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1 – 10 of 42Ana María Lucia‐Casademunt, J. Antonio Ariza‐Montes and Alfonso Carlos Morales‐Gutiérrez†
Employee well‐being (WB) is a strategic reference of prime importance due to its impact on human capital, employee health and quality in working life, factors that are key to…
Abstract
Purpose
Employee well‐being (WB) is a strategic reference of prime importance due to its impact on human capital, employee health and quality in working life, factors that are key to achieving successful organisations. The purpose of the current study is to assess the WB of female managers in the European workplace. The research analyses three dimensions (job satisfaction, comfort and enthusiasm) and the effect of job‐related factors on each one of these.
Design/methodology/approach
The Mental Health and Vitamin models (Warr, 1987) were taken as the starting‐point of the research. An alternative econometric method – an artificial neural network known as extreme learning machine was applied to a sample of 99 female managers collected from the 5th European Working Conditions Survey‐2010
Findings
The results obtained confirm that this methodology is valid to efficiently classify European female managers into those who feel satisfied with their jobs, calm and relaxed, and cheerful and in good spirits, and those who do not. Furthermore, the resulting model identifies the strongest factors important in determining the varied dimensions of occupational WB achieved.
Originality/value
Even today, despite the important contribution women managers make to the management of organisations, they have to face many challenges and overcome serious barriers in achieving and staying in positions of leaderships when compared to their male counterparts.
Propósito
El bienestar laboral constituye un referente estratégico de primer orden por su impacto sobre el capital humano – salud y calidad de vida laboral de los empleados –, en aras de alcanzar organizaciones exitosas. El objetivo del presente artículo es analizar el bienestar laboral a partir de sus tres dimensiones (satisfacción, confort y entusiasmo) de las mujeres que ocupan puestos de dirección en Europa y el efecto de ciertos factores laborales.
Diseño/metodología/enfoque
Se adopta como punto de partida los modelos teóricos de salud mental y vitamínico (Warr, 1987), aplicando un método econométrico novedoso – redes neuronales artificiales –, a una muestra de 99 mujeres directivas extraída de la V Encuesta Europea de Condiciones de Trabajo (2010).
Resultados
Los resultados obtenidos confirman la validez de esta novedosa metodología para clasificar eficazmente a las mujeres directivas que presentan un elevado grado de bienestar laboral. Por otra parte, con el modelo resultante se identifican los factores más determinantes para el logro de cada una de las dimensiones que constituyen el bienestar laboral.
Originalidad
Las mujeres directivas, quienes a pesar de lo mucho que tienen que aportar en la gestión de las organizaciones, aún hoy encuentran que su acceso y permanencia en los puestos de dirección está colmado de desafíos y barreras difíciles de superar en comparación con sus homólogos masculinos.
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This paper aims to contribute to the formulation of a theory of consciousness based only on computational processes. In this manner, sound computational explanations of qualia and…
Abstract
Purpose
This paper aims to contribute to the formulation of a theory of consciousness based only on computational processes. In this manner, sound computational explanations of qualia and the “hard problem” of consciousness are provided in response to a lack of physical, chemical and psychological explanations.
Design/methodology/approach
The study analyses the little that can be objectively known about qualia, and proposes a process that imitates the same effects. Then it applies the process to a robot (using a thought experiment) to understand whether this would produce the same sensations as humans experience.
Findings
A computational explanation of qualia and the “hard problem” of consciousness is possible through computational processes.
Research limitations/implications
This is a proposal, subject to argumentation and proof. It is a falsifiable theory, meaning that it is possible to test or reject it, as its computational basis allows for a future implementation.
Practical implications
Subjective feeling emerges as an evolutionary by-product when there are no strong evolutionary pressures on the brain. Qualia do not involve magic. These aspects of consciousness in robots and in organisations are capable of being manufactured; one can choose whether to build robots and organisations with qualia and subjective experience.
Originality/value
To the best of the author’s knowledge, no other computational interpretation of these aspects of consciousness exists. However, it is compatible with the multiple draft model of Dennett (1991) and the attention schema theory of Webb and Graziano (2015).
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Babar Khan, Fang Han, Zhijie Wang and Rana J. Masood
This paper aims to propose a biologically inspired processing architecture to recognize and classify fabrics with respect to the weave pattern (fabric texture) and yarn color…
Abstract
Purpose
This paper aims to propose a biologically inspired processing architecture to recognize and classify fabrics with respect to the weave pattern (fabric texture) and yarn color (fabric color).
Design/methodology/approach
By using the fabric weave patterns image identification system, this study analyzed the fabric image based on the Hierarchical-MAX (HMAX) model of computer vision, to extract feature values related to texture of fabric. Red Green Blue (RGB) color descriptor based on opponent color channels simulating the single opponent and double opponent neuronal function of the brain is incorporated in to the texture descriptor to extract yarn color feature values. Finally, support vector machine classifier is used to train and test the algorithm.
Findings
This two-stage processing architecture can be used to construct a system based on computer vision to recognize fabric texture and to increase the system reliability and accuracy. Using this method, the stability and fault tolerance (invariance) was improved.
Originality/value
Traditionally, fabric texture recognition is performed manually by visual inspection. Recent studies have proposed automatic fabric texture identification based on computer vision. In the identification process, the fabric weave patterns are recognized by the warp and weft floats. However, due to the optical environments and the appearance differences of fabric and yarn, the stability and fault tolerance (invariance) of the computer vision method are yet to be improved. By using our method, the stability and fault tolerance (invariance) was improved.
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Jiaying Chen, Cheng Li, Liyao Huang and Weimin Zheng
Incorporating dynamic spatial effects exhibits considerable potential in improving the accuracy of forecasting tourism demands. This study aims to propose an innovative deep…
Abstract
Purpose
Incorporating dynamic spatial effects exhibits considerable potential in improving the accuracy of forecasting tourism demands. This study aims to propose an innovative deep learning model for capturing dynamic spatial effects.
Design/methodology/approach
A novel deep learning model founded on the transformer architecture, called the spatiotemporal transformer network, is presented. This model has three components: the temporal transformer, spatial transformer and spatiotemporal fusion modules. The dynamic temporal dependencies of each attraction are extracted efficiently by the temporal transformer module. The dynamic spatial correlations between attractions are extracted efficiently by the spatial transformer module. The extracted dynamic temporal and spatial features are fused in a learnable manner in the spatiotemporal fusion module. Convolutional operations are implemented to generate the final forecasts.
Findings
The results indicate that the proposed model performs better in forecasting accuracy than some popular benchmark models, demonstrating its significant forecasting performance. Incorporating dynamic spatiotemporal features is an effective strategy for improving forecasting. It can provide an important reference to related studies.
Practical implications
The proposed model leverages high-frequency data to achieve accurate predictions at the micro level by incorporating dynamic spatial effects. Destination managers should fully consider the dynamic spatial effects of attractions when planning and marketing to promote tourism resources.
Originality/value
This study incorporates dynamic spatial effects into tourism demand forecasting models by using a transformer neural network. It advances the development of methodologies in related fields.
目的
纳入动态空间效应在提高旅游需求预测的准确性方面具有相当大的潜力。本研究提出了一种捕捉动态空间效应的创新型深度学习模型。
设计/方法/途径
本研究提出了一种基于变压器架构的新型深度学习模型, 称为时空变压器网络。该模型由三个部分组成:时空转换器、空间转换器和时空融合模块。时空转换器模块可有效提取每个景点的动态时间依赖关系。空间转换器模块可有效提取景点之间的动态空间相关性。提取的动态时间和空间特征在时空融合模块中以可学习的方式进行融合。通过卷积运算生成最终预测结果。
研究结果
结果表明, 与一些流行的基准模型相比, 所提出的模型在预测准确性方面表现更好, 证明了其显著的预测性能。纳入动态时空特征是改进预测的有效策略。它可为相关研究提供重要参考。
实践意义
所提出的模型利用高频数据, 通过纳入动态空间效应, 在微观层面上实现了准确预测。旅游目的地管理者在规划和营销推广旅游资源时, 应充分考虑景点的动态空间效应。
原创性/价值
本研究通过使用变压器神经网络, 将动态空间效应纳入旅游需求预测模型。它推动了相关领域方法论的发展。
Objetivo
La incorporación de efectos espaciales dinámicos ofrece un considerable potencial para mejorar la precisión de la previsión de la demanda turística. Este estudio propone un modelo innovador de aprendizaje profundo para capturar los efectos espaciales dinámicos.
Diseño/metodología/enfoque
Se presenta un novedoso modelo de aprendizaje profundo basado en la arquitectura transformadora, denominado red de transformador espaciotemporal. Este modelo tiene tres componentes: el transformador temporal, el transformador espacial y los módulos de fusión espaciotemporal. El módulo transformador temporal extrae de manera eficiente las dependencias temporales dinámicas de cada atracción. El módulo transformador espacial extrae eficientemente las correlaciones espaciales dinámicas entre las atracciones. Las características dinámicas temporales y espaciales extraídas se fusionan de manera que se puede aprender en el módulo de fusión espaciotemporal. Se aplican operaciones convolucionales para generar las previsiones finales.
Conclusiones
Los resultados indican que el modelo propuesto obtiene mejores resultados en la precisión de las previsiones que algunos modelos de referencia conocidos, lo que demuestra su importante capacidad de previsión. La incorporación de características espaciotemporales dinámicas supone una estrategia eficaz para mejorar las previsiones. Esto puede proporcionar una referencia importante para estudios afines.
Implicaciones prácticas
El modelo propuesto aprovecha los datos de alta frecuencia para lograr predicciones precisas a nivel micro incorporando efectos espaciales dinámicos. Los gestores de destinos deberían tener plenamente en cuenta los efectos espaciales dinámicos de las atracciones en la planificación y marketing para la promoción de los recursos turísticos.
Originalidad/valor
Este estudio incorpora efectos espaciales dinámicos a los modelos de previsión de la demanda turística mediante el empleo de una red neuronal transformadora. Supone un avance en el desarrollo de metodologías en campos afines.
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Recently Dr Erik Arnold, a consultant with Booz, Allen and Hamilton International produced an Evaluation Report which reviewed the UK Alvey Intelligent Knowledge‐Based Systems…
Abstract
Recently Dr Erik Arnold, a consultant with Booz, Allen and Hamilton International produced an Evaluation Report which reviewed the UK Alvey Intelligent Knowledge‐Based Systems (IKBS) programme. The report gives a history of the programme and indicates its main aims and strategies. Its recommendations and evaluation are based on a comprehensive discussion of the programme's achievements as well as its weaknesses. The evaluation report says that the programme has been a big success in reviving the fortunes of Artificial Intelligence in the UK. For various reasons AI lost its initial impetus in the UK in the early 1970s and there were very few scientists and probably only one university department that could undertake research and development when the Japanese announcements brought the field to the fore. Indeed there was very little interest and support from UK industry and commerce at that time.
Karel Diéguez-Santana, Giselle Rodríguez Rudi, Ana Julia Acevedo Urquiaga, Emanuel Muñoz and Neyfe Sablón-Cossio
In this paper, the authors adopt the theory of the circular economy to study the transitions that take place in three case studies in Mexico and Ecuador. The work is aimed to…
Abstract
Purpose
In this paper, the authors adopt the theory of the circular economy to study the transitions that take place in three case studies in Mexico and Ecuador. The work is aimed to systematize a circular economy assessment tool that fosters opportunities for improvement in business practices.
Design/methodology/approach
The methodology is based on a descriptive quantitative analysis, where a checklist is made with 91 items and nine study variables. This is from the study of the bibliography and business practice. Furthermore, the neural network method is used in a case study to predict the level of circular economy and the importance of each variable according to the sensitivity by the Lek’s profile method.
Findings
It is based on a descriptive quantitative analysis, where a checklist with 91 items and nine study variables is made, defined from a bibliographic study and business practice. Furthermore, the neural network method is used in a case study to predict the level of circular economy and the importance of each variable based on sensitivity.
Research limitations/implications
The application of the tool requires prior knowledge of the circular economy approach, which is why specialized personnel are needed for its application. This makes research more expensive in time and human resources.
Practical implications
The practical and methodological contribution of this work lies in the feasibility of the tool that favors the definition of improvement actions for the implementation contribution to the circular economy in business practices.
Social implications
The social contribution is framed in the gradual transition to circular economy approaches in underdeveloped countries.
Originality/value
The use of the neural network method to predict the level of circular economy in a case study allows making decisions in a predictive way. This encourages the development of the circular economy according to the context needs.
Objetivo
En este trabajo adoptamos la teoría de la economía circular para estudiar las transiciones que ocurren en tres casos de estudio en México y Ecuador. El trabajo tiene como objetivo sistematizar una herramienta de evaluación de la economía circular que fomente oportunidades de mejora en las prácticas empresariales.
Diseño / metodología / enfoque
La metodología se basa en un análisis cuantitativo descriptivo, donde se elabora un checklist con 91 ítems y nueve variables de estudio. Esto a partir del estudio de la bibliografía y la práctica empresarial. Además, el método de la red neuronal se utiliza en un estudio de caso para predecir el nivel de economía circular y la importancia de cada variable según la sensibilidad utilizando el método Lekprofile.
Hallazgos
Los resultados muestran que la herramienta es aplicable a diferentes contextos y simultáneamente permite la evaluación de la economía circular de forma holística. Además, la herramienta se puede vincular a técnicas predictivas, como el método de red neuronal. Esto se demostró en un estudio de caso.
Originalidad
en el uso del método de redes neuronales para predecir el nivel de economía circular en un caso de estudio. Esto permite la capacidad de tomar decisiones de forma predictiva y esto incentiva el desarrollo de la economía circular según la necesidad del contexto.
Limitaciones / implicaciones de la investigación
Las limitaciones se centran en la necesidad de conocer el tema de la economía circular para la aplicación de la herramienta. Por lo tanto, se necesita capacitación antes de comenzar un nuevo estudio. Esto encarece la investigación en tiempo y recursos humanos.
Implicaciones prácticas
El aporte práctico y metodológico de este trabajo radica en la viabilidad de la herramienta que favorece la definición de acciones de mejora para la contribución de la implementación a la economía circular en las prácticas empresariales.
Implicaciones sociales
La contribución social es parte de la transición gradual a enfoques de economía circular en países subdesarrollados.
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Letizia Alvino, Rob van der Lubbe, Reinoud A.M. Joosten and Efthymios Constantinides
The purpose of this paper is to assess whether or not electroencephalography (EEG) provides a valuable and substantial contribution to the prediction of consumer behaviour and…
Abstract
Purpose
The purpose of this paper is to assess whether or not electroencephalography (EEG) provides a valuable and substantial contribution to the prediction of consumer behaviour and their preferences during product consumption. In this study, the authors especially focus on individual preferences during a wine tasting experience.
Design/methodology/approach
A consumer neuroscience experiment was carried out with 26 participants that evaluated different red wines while their brain activity was recorded with EEG. A within-subjects design was employed and the experiment was carried out in two sessions. All participants took part in a blind taste session (no label session), in which information about the wine was not disclosed, and a normal taste session (label session), during which the bottle and its label were visible.
Findings
The findings suggest that EEG is a useful tool to study brain activity during product experience. EEG has high temporal resolution, low costs, small dimensions and superior manoeuvrability compared to other consumer neuroscience tools. However, it is noticed that there is a lack of solid theoretical background regarding brain areas (e.g. frontal cortex) and brain activity (e.g. brain waves) related to consumer preferences during product experience. This lack of knowledge causes several difficulties in replicating and validating the findings of other consumer neuroscience experiments for studying consumer behaviour.
Originality/value
The experiment presented in this paper is an exploratory study. It provides insights into the possible contribution of EEG data to the prediction of consumer behaviour during product experience.
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Xinwei Guo and Yang Chen
Currently, the vision and depth information obtained from the eye-to-hand RGB-D camera can apply to the reconstruction of the three-dimensional (3D) environment for a robotic…
Abstract
Purpose
Currently, the vision and depth information obtained from the eye-to-hand RGB-D camera can apply to the reconstruction of the three-dimensional (3D) environment for a robotic operation workspace. The reconstructed 3D space contributes to a symmetrical and equal observation view for robots and humans, which can be considered a digital twin (DT) environment. The purpose of this study is to enhance the robot skill in the physical workspace, although the artificial intelligence (AI) technique has high performance of the robotic operation in the known environments.
Design/methodology/approach
A multimodal interaction framework is proposed in DT operation environments.
Findings
A fast image-based target segmentation technique is combined in the 3D reconstruction of the robotic operation environment from the eye-to-hand camera, thus expediting the 3D DT environment generation without accuracy loss. A multimodal interaction interface is integrated into the DT environment.
Originality/value
The users are supported to operate the virtual objects in the DT environment using speech, mouse and keyboard simultaneously. The humans’ operations in 3D DT virtual space are recorded, and cues are provided for the robot’s operations in practice.
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During the last two years the many conferences and congresses involving cybernetics have focused on particular research and development themes. Whether the venue was at Vienna …
Abstract
During the last two years the many conferences and congresses involving cybernetics have focused on particular research and development themes. Whether the venue was at Vienna (The Austrian Society for Cybernetic Studies), at Namur (The Association Internationale de Cybernétique), at Barcelona (The World Association of Cybernetics, Computer Science and System Theory, TAKIS) or in London, where the World Organisation of General Systems and Cybernetics held its Seventh International Congress of Cybernetics and Systems, the profile of the research and development contributions follows a common set of themes. The London Seventh Congress will be reviewed in some detail in Kybernetes and it will be seen that its aims were similar to those voiced at the six previous events in London, Oxford, Bucharest, Amsterdam, Mexico and Paris. The organisers identified these as being the development of the interdisciplinary sciences of cybernetics and systems without spurious accretions and exotic notions. Whatever the aims of the other cybernetics meetings they too form an international forum for the exchange of up‐to‐date information and the enhancement of contacts between scientists. At London the two hundred or so papers accepted for presentation reflected current work in fields ranging from artificial intelligence and automation to medical cybernetics and sociocybernetics.
Dong Zhu, Liping Hou, Mo Chen and Bocheng Bao
The purpose of this paper is to develop an field programmable gate array (FPGA)-based neuron circuit to mimic dynamical behaviors of tabu learning neuron model.
Abstract
Purpose
The purpose of this paper is to develop an field programmable gate array (FPGA)-based neuron circuit to mimic dynamical behaviors of tabu learning neuron model.
Design/methodology/approach
Numerical investigations for the tabu learning neuron model show the coexisting behaviors of bi-stability. To reproduce the numerical results by hardware experiments, a digitally FPGA-based neuron circuit is constructed by pure floating-point operations to guarantee high computational accuracy. Based on the common floating-point operators provided by Xilinx Vivado software, the specific functions used in the neuron model are designed in hardware description language programs. Thus, by using the fourth-order Runge-Kutta algorithm and loading the specific functions orderly, the tabu learning neuron model is implemented on the Xilinx FPGA board.
Findings
With the variation of the activation gradient, the initial-related coexisting attractors with bi-stability are found in the tabu learning neuron model, which are experimentally demonstrated by a digitally FPGA-based neuron circuit.
Originality/value
Without any piecewise linear approximations, a digitally FPGA-based neuron circuit is implemented using pure floating-point operations, from which the initial conditions-related coexisting behaviors are experimentally demonstrated in the tabu learning neuron model.
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