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Angel P. del Pobil
University Jaume-I, Castellon, Spain

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Journal article
Published: 30 July 2021 in Journal of Retailing and Consumer Services
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Finding motivations for customer brand loyalty is one of the most popular academic and practical research fields; in this regard, some scholars have explored motivations in the retail industry. As the concept of private brands has been one of the most widely employed strategies for business success in the industry, comparing private and national brands in terms of customer loyalty is an important topic in the retail industry. Thus, the current research focuses on exploring antecedents of customer loyalty in private and national brands, as well as investigating whether there are notable structural differences between the brands. The results, based on 1,631 responses, indicate that customer perceived service/product quality, satisfaction, trust, and cost are notable determinants of brand loyalty, while the relationship between customer satisfaction and service quality of private brands is not supported. Moreover, both indirect and direct effects of the employed factors on customer brand loyalty are reported.

ACS Style

Syjung Hwang; Minyoung Lee; Eunil Park; Angel P. del Pobil. Determinants of customer brand loyalty in the retail industry: A comparison between national and private brands in South Korea. Journal of Retailing and Consumer Services 2021, 63, 102684 .

AMA Style

Syjung Hwang, Minyoung Lee, Eunil Park, Angel P. del Pobil. Determinants of customer brand loyalty in the retail industry: A comparison between national and private brands in South Korea. Journal of Retailing and Consumer Services. 2021; 63 ():102684.

Chicago/Turabian Style

Syjung Hwang; Minyoung Lee; Eunil Park; Angel P. del Pobil. 2021. "Determinants of customer brand loyalty in the retail industry: A comparison between national and private brands in South Korea." Journal of Retailing and Consumer Services 63, no. : 102684.

Journal article
Published: 23 June 2021 in Applied Sciences
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Commercially viable automated picking in unstructured environments by a robot arm remains a difficult challenge. The problem of robot grasp planning has long been around but the existing solutions tend to be limited when it comes to deploy them in open-ended realistic scenarios. Practical picking systems are called for that can handle the different properties of the objects to be manipulated, as well as the problems arising from occlusions and constrained accessibility. This paper presents a practical solution to the problem of robot picking in an online shopping warehouse by means of a novel approach that integrates a carefully selected method with a new strategy, the centroid normal approach (CNA), on a cost-effective dual-arm robotic system with two grippers specifically designed for this purpose: a two-finger gripper and a vacuum gripper. Objects identified in the scene point cloud are matched to the grasping techniques and grippers to maximize success. Extensive experimentation provides clues as to what are the reasons for success and failure. We chose as benchmark the scenario proposed by the 2017 Amazon Robotics Challenge, since it represents a realistic description of a retail shopping warehouse case; it includes many challenging constraints, such as a wide variety of different product items with a diversity of properties, which are also presented with restricted visibility and accessibility.

ACS Style

Nataliya Nechyporenko; Antonio Morales; Enric Cervera; Angel del Pobil. A Practical Approach for Picking Items in an Online Shopping Warehouse. Applied Sciences 2021, 11, 5805 .

AMA Style

Nataliya Nechyporenko, Antonio Morales, Enric Cervera, Angel del Pobil. A Practical Approach for Picking Items in an Online Shopping Warehouse. Applied Sciences. 2021; 11 (13):5805.

Chicago/Turabian Style

Nataliya Nechyporenko; Antonio Morales; Enric Cervera; Angel del Pobil. 2021. "A Practical Approach for Picking Items in an Online Shopping Warehouse." Applied Sciences 11, no. 13: 5805.

Journal article
Published: 19 February 2021 in Sensors
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Deep learning is the mainstream paradigm in computer vision and machine learning, but performance is usually not as good as expected when used for applications in robot vision. The problem is that robot sensing is inherently active, and often, relevant data is scarce for many application domains. This calls for novel deep learning approaches that can offer a good performance at a lower data consumption cost. We address here monocular depth estimation in warehouse automation with new methods and three different deep architectures. Our results suggest that the incorporation of sensor models and prior knowledge relative to robotic active vision, can consistently improve the results and learning performance from fewer than usual training samples, as compared to standard data-driven deep learning.

ACS Style

Ryota Yoneyama; Angel Duran; Angel del Pobil. Integrating Sensor Models in Deep Learning Boosts Performance: Application to Monocular Depth Estimation in Warehouse Automation. Sensors 2021, 21, 1437 .

AMA Style

Ryota Yoneyama, Angel Duran, Angel del Pobil. Integrating Sensor Models in Deep Learning Boosts Performance: Application to Monocular Depth Estimation in Warehouse Automation. Sensors. 2021; 21 (4):1437.

Chicago/Turabian Style

Ryota Yoneyama; Angel Duran; Angel del Pobil. 2021. "Integrating Sensor Models in Deep Learning Boosts Performance: Application to Monocular Depth Estimation in Warehouse Automation." Sensors 21, no. 4: 1437.

Journal article
Published: 04 February 2021 in Sensors
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Over time, the field of robotics has provided solutions to automate routine tasks in different scenarios. In particular, libraries are awakening great interest in automated tasks since they are semi-structured environments where machines coexist with humans and several repetitive operations could be automatically performed. In addition, multirotor aerial vehicles have become very popular in many applications over the past decade, however autonomous flight in confined spaces still presents a number of challenges and the use of small drones has not been reported as an automated inventory device within libraries. This paper presents the UJI aerial librarian robot that leverages computer vision techniques to autonomously self-localize and navigate in a library for automated inventory and book localization. A control strategy to navigate along the library bookcases is presented by using visual markers for self-localization during a visual inspection of bookshelves. An image-based book recognition technique is described that combines computer vision techniques to detect the tags on the book spines, followed by an optical character recognizer (OCR) to convert the book code on the tags into text. These data can be used for library inventory. Misplaced books can be automatically detected, and a particular book can be located within the library. Our quadrotor robot was tested in a real library with promising results. The problems encountered and limitation of the system are discussed, along with its relation to similar applications, such as automated inventory in warehouses.

ACS Style

Ester Martinez-Martin; Eric Ferrer; Ilia Vasilev; Angel del Pobil. The UJI Aerial Librarian Robot: A Quadcopter for Visual Library Inventory and Book Localisation. Sensors 2021, 21, 1079 .

AMA Style

Ester Martinez-Martin, Eric Ferrer, Ilia Vasilev, Angel del Pobil. The UJI Aerial Librarian Robot: A Quadcopter for Visual Library Inventory and Book Localisation. Sensors. 2021; 21 (4):1079.

Chicago/Turabian Style

Ester Martinez-Martin; Eric Ferrer; Ilia Vasilev; Angel del Pobil. 2021. "The UJI Aerial Librarian Robot: A Quadcopter for Visual Library Inventory and Book Localisation." Sensors 21, no. 4: 1079.

Journal article
Published: 12 January 2021 in International Journal of Environmental Research and Public Health
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Non-communicable diseases (NCDs) are one of the major health threats in the world. Thus, identifying the factors that influence NCDs is crucial to monitor and manage diseases. This study investigates the effects of social-environmental and behavioral risk factors on NCDs as well as the effects of social-environmental factors on behavioral risk factors using an integrated research model. This study used a dataset from the 2017 Korea National Health and Nutrition Examination Survey. After filtering incomplete responses, 5462 valid responses remained. Items including one’s social-environmental factors (household income, education level, and region), behavioral factors (alcohol use, tobacco use, and physical activity), and NCDs histories were used for analyses. To develop a comprehensive index of each factor that allows comparison between different concepts, the researchers assigned scores to indicators of the factors and calculated a ratio of the scores. A series of path analyses were conducted to determine the extent of relationships among NCDs and risk factors. The results showed that social-environmental factors have notable effects on stroke, myocardial infarction, angina, diabetes, and gastric, liver, colon, lung, and thyroid cancers. The results indicate that the effects of social-environmental and behavioral risk factors on NCDs vary across the different types of diseases. The effects of social-environmental factors and behavioral risk factors significantly affected NCDs. However, the effect of social-environmental factors on behavioral risk factors was not supported. Furthermore, social-environmental factors and behavioral risk factors affect NCDs in a similar way. However, the effects of behavioral risk factors were smaller than those of social-environmental factors. The current research suggests taking a comprehensive view of risk factors to further understand the antecedents of NCDs in South Korea.

ACS Style

Nam Jeong Jeong; Eunil Park; Angel P. Del Pobil. Effects of Behavioral Risk Factors and Social-Environmental Factors on Non-Communicable Diseases in South Korea: A National Survey Approach. International Journal of Environmental Research and Public Health 2021, 18, 612 .

AMA Style

Nam Jeong Jeong, Eunil Park, Angel P. Del Pobil. Effects of Behavioral Risk Factors and Social-Environmental Factors on Non-Communicable Diseases in South Korea: A National Survey Approach. International Journal of Environmental Research and Public Health. 2021; 18 (2):612.

Chicago/Turabian Style

Nam Jeong Jeong; Eunil Park; Angel P. Del Pobil. 2021. "Effects of Behavioral Risk Factors and Social-Environmental Factors on Non-Communicable Diseases in South Korea: A National Survey Approach." International Journal of Environmental Research and Public Health 18, no. 2: 612.

Journal article
Published: 20 June 2020 in Telematics and Informatics
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Considering the rapidly improving technologies in artificial intelligence (AI), researchers in mass communication and journalism have paid attention to the use of AI technologies. However, there are still notable concerns about the particular use of AI technologies in this field. Put simply, can AI technologies reduce human tasks? In order to address this question, this study investigates the effects of content generators (human vs. AI) and information delivery methods (text vs. audio vs. video) on users’ perceptions of content. The results indicate that the generators and methods play a notable role in eliciting greater quality, satisfaction, and readability of the content. Based on the findings, the implications are addressed.

ACS Style

Jina Kim; Soyeon Shin; Kunwoo Bae; Soyoung Oh; Eunil Park; Angel P. del Pobil. Can AI be a content generator? Effects of content generators and information delivery methods on the psychology of content consumers. Telematics and Informatics 2020, 55, 101452 .

AMA Style

Jina Kim, Soyeon Shin, Kunwoo Bae, Soyoung Oh, Eunil Park, Angel P. del Pobil. Can AI be a content generator? Effects of content generators and information delivery methods on the psychology of content consumers. Telematics and Informatics. 2020; 55 ():101452.

Chicago/Turabian Style

Jina Kim; Soyeon Shin; Kunwoo Bae; Soyoung Oh; Eunil Park; Angel P. del Pobil. 2020. "Can AI be a content generator? Effects of content generators and information delivery methods on the psychology of content consumers." Telematics and Informatics 55, no. : 101452.

Journal article
Published: 05 June 2019 in Applied Sciences
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In some countries, renewable energy resources have become one of the mainstreams of energy savings and sustainable development. Thailand is one of the major countries to use renewable energy generation facilities in public buildings. In particular, public educational institutes consume large amounts of electricity from the grid. To reduce the electricity dependency on the national grid connection and greenhouse gas emissions, this paper introduces potential optimized solutions of renewable energy generation systems for a public university in Thailand, Chiang Mai University. Based on the simulation results from HOMER software, the potential configuration organized by PV panels, batteries and converters is proposed. The suggested configuration achieves 100% of the renewable fraction with $0.728 of the cost of energy for per electricity. Moreover, the greenhouse gas emissions are significantly reduced. Both the implications and limitations are presented based on simulation results.

ACS Style

Eunil Park; Sang Jib Kwon; Angel P. Del Pobil. Can Large Educational Institutes Become Free from Grid Systems? Determination of Hybrid Renewable Energy Systems in Thailand. Applied Sciences 2019, 9, 2319 .

AMA Style

Eunil Park, Sang Jib Kwon, Angel P. Del Pobil. Can Large Educational Institutes Become Free from Grid Systems? Determination of Hybrid Renewable Energy Systems in Thailand. Applied Sciences. 2019; 9 (11):2319.

Chicago/Turabian Style

Eunil Park; Sang Jib Kwon; Angel P. Del Pobil. 2019. "Can Large Educational Institutes Become Free from Grid Systems? Determination of Hybrid Renewable Energy Systems in Thailand." Applied Sciences 9, no. 11: 2319.

Journal article
Published: 06 April 2019 in Sensors
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Advances in Robotics are leading to a new generation of assistant robots working in ordinary, domestic settings. This evolution raises new challenges in the tasks to be accomplished by the robots. This is the case for object manipulation where the detect-approach-grasp loop requires a robust recovery stage, especially when the held object slides. Several proprioceptive sensors have been developed in the last decades, such as tactile sensors or contact switches, that can be used for that purpose; nevertheless, their implementation may considerably restrict the gripper's flexibility and functionality, increasing their cost and complexity. Alternatively, vision can be used since it is an undoubtedly rich source of information, and in particular, depth vision sensors. We present an approach based on depth cameras to robustly evaluate the manipulation success, continuously reporting about any object loss and, consequently, allowing it to robustly recover from this situation. For that, a Lab-colour segmentation allows the robot to identify potential robot manipulators in the image. Then, the depth information is used to detect any edge resulting from two-object contact. The combination of those techniques allows the robot to accurately detect the presence or absence of contact points between the robot manipulator and a held object. An experimental evaluation in realistic indoor environments supports our approach.

ACS Style

Ester Martinez-Martin; Angel P. Del Pobil. Vision for Robust Robot Manipulation. Sensors 2019, 19, 1648 .

AMA Style

Ester Martinez-Martin, Angel P. Del Pobil. Vision for Robust Robot Manipulation. Sensors. 2019; 19 (7):1648.

Chicago/Turabian Style

Ester Martinez-Martin; Angel P. Del Pobil. 2019. "Vision for Robust Robot Manipulation." Sensors 19, no. 7: 1648.

Conference paper
Published: 31 December 2018 in Advances in Intelligent Systems and Computing
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The purpose of this study is to investigate the most effective methodologies for the grasping of items in an environment where success, robustness and time of the algorithmic computation and its implementation are key constraints. The study originates from the Amazon Robotics Challenge 2017 (ARC’17) which aims to automate the picking process in online shopping warehouses where the robot has to deal with real world problems of restricted visibility and accessibility. A two-finger and a vacuum grippers were chosen for their practicality and ubiquity in industry. The proposed solution to grasping was retrieval of a final position and orientation of the end effector using an Xbox 360 Kinect sensor information of the object. Antipodal Grasp Identification and Learning (AGILE) and Height Accumulated Features (HAF) feature based methods were chosen for implementation on the two finger gripper due to their ease of applicability, same type of input, and reportedly high success rate. A comparison of these methods was done.

ACS Style

Nataliya Nechyporenko; Antonio Morales; Angel P. Del Pobil. Grasping Strategies for Picking Items in an Online Shopping Warehouse. Advances in Intelligent Systems and Computing 2018, 775 -785.

AMA Style

Nataliya Nechyporenko, Antonio Morales, Angel P. Del Pobil. Grasping Strategies for Picking Items in an Online Shopping Warehouse. Advances in Intelligent Systems and Computing. 2018; ():775-785.

Chicago/Turabian Style

Nataliya Nechyporenko; Antonio Morales; Angel P. Del Pobil. 2018. "Grasping Strategies for Picking Items in an Online Shopping Warehouse." Advances in Intelligent Systems and Computing , no. : 775-785.

Conference paper
Published: 31 December 2018 in Advances in Intelligent Systems and Computing
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Nowadays, robots are more and more autonomous, they are able to investigate autonomously the surrounding environment, take decisions, and, of course, accomplish elaborated tasks receiving simple inputs by users. Generally, every robot has to move to interact with the environment and human users replicating human-like motions and decisions. The literature already gives a lot of documentation about mobile/flying robots spanning paths in 2D and 3D environments, while the motion of articulated arms in 3D environments still requires investigation and experiments. This paper investigates MoveIt!, one of the most famous motion planner software, understanding its limits and trying to extend its capabilities. Integrating another planner with MoveIt!’s planning routine to split longer actions into smaller ones increases planning robustness. Due to the participation to Amazon Robotics Challenge 2017, every experiment has been carried on in automatic packing line scenarios, in which Baxter, a humanoid robot sporting two 7 DOF arms, had to perform actions avoiding known obstacles.

ACS Style

Emanuele Sansebastiano; Angel P. Del Pobil. Multiple Path Planner Integration for Obstacle Avoidance: MoveIt! and Potential Field Planner Synergy. Advances in Intelligent Systems and Computing 2018, 78 -85.

AMA Style

Emanuele Sansebastiano, Angel P. Del Pobil. Multiple Path Planner Integration for Obstacle Avoidance: MoveIt! and Potential Field Planner Synergy. Advances in Intelligent Systems and Computing. 2018; ():78-85.

Chicago/Turabian Style

Emanuele Sansebastiano; Angel P. Del Pobil. 2018. "Multiple Path Planner Integration for Obstacle Avoidance: MoveIt! and Potential Field Planner Synergy." Advances in Intelligent Systems and Computing , no. : 78-85.

Journal article
Published: 28 September 2018 in Robotics and Autonomous Systems
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The estimation of the internal model of a robotic system results from the interaction of its morphology, sensors and actuators, with a particular environment. Model learning techniques, based on supervised machine learning, are widespread for determining the internal model. An important limitation of such approaches is that once a model has been learnt, it does not behave properly when the robot morphology is changed. From this it follows that there must exist a relationship between them. We propose a model for this correlation between the morphology and the internal model parameters, so that a new internal model can be predicted when the morphological parameters are modified. Different neural network architectures are proposed to address this high dimensional regression problem. A case study is analyzed in detail to illustrate and evaluate the performance of the approach, namely, a pan–tilt robot head executing saccadic movements. The best results are obtained for an architecture with parallel neural networks. Our results can be instrumental in state-of-the-art trends such as self-reconfigurable robots, reproducible research, cyber-physical robotic systems or cloud robotics, in which internal models would available as shared knowledge, so that robots with different morphologies can readily exhibit a particular behavior in a given environment.

ACS Style

Angel J. Duran; Angel P. Del Pobil. Predicting the internal model of a robotic system from its morphology. Robotics and Autonomous Systems 2018, 110, 33 -43.

AMA Style

Angel J. Duran, Angel P. Del Pobil. Predicting the internal model of a robotic system from its morphology. Robotics and Autonomous Systems. 2018; 110 ():33-43.

Chicago/Turabian Style

Angel J. Duran; Angel P. Del Pobil. 2018. "Predicting the internal model of a robotic system from its morphology." Robotics and Autonomous Systems 110, no. : 33-43.

Journal article
Published: 25 September 2018 in Applied Sciences
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Since the importance and effects of national energy policies, plans, and roadmaps were presented in South Korea, the role of renewable energy resources has received great attention. Moreover, as there is significant reasoning for reducing and minimizing nuclear and fossil fuel usage in South Korean national energy plans, several academic scholars and implementers have expended significant effort to present the potential and feasibility of renewable energy resources in South Korea. This study contributes to these efforts by presenting potential sustainable configurations of renewable energy production facilities for a public building in South Korea. Based on economic, environmental, and technical information as well as the presented simulation results, it proposes an environmentally friendly renewable energy production facility configuration that consists of photovoltaic arrays, battery units, and a converter. Subsidies for installing and renovating such facilities are also considered. The potential configuration indicates $0.464 as the cost of energy, 100% of which is renewable. Potential limitations and future research areas are suggested based on the results of these simulations.

ACS Style

Eunil Park; Angel P. Del Pobil. Eco-Friendly Education Facilities: The Case of a Public Education Building in South Korea. Applied Sciences 2018, 8, 1733 .

AMA Style

Eunil Park, Angel P. Del Pobil. Eco-Friendly Education Facilities: The Case of a Public Education Building in South Korea. Applied Sciences. 2018; 8 (10):1733.

Chicago/Turabian Style

Eunil Park; Angel P. Del Pobil. 2018. "Eco-Friendly Education Facilities: The Case of a Public Education Building in South Korea." Applied Sciences 8, no. 10: 1733.

Research article
Published: 23 August 2018 in Computational Intelligence and Neuroscience
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Aimed at building autonomous service robots, reasoning, perception, and action should be properly integrated. In this paper, the depth cue has been analysed as an early stage given its importance for robotic tasks. So, from neuroscience findings, a hierarchical four-level dorsal architecture has been designed and implemented. Mainly, from a stereo image pair, a set of complex Gabor filters is applied for estimating an egocentric quantitative disparity map. This map leads to a quantitative depth scene representation that provides the raw input for a qualitative approach. So, the reasoning method infers the data required to make the right decision at any time. As it will be shown, the experimental results highlight the robust performance of the biologically inspired approach presented in this paper.

ACS Style

Ester Martinez-Martin; Angel P. Del Pobil. A Biologically Inspired Approach for Robot Depth Estimation. Computational Intelligence and Neuroscience 2018, 2018, 1 -16.

AMA Style

Ester Martinez-Martin, Angel P. Del Pobil. A Biologically Inspired Approach for Robot Depth Estimation. Computational Intelligence and Neuroscience. 2018; 2018 ():1-16.

Chicago/Turabian Style

Ester Martinez-Martin; Angel P. Del Pobil. 2018. "A Biologically Inspired Approach for Robot Depth Estimation." Computational Intelligence and Neuroscience 2018, no. : 1-16.

Journal article
Published: 01 May 2018 in Sustainability
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Since the concept of a smart city was introduced, IoT (Internet of Things) has beenconsidered the key infrastructure in a smart city. However, there are currently no detailed explanations of the technical contributions of IoT in terms of the management, development, and improvements of smart cities. Therefore, the current study describes the importance of IoT technologies on the technology roadmap (TRM) of a smart city. Moreover, the survey with about 200 experts was conducted to investigate both the importance and essentiality of detail components of IoT technologies for a smart city. Based on the survey results, the focal points and essential elements for the successful developments of a smart city are presented.

ACS Style

Eunil Park; Angel P. Del Pobil; Sang Jib Kwon. The Role of Internet of Things (IoT) in Smart Cities: Technology Roadmap-oriented Approaches. Sustainability 2018, 10, 1388 .

AMA Style

Eunil Park, Angel P. Del Pobil, Sang Jib Kwon. The Role of Internet of Things (IoT) in Smart Cities: Technology Roadmap-oriented Approaches. Sustainability. 2018; 10 (5):1388.

Chicago/Turabian Style

Eunil Park; Angel P. Del Pobil; Sang Jib Kwon. 2018. "The Role of Internet of Things (IoT) in Smart Cities: Technology Roadmap-oriented Approaches." Sustainability 10, no. 5: 1388.

Conference paper
Published: 11 February 2017 in Advances in Intelligent Systems and Computing
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Supervised machine learning techniques have proven very effective to solve the problems arising from model learning in robotics. A significant limitation of such approaches is that internal models learned for a specific robot are likely to fail when transferred to a robot with a different morphology. One of the challenges to relate the morphology and the internal model is the difference in the number of parameters that define them. We propose three neural network architectures for solving this problem, along with a case study to evaluate their performance, namely saccadic movements in a robotic head. We generate a huge dataset to test the performance of the proposed architectures. Our results suggest that the best solution is provided by the parallel neural network, due to the fact that the trained weights are independent of one another.

ACS Style

Angel J. Duran; Angel P. Del Pobil. Discovering the Relationship Between the Morphology and the Internal Model in a Robot System by Means of Neural Networks. Advances in Intelligent Systems and Computing 2017, 531, 839 -852.

AMA Style

Angel J. Duran, Angel P. Del Pobil. Discovering the Relationship Between the Morphology and the Internal Model in a Robot System by Means of Neural Networks. Advances in Intelligent Systems and Computing. 2017; 531 ():839-852.

Chicago/Turabian Style

Angel J. Duran; Angel P. Del Pobil. 2017. "Discovering the Relationship Between the Morphology and the Internal Model in a Robot System by Means of Neural Networks." Advances in Intelligent Systems and Computing 531, no. : 839-852.

Conference paper
Published: 10 August 2016 in Natural Computing Series
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The genes of living organisms serve as large stores of information for replicating their behavior and morphology over generations. The evolutionary view of genetics that has inspired artificial systems with a Mendelian approach does not take into account the interaction between species and with the environment to generate a particular phenotype. In this paper, a genotype model is suggested to shape the relationship with the phenotype and the environment in an artificial system. A method to obtain a genotype from a population of a particular robotic system is also proposed. Finally, we show that this model presents a similar behavior to that of living organisms in what regards the concept of norm of reaction.This paper describes research done at the UJI Robotic Intelligence Laboratory. Support for this laboratory is provided in part by Ministerio de Econom´ıa y Competitividad (DPI2015-69041-R), by Generalitat Valenciana (PROMETEOII/2014/028) and by Universitat Jaume I (P1-1B2014-52, PREDOC/ 2013/06)

ACS Style

Angel J. Duran; Angel P. Del Pobil. A Model of Artificial Genotype and Norm of Reaction in a Robotic System. Natural Computing Series 2016, 267 -279.

AMA Style

Angel J. Duran, Angel P. Del Pobil. A Model of Artificial Genotype and Norm of Reaction in a Robotic System. Natural Computing Series. 2016; ():267-279.

Chicago/Turabian Style

Angel J. Duran; Angel P. Del Pobil. 2016. "A Model of Artificial Genotype and Norm of Reaction in a Robotic System." Natural Computing Series , no. : 267-279.

Journal article
Published: 01 September 2015 in Sustainability
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Since the introduction of corporate social responsibility (CSR), it has become an important duty of companies and organizations. In addition, academic and industry researchers have attempted to explore the effects of corporate social responsibility on firm performance. To this end, this study examined how corporate social responsibility and service quality are notably associated with customer satisfaction and behavioral intention to use by employing a structural equation modeling method. A research model with nine constructs was introduced and the findings revealed that economic, social, and environmental responsibility, as well as in-flight service quality, significantly determined customer satisfaction, while there were notable connections between customer satisfaction and behavioral intention to use. However, service quality at airports did not have a significant effect on satisfaction. The practical and theoretical implications of the current study are discussed.

ACS Style

Eunil Park; Sanghoon Lee; Sang Jib Kwon; Angel P. Del Pobil. Determinants of Behavioral Intention to Use South Korean Airline Services: Effects of Service Quality and Corporate Social Responsibility. Sustainability 2015, 7, 12106 -12121.

AMA Style

Eunil Park, Sanghoon Lee, Sang Jib Kwon, Angel P. Del Pobil. Determinants of Behavioral Intention to Use South Korean Airline Services: Effects of Service Quality and Corporate Social Responsibility. Sustainability. 2015; 7 (9):12106-12121.

Chicago/Turabian Style

Eunil Park; Sanghoon Lee; Sang Jib Kwon; Angel P. Del Pobil. 2015. "Determinants of Behavioral Intention to Use South Korean Airline Services: Effects of Service Quality and Corporate Social Responsibility." Sustainability 7, no. 9: 12106-12121.

Journal article
Published: 20 August 2015 in Sustainability
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The concepts of corporate social responsibility (CSR) and user experience have been identified as core determinants of the success of service providers. Accordingly, practitioners and researchers have investigated the effects of service providers’ CSR and user experience on behavioral intention to use a particular service. Based on the importance of these concepts, the current study integrates subjective dimensions of CSR with the technology acceptance model (TAM) to explore whether the CSR efforts of mobile telecommunication services providers and the service acceptance of their customers have significant effects on behavioral intention to use a service. We apply structural equation modeling and find that two factors from the TAM (i.e., usefulness and ease of use) as well as economic, social, and environmental responsibility are significantly related to customer attitude and satisfaction. Moreover, our results show that there are significantly positive relationships between customer attitude and behavioral intention to use a service, as well as between customer satisfaction and intention. Practical and theoretical implications along with notable limitations of the current study are presented.

ACS Style

Sanghoon Lee; Eunil Park; Sang Jib Kwon; Angel P. Del Pobil. Antecedents of Behavioral Intention to Use Mobile Telecommunication Services: Effects of Corporate Social Responsibility and Technology Acceptance. Sustainability 2015, 7, 11345 -11359.

AMA Style

Sanghoon Lee, Eunil Park, Sang Jib Kwon, Angel P. Del Pobil. Antecedents of Behavioral Intention to Use Mobile Telecommunication Services: Effects of Corporate Social Responsibility and Technology Acceptance. Sustainability. 2015; 7 (8):11345-11359.

Chicago/Turabian Style

Sanghoon Lee; Eunil Park; Sang Jib Kwon; Angel P. Del Pobil. 2015. "Antecedents of Behavioral Intention to Use Mobile Telecommunication Services: Effects of Corporate Social Responsibility and Technology Acceptance." Sustainability 7, no. 8: 11345-11359.

Book chapter
Published: 20 June 2015 in Machine Learning for the Quantified Self
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This chapter describes how we model the integration of on-line, action-oriented visual information (dorsal pathway) with knowledge about the target object and memories of previous grasping experiences and object characteristics (ventral pathway). Previous models of vision-based grasping have built so far mainly, when not exclusively, on monkey data. Recent neuropsychological and neuroimaging research has shed a new light on how visuomotor coordination is organized and performed in the human brain. Thanks to such research, a model of vision-based grasping which integrates knowledge coming from single-cell monkey studies with human data can be developed. The basic framework of the proposed model is outlined in this chapter. Final goal of the proposal is to mimic, in a robotic setup, the coordination between sensory, associative and motor cortex of the human brain in vision-based grasping actions.

ACS Style

Eris Chinellato; Angel P. del Pobil. Vision-Based Grasping, Where Robotics Meets Neuroscience. Machine Learning for the Quantified Self 2015, 57 -81.

AMA Style

Eris Chinellato, Angel P. del Pobil. Vision-Based Grasping, Where Robotics Meets Neuroscience. Machine Learning for the Quantified Self. 2015; ():57-81.

Chicago/Turabian Style

Eris Chinellato; Angel P. del Pobil. 2015. "Vision-Based Grasping, Where Robotics Meets Neuroscience." Machine Learning for the Quantified Self , no. : 57-81.

Book chapter
Published: 20 June 2015 in Machine Learning for the Quantified Self
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This chapter describes how we model the integration of on-line, action-oriented visual information (dorsal pathway) with knowledge about the target object and memories of previous grasping experiences and object characteristics (ventral pathway). Previous models of vision-based grasping have built so far mainly, when not exclusively, on monkey data. Recent neuropsychological and neuroimaging research has shed a new light on how visuomotor coordination is organized and performed in the human brain. Thanks to such research, a model of vision-based grasping which integrates knowledge coming from single-cell monkey studies with human data can be developed. The basic framework of the proposed model is outlined in this chapter. Final goal of the proposal is to mimic, in a robotic setup, the coordination between sensory, associative and motor cortex of the human brain in vision-based grasping actions.

ACS Style

Eris Chinellato; Angel P. del Pobil. Extraction of Grasp-Related Visual Features. Machine Learning for the Quantified Self 2015, 83 -118.

AMA Style

Eris Chinellato, Angel P. del Pobil. Extraction of Grasp-Related Visual Features. Machine Learning for the Quantified Self. 2015; ():83-118.

Chicago/Turabian Style

Eris Chinellato; Angel P. del Pobil. 2015. "Extraction of Grasp-Related Visual Features." Machine Learning for the Quantified Self , no. : 83-118.