Multidimensional Task Research Articles

Markedness Correspondence in Translation of Books’ Titles

Translation is a multi-dimensional task which requires different aspects of competencies one of which is linguistics. Falling within the realm of linguistic competence is the ability to produce relatively similar degree of markedness throughout the translation. Such ability contributes to keep the thematic structure of sentences intact and make the same propositional meanings have different communicative meanings. The present study which is a descriptive analytical corpus-based one aimed to analyze the thematic structure of titles of all English books rendered into Persian from the beginning of translation in Iran to 2004drawing on Hallidayan linguistic taxonomy of marked sentences as proposed by Baker (1992). The corpus is a parallel one consisting of 141 marked English book titles and their Persian translations. Comparative analyses of items revealed that about 56.7% of all marked English sentences havebeen translated into marked Persian sentences, i.e. the thematic structure of ST has been preserved. The similar thematic structure entails corresponding communicative meaning of STand TT. Keywords: Translation, Information structure (IS), Theme/Rheme, Markedness

Research on multi-dimensional N-back task induced EEG variations.

In order to test the effectiveness of multi-dimensional N-back task for inducing deeper brain fatigue, we conducted a series of N*L-back experiments: 1*1-back, 1*2-back, 2*1-back and 2*2-back tasks. We analyzed and compared the behavioral results, EEG variations and mutual information among these four different tasks. There was no significant difference in average EEG power and power spectrum entropy (PSE) among the tasks. However, the behavioral result of N*2-back task showed significant difference compared to traditional one dimensional N-back task. Connectivity changes were observed with the addition of one more matching task in N-back. We suggest that multi-dimensional N-back task consume more brain resources and activate different brain areas. These results provide a basis for multi-dimensional N-back tasks that can be used to induce deeper mental fatigue or exert more workload.

Attention-Getting and/or Effort-Inducing? An Examination of How Incentive Compensation Motivates Quality and Quantity Performance in a Multidimensional Environment

We investigate the effectiveness of two proposed motivating properties of incentive compensation – the attention-getting property and the effort-inducing property – in a multidimensional task environment. Specifically, in a task environment with quantity and quality dimensions we empirically test the effects of the two properties on performance in an effort to gain a more thorough understanding of the workings of incentive compensation. Our experimental results indicate that the attention-getting property always has a positive performance effect on the task dimension to which attention is directed. We also find that the effort-inducing property has an incremental positive performance effect over and above the attention-getting property on the quality dimension, but not on the quantity dimension. Our analysis also highlights that the attention-getting and effort-inducing properties of incentive compensation have separate performance spillover effects onto non-incentivized task dimensions and we provide insight on how these spillover effects vary. Our study has direct implications for theoretical research on, and use in practice of, inventive compensation in multidimensional task environments.

The international state of research on measurement of competency in higher education

With the Program for International Student Assessment and Trends in International Mathematics and Science Study surveys, competency assessment became an important policy instrument in the school sector; only recently has international competency measurement gained attention in higher education with the Assessment of Higher Education Learning Outcomes (AHELO) feasibility study. As AHELO showed, measurement of competencies in higher education is a complex and multidimensional task, which poses great methodological challenges. These challenges arise out of the high diversity of degree courses, study programs, and institutions of higher education. Nevertheless, we need to address these challenges immediately if we aim to create evidence-based high-quality educational systems. This paper overviews the field of international research on competency measurement in higher education. Our analyses revealed a substantial lack of research in this area. Nonetheless, existing studies and assessment practices in various countries provide orientation on how to model competencies based on curricular and professional requirements, design assessments following the assessment triangle, and validate them comprehensively.

Carrots That Look Like Sticks: Toward an Understanding of Multitasking Incentive Schemes

Constructing compensation schemes for effort in multi-dimensional tasks is complex, particularly when some dimensions are not easily observable. When incentive schemes contractually reward workers for easily observed measures, such as quantity produced, the standard model predicts that unrewarded dimensions, such as quality, will be neglected. Yet, there remains mixed empirical evidence in favor of this standard principal-agent model prediction. This paper reconciles the literature by using both theory and empirical evidence. The theory outlines conditions under which principals can use a piece rate scheme to induce higher quantity and quality levels than analogous fixed wage schemes. Making use of a series of complementary laboratory and field experiments we show that this effect occurs because the agent is uncertain about the principal's monitoring ability and the principal's choice of a piece rate signals to the agent that she is efficient at monitoring.

Carrots That Look Like Sticks: Toward an Understanding of Multitasking Incentive Schemes

Constructing compensation schemes for effort in multidimensional tasks is complex, particularly when some dimensions are not easily observable. When incentive schemes contractually reward workers for easily observed measures, such as quantity produced, the standard model predicts that unrewarded dimensions, such as quality, will be neglected. Yet, there remains mixed empirical evidence in favor of this standard principal‐agent model prediction. This article reconciles the literature using both theory and empirical evidence. The theory outlines conditions under which principals can use a piece rate scheme to induce higher quantity and quality levels than analogous fixed wage schemes. Making use of a series of complementary laboratory and field experiments we show that this effect occurs because the agent is uncertain about the principal's monitoring ability and the principal's choice of a piece rate signals to the agent that she is efficient at monitoring.

Teaching mechatronics with tuned problem-based projects

ABSTRACTSystem design—a complex multi-dimensional synthesis task—is a key skill for practising mechatronics engineers. Challenging team projects stimulate engineering students into developing this skill and others, including teamwork, communication and project planning. This paper describes a teaching design that combines project-based learning with problem-based learning. The design of the challenge is specifically tuned to give rise to conflicting engineering constraints and common problems encountered in mechatronics. This paper describes how to use the design process to develop a project-problem framework, and provides a case study in which limited energy economy, sensing and control, and disturbances and uncertainty challenges are emphasised.

Deterministic Multi-dimensional Task Scheduling Algorithms for Wearable Sensor Devices

In recent years, wearable sensor devices are reshaping the way people live, work, and play. A wearable sensor device is a computer that is subsumed into the personal space of the user, and is always on, and always accessible. Therefore, among the most salient aspects of a wearable sensor device should be a small form factor, long battery lifetime, and real-time characteristics. Thereby, sophisticated applications of a wearable sensor device use real-time operating systems to guarantee real-time deadlines. The deterministic multi-dimensional task scheduling algorithms are implemented on ARC (Actual Remote Control) with relatively limited hardware resources. ARC is a wearable wristwatch-type remote controller; it can also serve as a universal remote control, for various wearable sensor devices. In the proposed algorithms, there is no limit on the maximum number of task priorities, and the memory requirement can be dramatically reduced. Furthermore, regardless of the number of tasks, the complexity of the time and space of the proposed algorithms is O(1). A valuable contribution of this work is to guarantee real-time deadlines for wearable sensor devices.

Participation in the Labour Market - Generation Y and Other Age Groups

The objective of the Europe 2020 strategy is to achieve the employment rate in 2020 on level of 75% for the European Union. Strategic objectives for the Member States are different. In Poland in 2020, the employment rate should reach 71%. Employment rates differs depending on age groups, gender and country in which it is measured. There are also many factors that mobilizing generations to maintain employment. These factors determine the level of employment rate. They also cause that determination of the participation of social groups in the labour market is a multi-dimensional task. The aim of the study is to examine the labour market participation of people from generation Y in comparisons to other age groups. People in this age group are guided by other values in lifestyle than older people. To achieve the objectives of the study were used statistical analysis methods adequate to the scale of measurement of factors observed on the labour market. DOI: 10.5901/ajis.2014.v3n3p111

SUSTAINABLE ECONOMY INSPIRED LARGE-SCALE FEED-FORWARD PORTFOLIO CONSTRUCTION

To understand large-scale portfolio construction tasks we analyse sustainable economy problems by splitting up large tasks into smaller ones and offer an evolutional feed-forward system-based approach. The theoretical justification for our solution is based on multivariate statistical analysis of multidimensional investment tasks, particularly on relations between data size, algorithm complexity and portfolio efficacy. To reduce the dimensionality/sample size problem, a larger task is broken down into smaller parts by means of item similarity – clustering. Similar problems are given to smaller groups to solve. Groups, however, vary in many aspects. Pseudo randomly-formed groups compose a large number of modules of feed-forward decision-making systems. The evolution mechanism forms collections of the best modules for each single short time period. Final solutions are carried forward to the global scale where a collection of the best modules is chosen using a multiclass cost-sensitive perceptron. Collected modules are combined in a final solution in an equally weighted approach (1/N Portfolio). The efficacy of the novel decision-making approach was demonstrated through a financial portfolio optimization problem, which yielded adequate amounts of real world data. For portfolio construction, we used 11,730 simulated trading robot performances. The dataset covered the period from 2003 to 2012 when environmental changes were frequent and largely unpredictable. Walk-forward and out-of-sample experiments show that an approach based on sustainable economy principles outperforms benchmark methods and that shorter agent training history demonstrates better results in periods of a changing environment.

Free Search - comparative analysis 100

Search methods' abilities for adaptation to various multidimensional tasks where optimisation parameters are hundreds, thousands and more, without retuning of algorithms' parameters seems to be a great challenge for modern computational intelligence. Many evolutionary, swarm and adaptive methods, which perform well on numerical tests with up to ten dimensions are suffering insuperable stagnation when applied to 100 and more dimensional tests. This article presents a comparison between particle swarm optimisation, differential evolution both with enhanced adaptivity and Free Search applied to 100 multidimensional heterogeneous real-value numerical tests. The aim is to extend the knowledge on how high dimensionality reflects on search space complexity, in particular to identify minimal time and minimal number of objective function evaluations required by used methods for reaching acceptable solution with non-zero probability on tasks with high dimensions' number. The achieved experimental results are summarised and analysed. Brief discussion on concepts, which support search methods effectiveness, concludes the article.

Migrating enterprise applications to the cloud: methodology and evaluation

Migrating existing on-premise applications to the cloud is a complex and multi-dimensional task and may require adapting the applications themselves significantly. For example, when considering the migration of the database layer of an application, which provides data persistence and manipulation capabilities, it is necessary to address aspects like differences in the granularity of interactions and data confidentiality, and to enable the interaction of the application with remote data sources. In this work, we present a methodology for application migration to the cloud that takes these aspects into account. In addition, we also introduce a tool for decision support, application refactoring and data migration that assists application developers in realising this methodology. We evaluate the proposed methodology and enabling tool using a case study in collaboration with an IT enterprise.

Drug safety testing paradigm, current progress and future challenges: an overview.

Early assessment of the toxicity potential of new molecules in pharmaceutical industry is a multi-dimensional task involving predictive systems and screening approaches to aid in the optimization of lead compounds prior to their entry into development phase. Due to the high attrition rate in the pharma industry in last few years, it has become imperative for the nonclinical toxicologist to focus on novel approaches which could be helpful for early screening of drug candidates. The need is that the toxicologists should change their classical approach to a more investigative approach. This review discusses the developments that allow toxicologists to anticipate safety problems and plan ways to address them earlier than ever before. This includes progress in the field of in vitro models, surrogate models, molecular toxicology, 'omics' technologies, translational safety biomarkers, stem-cell based assays and preclinical imaging. The traditional boundaries between teams focusing on efficacy/ safety and preclinical/ clinical aspects in the pharma industry are disappearing, and translational research-centric organizations with a focused vision of bringing drugs forward safely and rapidly are emerging. Today's toxicologist should collaborate with medicinal chemists, pharmacologists, and clinicians and these value-adding contributions will change traditional toxicologists from side-effect identifiers to drug development enablers.

Neural Mechanisms Involved in Multi-Dimensional Task Switching: A Meta-Analysis

Neural Mechanisms Involved in Multi-Dimensional Task Switching: A Meta-Analysis

Multi-dimensional Constrained Cloud Computing Task Scheduling Mechanism Based on Genetic Algorithm

A new Cloud Computing task scheduling mechanism with multi-dimensional constrained based on Genetic Algorithm (GA) was proposed to reduce time to complete tasks and to improve usersâ?? satisfaction by reducing expenses. The algorithm improves fitness function with comprehensive efficiency constituted of shortest completion time and minimum cost. Finally, simulation results showed that this algorithm is highly efficient and meet not only performance needs but also economic needs of users.

Planning practice in support of economically and environmentally sustainable roads in floodplains: The case of the Mekong delta floodplains

Road development in relatively undisturbed floodplain systems, such as the floodplains of the Mekong River, will impact hydraulics and interrupt the natural flow of water. This affects the ecology and environment, and the livelihoods of people who depend on fishing and agriculture. On the other hand, floods can severely damage road infrastructure in years with large floods and can cause high annual maintenance costs. Improving road development practices in floodplains is a complex, multidimensional task involving hydraulic and geotechnical analysis, ecosystem analysis, socio-economic analysis, policy analysis, etc. This paper analyses the planning practice of road development and rehabilitation and how this practice can be improved in support of economically and environmentally sustainable roads in floodplains. It is concluded that although ample technical, planning and environmental assessment guidelines exist, guidelines need updating to address cumulative impacts at floodplain level and factors hampering the implementation in guidelines should be addressed in the guideline design (process).

Everyone's own poverty: Gendering poverty alleviation policies in Turkey

The last general election campaign in 2011 was the first in Turkish history to focus on transferring cash to women. This is a strong indication of the feminized face of poverty in Turkey, but also a sign that women are seen as instrumental agents in poverty alleviation. Although until now there has been no systematic policy directed solely to women fighting against poverty, there are patchy micro-credit approaches that target women and households. This article examines gendered aspect of poverty and poverty alleviation policies in Turkey. It argues that the changing nature of poverty has forced the re-alignment of policies to take women into consideration as the main agents of poverty alleviation. Based on the findings of a field survey conducted in the cities of Mugla and Mardin, the study also sheds light on the nature of women's self-expressed needs for poverty alleviation, and shows that addressing female poverty is a multi-faced and multi-dimensional task that should include both holistic and particularistic approaches to poverty alleviation. In the study, 204 women from Mugla (western part of Turkey) and 204 women from Mardin (eastern part of Turkey), where different ethnicities live, were asked what government action was needed to increase their household welfare. The results show that the government action needed to increase household welfare changes according to the geographical location of women and ethnic differences, and this is not necessarily in accordance with the past and current poverty alleviation policies.

Challenges in agrochemicals design

Design of active ingredients is a multidimensional task. Sufficient activity in combination with high bioavailability and no (or at least low) toxicological behaviour are prerequisites for promising candidates. In this respect, pharmaceutical and agrochemical companies need to address the same issues. Considering the activity one can generally conclude that is target regardless of whether the respective organism is a human or a pest. In detail however, drugs modulate activity of dysfunctional proteins or their functional counterparts aiming to reduce the pathogenic effects. In contrast to that agrochemicals modulate vitally important proteins in order to keep harmful organisms under control. Bioavailability of drugs usually addresses the human patient with regard to a preferred oral application. Agrochemicals have to be divided into herbicides, fungicides and insecticides controlling weed, harmful fungi and insect pests. For each of these harmful organisms different absorption, distribution, metabolism and excretion routes have to be considered leading to quite different physicochemical properties of lead compounds. Based on the above-mentioned similarities and differences, the presentation will give an overview on commonly applied computational approaches in pharmaceutical and agrochemical companies as well as several unique challenges relevant just for the design of potent crop protection compounds.

Car driving in schizophrenia: can visual memory and organization make a difference?

Purpose: Driving is a meaningful occupation which is ascribed to functional independence in schizophrenia. Although it is estimated that individuals with schizophrenia have two times more traffic accidents, little research has been done in this field. Present research explores differences in mental status, visual working memory and visual organization between drivers and non-drivers with schizophrenia in comparison to healthy drivers. Methods: There were three groups in the study: 20 drivers with schizophrenia, 20 non-driving individuals with schizophrenia and 20 drivers without schizophrenia (DWS). Visual perception was measured with Rey-Osterrieth Complex Figure test and a general cognitive status with Mini-Mental State Examination. Results: The general cognitive status predicted actual driving situation in people with schizophrenia. No statistically significant differences were found between driving and non-driving persons with schizophrenia on any of the visual parameters tested, although these abilities were significantly lower than those of DWS. Conclusion: The research demonstrates that impairment of visual abilities does not prevent people with schizophrenia from driving and emphasizes the importance of general cognitive status for complex and multidimensional everyday tasks. The findings support the need for further investigation in the field of car driving for this population – a move that will considerably contribute to the participation and well-being.Implication for RehabilitationUnique approach for driving evaluation in schizophrenia should be designed since direct applications of knowledge and practice acquired from other populations are not reliable.This research demonstrates that visual perception deficits in schizophrenia do not prevent clients from driving, and general cognitive status appeared to be a valid determinant for actual driving.We recommended usage of a general test of cognition such as Mini-Mental State Examination, or conjunction number of cognitive factors such as executive functions (e.g. Trail Making Test) and attention (e.g. Continuous Performance Test) in addition to spatial-visual ability tests (e.g. Rey-Osterrieth Complex Figure test) for considering driving status in schizophrenia.

Governing risk, engaging publics and engendering trust: New horizons for law and social science?

Modern biosciences require governance frameworks capable of simultaneously managing risk, coping with uncertainty, combatting ambivalence, and building trust, while encouraging the delivery of those instrumental outputs that we value/demand. This multi-dimensional task makes the design and delivery of good governance frameworks extremely difficult. Efforts to date have, by and large, failed, particularly where the law has been relied on. Preoccupation with risk has tended to shape regulatory systems, but the conception of risk relied on is deficient, and its use is often oriented to support precautionary approaches in the absence of ‘evidence’. Our collaborative efforts lead us to suggest that more robust mechanisms need to be deployed which reveal and promote interactions with a fuller gamut of risks. We argue for a reflexive mode of governance which addresses the dynamic nature of science and uses the law more effectively as a value- and institution-framing mechanism.