends the MCPF approach by using Bayesian inference to select stimulus parameters that are predicted to yield maximum expected information (MEI) during data collection. The accuracy and reliability of the MCPF-MEI approach were compared to the standardized CLS measurement procedure (ISO16832:2006). A non-adaptive, fixed-level, paradigm served as a “gold-standard” for this comparison. The test time required to obtain measurements in the standard procedure is a major barrier to its clinical uptake. Test time was reduced from approximately 15 minutes to approximately 3 minutes with the MEI-adaptive procedure. Results indicated that the test-retest reliability and accuracy of the MCPF-MEI adaptive procedures were similar to the standardized CLS procedure. Computer simulations suggest that the reliability and accuracy of the MEI procedure were limited by intrinsic uncertainty of the listeners represented in the MCPF catalog. In other words, the MCPF provided insufficient predictive power to significantly improve adaptive-tracking efficiency under practical conditions. Concurrent optimization of both the MCPF catalog and the MEI-adaptive procedure have the potential to produce better results. Regardless of the adaptive-tracking method used in the CLS procedure, the MCPF catalog remains clinically useful for enabling maximum-likelihood determination of loudness categories. (shrink)

Pluripotency can be considered a functional characteristic of pluripotent stem cells (PSCs) populations and their niches, rather than a property of individual cells. In this view, individual cells within the population independently adopt a variety of different expression states, maintained by different signaling, transcriptional, and epigenetics regulatory networks. In this review, we propose that generation of integrative network models from single cell data will be essential for getting a better understanding of the regulation of self‐renewal and differentiation. In particular, we (...) suggest that the identification of network stability determinants in these integrative models will provide important insights into the mechanisms mediating the transduction of signals from the niche, and how these signals can trigger differentiation. In this regard, the differential use of these stability determinants in subpopulation‐specific regulatory networks would mediate differentiation into different cell fates. We suggest that this approach could offer a promising avenue for the development of novel strategies for increasing the efficiency and fidelity of differentiation, which could have a strong impact on regenerative medicine. (shrink)

European firms are currently in a process of transition toward a circular economy, which is expected to guarantee sustainable growth over time. Developing eco-efficient practices is a necessary step in this transition. This study analyzes the impact of stakeholder engagement in a circular business ecosystem on the development of these circular eco-efficient practices. Past literature has evidenced the impact of stakeholder environmental pressure on firm strategic decisions and outcomes. We adopt the stakeholder theory from a more recent vision, arguing that (...) “shaking stakeholders up” within a circular ecosystem is a more advanced strategy than the traditional approach of reacting to stakeholder pressure. Using structural equation modeling, we examine the data of 14,726 European firms and their relationships with five primary stakeholder groups. The results offer theoretical and empirical support for the idea that firms can go further in adopting eco-efficient circular practices by shaking stakeholders up, selecting them, and managing relationships with them. (shrink)

The present study examined the effects of transcranial direct current stimulation using Halo Sport on the time to exhaustion in relation with muscle activities and corticomuscular coupling of agonist and antagonist muscles during a sustained isometric fatiguing contraction performed with the elbow flexors. Twenty healthy male college students were randomly assigned to tDCS group and control group. The two group participants performed two experimental sessions which consisted of pre-fatigue isometric maximal voluntary contraction, sustained submaximal voluntary contractions performed to exhaustion, and (...) post-fatigue MVC with the right elbow flexor muscles. Sham stimulation and tDCS were applied for control and tDCS group participants 20 min prior to the second session test, respectively. MVC strength in pre- and post-fatigue test, TTE, electroencephalogram, and electromyography of biceps brachii and triceps brachii were recorded during the tests. It was found that tDCS using the Halo Sport device significantly increased TTE and thus improved muscular endurance performance. The improvement may be partly related to the improvement of neuromuscular efficiency as reflected by decrease of antagonistic muscle coactivation activities, which may be related to cortical originated central processing mechanism of neuromuscular activities. (shrink)

Due to the increasing number of people traveling by air, the passenger flow at the airport is increasing, and the problem of passenger drop-off and pickup has a huge impact on urban traffic. The difficulty of taking a taxi at the airport is still a hot issue in the society. Aiming at the problem of optimizing the allocation of taxi resource, this paper is based on the cost-benefit analysis method to determine the factors that affect the taxi driver’s decision-making. The (...) mathematical methods such as function equation, BP neural network algorithm, and queuing theory were used to establish a complete decision-making model for taxi drivers and an optimization model of dispatching efficiency at the airport. A conclusion has been drawn that the allocation of airport taxi resource should be arranged closely related to drivers’ revenue and the layout of airport line. (shrink)

Assumed benefits from improved reputation are often used as motives to drive corporate social responsibility (CSR) initiatives. Are improved cost efficiencies among these reputation benefits? Cost efficiencies and cost management have become more relevant as revenue streams dry up in these tough economic times. Can a good reputation aid these efforts to develop cost efficiencies specifically when managing labor costs? Prior research hypothesizes that good reputation can create labor productivity and efficiency benefits. The purpose of this study is to (...) empirically investigate reputation's relationship with labor efficiency, labor productivity, and labor cost. Using a sample of highly reputable firms from Fortune's America's Most Admired Companies list and a corresponding matched sample of firms, we find that reputation is associated with improved labor efficiency and labor productivity. However, we do not find a significant association between reputation and reduced labor costs. Our study contributes to current research hypothesizing and finding efficiency benefits associated with good reputation. Documenting these potential reputation benefits has important implications for CSR activities and initiatives. It supports recent work that incorporates reputation into a more developed model of the relationship between CSR and performance (Vilanova et al.: 2009, Journal of Business Ethics 87, 57-69). This work is useful to businesses and supports strategies focused on "doing well by doing good" and maintaining healthy reputations. (shrink)

Significant changes are proposed for the research ethics system governing the review of the conduct of medical research in the UK. This paper examines these changes and whether they will meet the aimed-for goal of improving the efficiency of the research ethics system. The author concludes that, unfortunately, they will not and thus should be rejected.

Quality and service improvement (QSI) research employs a broad range of methods to enhance the efficiency of healthcare delivery. QSI research differs from traditional healthcare research and poses unique ethical questions. Since QSI research aims to generate knowledge to enhance quality improvement efforts, should it be considered research for regulatory purposes? Is review by a research ethics committee required? Should healthcare providers be considered research participants? If participation in QSI research entails no more than minimal risk, is (...) consent required? The lack of consensus on answers to these questions highlights the need for ethical guidance. Three distinct approaches to classifying QSI research in accordance with existing ethical principles and regulations can be found in the literature. In the first approach, QSI research is viewed as distinct from other types of healthcare research and does not require regulation. In the second approach, QSI research falls within regulatory guidelines but is exempt from research ethics committee review. In the third approach, QSI research is deemed to be part of the learning healthcare system and, as such, is subject to a different set of ethical principles entirely. In this paper, we critically assess each of these views. While none of these approaches is entirely satisfactory, we argue that use of the ethical principles governing research provides the best means of addressing the numerous questions posed by QSI research. (shrink)

A principal rationale for public policy is to address market failures. Pareto efficiency is therefore a highly common and relatively non-controversial evaluative criterion for many policy analyses and is discussed at length in policy analysis texts. This makes sense, for Pareto improvements involve making at least one person better off without making anyone worse off. Who could object to that? But does efficiency deserve the prominence it enjoys in public policy? Is one policy option better than another, at (...) least in one respect, simply because it is more Pareto efficient? Or, is efficiency valuable for some other reason? In this chapter, I discuss Pareto efficiency as an evaluative criterion and argue that it is a stand-in for a more foundational criterion: wellbeing. I begin with an overview of Pareto efficiency, discuss the various ways in which it is operationalized to evaluate policy options, and argue that it is valuable insofar as more efficient states of affairs promise more wellbeing than less efficient states of affairs. I then raise questions regarding whether the conception of wellbeing presupposed by Pareto efficiency – preference satisfaction – is a defensible conception of wellbeing. I go on to introduce three alternative conceptions of wellbeing which have been proposed and defended by both philosophers and policy scholars, namely, hedonism, objective goods views, and the capability approach, and suggest ways in which each can be operationalized as an evaluative criterion. I close by discussing four ‘theory-free’ approaches to thinking about the impact of policies on the quality of people’s lives. Such approaches reject the idea that there is one single theory of wellbeing that should be used to evaluate policy options, and instead develop ways to evaluate the impact of policies on people’s lives that are not grounded in a specific theory. (shrink)

Attention has been theorized as a system comprising three networks that can be estimated reliably by the attention network test ; the three networks are defined as alerting, orienting, and conflict control. The present study aims to identify the attention networks that are crucial for elite shooting and archery athletes and to examine whether mindfulness training can improve elite athletes' attention networks. We compared the performances in ANT between 62 elite athletes from the Chinese national team of shooting and archery (...) and 49 athletes from a provincial team in China. The results indicate three well-functioned attention networks in both groups, but elite athletes in the national team responded faster overall than athletes in the provincial team. The 62 elite athletes in the national team then received mindfulness training with varied periods ranging from 5 to 8 weeks, after which the ANT was re-administered. After mindfulness training, the elite athletes improved in orienting and conflict control networks compared with their pre-training performances. These results suggest that elite shooting and archery athletes in the national team are more efficient in all three attention networks, which means that they are able to reach the alerting state faster, make better use of environmental information, and suppress interference from distractors more efficiently. Moreover, the orienting and conflict control networks of the elite shooting and archery athletes can be improved by mindfulness training. We conclude that mindfulness practice should be considered as a useful addition to daily training for shooting and archery athletes. (shrink)

Teaching the art of profession-related communication to students of non-linguistic study fields allows instructors to explain their students how to keep up the conversation using facts, data, concepts etc. specific to the area of their future profession. It activates the acquisition processes as well as increases students' motivation to study. The formation of oral monologue speaking skills in students of non-linguistic study fields is one of the tasks within the course of Foreign ( English) Language for Specific Purposes.This process is (...) associated with certain difficulties, which can inhibit learning and demotivated students to study. Among strategies and techniques aiding learning that can be used to improve performance and study outcomes during the course and can be implemented for the enhancement of speaking on occupation-related topics, the mind mapping technique is of specific relevance. It can serve as an interesting and useful tool serving to enhance quality of oral speaking skills in students majoring in Psychology as the representatives of non-linguistic study fields. The article analyses the carried out research concerning the facilitating impact of mind mapping on the oral speech performance of Psychology students. The study hypothesis implies that the use of the mind-mapping technique in the process of preparing for and presenting the talk in the study sessions enhances students' oral monologue speech performance. In order to check the hypothesis, we have conducted the experiment in Bohdan Khmelnytsky National University of Cherkasy at the Department of Psychology. The study involved 46 first-year students, including 34 female and 12 male participants. The respondents were randomly assigned to the experimental mind-mapping group of 23 students ( including 6 males) and the control group of 23 students ( including 6 males as well). The students in the experimental group were involved into the experiment using the mind-mapping technique during their study, and the students in the control group continued their study in the usual way. The hypothesis was confirmed. The mind map use stimulates activity of both brain hemispheres, thus making it easier for students to memorize thematic vocabulary, follow the logical sequence of the talk when speaking. The research findings have shown the effectiveness of implementing the mind-mapping technique into the university course teaching English for Specific Purposes to develop, advance and master students' professional communicative competence. Consistent use of mind maps will also promote the educational process efficiency and have positive effects on the general formation of competitive skilled specialists. (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)

Responsible risk management is central to banking ethics. With the 1999 publication of the Basel Committee's proposal, Basel II, for a New Capital Accord to replace the 1988 agreement, Basel I, an attempt has been made to address the problem of correlating banks' risk management with their capital requirements. The Basel II framework, finalised in June 2004, is designed to improve risk management by using models based on past performance to help set the amount of capital banks are required to (...) hold by regulators, with the purpose of improving the efficiency of capital allocation. The objectives of this study are to investigate how banks generally, but particularly those located in China, could improve their risk management systems and what the implications of these new regulations are for them. Three relevant propositions were formulated, namely, Basel II will improve risk management; Basel II will improve capital allocation efficiency; and compliance with advanced risk management systems is biased in favour of the large banks. Evidence was assembled with which to evaluate these three propositions by gathering relevant primary data by means of a representative survey of Chinese banking executives involved in risk management. The findings strongly support the first two of the above propositions and partly support the third proposition. (shrink)