María José Pujol, Francisco A. Pujol, Fidel Aznar, Mar Pujol and Ramón Rizo
In this paper the authors aim to show the advantages of using the decomposition method introduced by Adomian to solve Emden's equation, a classical non‐linear equation that…
Abstract
Purpose
In this paper the authors aim to show the advantages of using the decomposition method introduced by Adomian to solve Emden's equation, a classical non‐linear equation that appears in the study of the thermal behaviour of a spherical cloud and of the gravitational potential of a polytropic fluid at hydrostatic equilibrium.
Design/methodology/approach
In their work, the authors first review Emden's equation and its possible solutions using the Frobenius and power series methods; then, Adomian polynomials are introduced. Afterwards, Emden's equation is solved using Adomian's decomposition method and, finally, they conclude with a comparison of the solution given by Adomian's method with the solution obtained by the other methods, for certain cases where the exact solution is known.
Findings
Solving Emden's equation for n in the interval [0, 5] is very interesting for several scientific applications, such as astronomy. However, the exact solution is known only for n=0, n=1 and n=5. The experiments show that Adomian's method achieves an approximate solution which overlaps with the exact solution when n=0, and that coincides with the Taylor expansion of the exact solutions for n=1 and n=5. As a result, the authors obtained quite satisfactory results from their proposal.
Originality/value
The main classical methods for obtaining approximate solutions of Emden's equation have serious computational drawbacks. The authors make a new, efficient numerical implementation for solving this equation, constructing iteratively the Adomian polynomials, which leads to a solution of Emden's equation that extends the range of variation of parameter n compared to the solutions given by both the Frobenius and the power series methods.
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Pilar Arques, Francisco A. Pujol, Faraón Llorens, Mar Pujol and Ramón Rizo
One of the main goals of vision systems is to recognize objects in real world to perform appropriate actions. This implies the ability of handling objects and, moreover, to know…
Abstract
Purpose
One of the main goals of vision systems is to recognize objects in real world to perform appropriate actions. This implies the ability of handling objects and, moreover, to know the relations between these objects and their environment in what we call scenes. Most of the time, navigation in unknown environments is difficult due to a lack of easily identifiable landmarks. Hence, in this work, some geometric features to identify objects are considered. Firstly, a Markov random field segmentation approach is implemented. Then, the key factor for the recognition is the calculation of the so‐called distance histograms, which relate the distances between the border points to the mass center for each object in a scene.
Design/methodology/approach
This work, first discusses the features to be analyzed in order to create a reliable database for a proper recognition of the objects in a scene. Then, a robust classification system is designed and finally some experiments are completed to show that the recognition system can be utilized in a real‐world operation.
Findings
The results of the experiments show that including this distance information improves significantly the final classification process.
Originality/value
This paper describes an object recognition scheme, where a set of histograms is included to the features vector. As is shown, the incorporation of this feature improves the robustness of the system and the recognition rate.
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Pilar Arques, Patricia Compañ, Rafael Molina, Mar Pujol and Ramón Rizo
Segmentation is an important topic in computer vision and image processing. In this paper, we sketch a scheme for a multiscale segmentation algorithm and prove its validity on…
Abstract
Segmentation is an important topic in computer vision and image processing. In this paper, we sketch a scheme for a multiscale segmentation algorithm and prove its validity on some real images. We propose an approach to the model based on MRF (Markov Random Field) as a systematic way for integrating constraints for robust image segmentation. To do that, robust features and their integration in the energy function, which directs the process, have been defined. In this approach, the image is first transformed to different scales to determine which one fits better to our purposes. Then, it is segmented into a set of disjoint regions, the adjacent graph (AG) is determined and a MRF model is defined on the corresponding AG. Robust features are incorporated to the energy function by means of clique functions and optimal segmentation is then achieved by finding a labeling configuration that minimizes the energy function using Simulated Annealing.
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Francisco Gallego, Faraón Llorens, Mar Pujol and Ramón Rizo
The main intention of this paper is to state the benefits of using online videogames as a research environment, where AI algorithms are improved by means of learning from…
Abstract
Purpose
The main intention of this paper is to state the benefits of using online videogames as a research environment, where AI algorithms are improved by means of learning from real‐human‐behaviour examples.
Design/methodology/approach
The manner of taking advantage from the flux of real‐human‐behaviour examples inside an online videogame is stated. Then Mad University, a prototype online videogame specifically conceived and developed for this purpose, is explained.
Findings
Human‐like AI in artificial algorithms can be boosted by means of a specific kind of online videogame called MMORPGs, used as a research environment.
Research limitations/implications
Mad University is a prototype videogame which has been developed to experiment with AI algorithms that aim to learn strategies in a generalized fashion. The next research step will be to improve Mad University and to put it to work with hundreds of players and then research and test the effectiveness of the AI algorithms.
Originality/value
This paper proposes a new way of testing and experimenting with AI algorithms in order to obtain more human‐like results, and claims to have attempted to develop a generalized learning method.
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Pilar Arques, Patricia Compañ, Rafael Molina, Mar Pujol and Ramon Rizo
In this work, we propose an approach to the model based on Markov random field (MRF) as a systematic way for integrating constraints for robust image segmentation. To do that…
Abstract
In this work, we propose an approach to the model based on Markov random field (MRF) as a systematic way for integrating constraints for robust image segmentation. To do that, robust features and their integration in the energy function, which directs the process, have been defined. The suitability of the method has been verified by comparing classic features with the robust ones. In this approach, the image is first segmented into a set of disjoint regions and the adjacent graph (AG) has been determined. This approach is applied by defining an MRF model on the corresponding AG. Robust features are incorporated to the energy function by means of clique functions, and optimal segmentation is then achieved by finding a labelling configuration, which minimizes the energy function using the simulated annealing.
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Volker Stocker, William Lehr and Georgios Smaragdakis
The COVID-19 pandemic has disrupted the ‘real’ world and substantially impacted the virtual world and thus the Internet ecosystem. It has caused a significant exogenous shock that…
Abstract
The COVID-19 pandemic has disrupted the ‘real’ world and substantially impacted the virtual world and thus the Internet ecosystem. It has caused a significant exogenous shock that offers a wealth of natural experiments and produced new data about broadband, clouds, and the Internet in times of crisis. In this chapter, we characterise and evaluate the evolving impact of the global COVID-19 crisis on traffic patterns and loads and the impact of those on Internet performance from multiple perspectives. While we place a particular focus on deriving insights into how we can better respond to crises and better plan for the post-COVID-19 ‘new normal’, we analyse the impact on and the responses by different actors of the Internet ecosystem across different jurisdictions. With a focus on the USA and Europe, we examine the responses of both public and private actors, with the latter including content and cloud providers, content delivery networks, and Internet service providers (ISPs). This chapter makes two contributions: first, we derive lessons learned for a future post-COVID-19 world to inform non-networking spheres and policy-making; second, the insights gained assist the networking community in better planning for the future.
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Jordi de San Eugenio Vela, Xavier Ginesta Portet, Marc Compte-Pujol, Joan Frigola-Reig and Cristina Fernández-Rovira
This paper aims to analyse the implications in terms of economic promotion and local development that ensue from the implementation of a strategy of agrarian branding in five…
Abstract
Purpose
This paper aims to analyse the implications in terms of economic promotion and local development that ensue from the implementation of a strategy of agrarian branding in five municipalities in the Baixa Tordera region (Catalonia, Spain).
Design/methodology/approach
The research follows a case study logic. First, five focus groups were designed and distributed by sectors of activity. Second, six in-depth interviews were scheduled with opinion leaders from the region. Finally, a survey open to all inhabitants was set up on the town councils’ websites.
Findings
The brand understood as a device removed from the connotations of indiscriminate marketing should guarantee the following elements in its deployment and implementation: knowledge, recognition, complicity, development and denomination of origin.
Practical implications
This research contributes to improve the management models of agrarian spaces, but it also helps expand the research background on studies on agrarian branding.
Originality/value
The place brand must become something close to a denomination of origin that, informally, invites us to define the future of this agrarian area. It therefore also affects the complexity of the planning and development of this area which, from now on, must necessarily be supramunicipal. In this way, the brand needs to offer a holistic vision of the region to all the agents that work in the strategic and urban planning of the five municipalities under study.
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Manuel F. Suárez‐Barraza, Juan Ramis‐Pujol and Mariana Estrada‐Robles
The Gemba‐Kaizen approach is a key business process strategy employed by companies (multinationals also) to enhance their manufacturing performance. However, whilst there is…
Abstract
Purpose
The Gemba‐Kaizen approach is a key business process strategy employed by companies (multinationals also) to enhance their manufacturing performance. However, whilst there is significant research information available on implementing management systems in a sequential manner, there is little information available relating to the application of this approach to provide a single and highly effective methodology for process innovation in the context of the Gemba‐Kaizen approach in multinational companies. Therefore, the purpose of this paper is to develop and apply a process innovation framework in terms of methodology for multinational companies. The research question that governs the study is: How is the Gemba‐Kaizen approach applied in an organisational context such as that of a multinational food company in Mexico?
Design/methodology/approach
An exploratory case study was conducted. One multinational food company (chocolate) which has been established in Mexico for at least 19 years was selected. The paper chronicles the design and application of a process innovation framework in the context of the Gemba‐Kaizen approach. In total, four methods were used to gather data: direct observation; participative observation; documentary analysis; and semi‐structured interviews.
Findings
This paper proposes a process innovation framework using the Gemba‐Kaizen approach. The development, refinement and implementation of a process innovation framework in the context of the Gemba‐Kaizen approach has been achieved, working closely with a multinational food company. Consequently, as a result of the application, a conceptual framework was established, based on the results of comparing theory and fieldwork: this provides a glimpse into the relationship of the Gemba‐Kaizen approach with other improvement methodologies, known as Process Redesign, in the organisation analysed.
Practical implications
Derived to describe the case study on how to apply the Gemba‐Kaizen approach through process innovation methodology, the paper may prove to be of value to practitioners and managers involved in the field. Similarly, a section on managerial implications has also been included.
Originality/value
The paper contributes to the limited existing literature on the Gemba‐Kaizen system and subsequently disseminates this information in order to provide impetus, guidance and support towards increasing the development of companies, in an attempt to move the Mexico manufacturing (food) sector towards world‐class manufacturing performance.
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Gail Gilchrist, Alicia Blázquez and Marta Torrens
This paper's aim is to examine the relationship between intimate partner violence, childhood abuse and psychiatric disorders among 118 female drug users in treatment in Barcelona…
Abstract
Purpose
This paper's aim is to examine the relationship between intimate partner violence, childhood abuse and psychiatric disorders among 118 female drug users in treatment in Barcelona, Spain.
Design/methodology/approach
Secondary analysis of a cross‐sectional study of the psychiatric, behavioural and social risk factors for HIV. DSM‐IV disorders were assessed using the Spanish Psychiatric Research Interview for Substance and Mental Disorders; the Composite Abuse Scale assessed intimate partner violence and the Child Maltreatment History Self‐Report assessed childhood physical and sexual abuse.
Findings
The odds of experiencing intimate partner violence were 2.42 times greater among those with any depressive disorder (95 per cent CI 1.13, 5.20), over three times greater for those who reported ever attempting suicide (OR 3.20; 95 per cent CI 1.29, 7.94), met criteria for borderline personality disorder (OR 3.05; 95 per cent CI 1.31, 7.11), had been abused in childhood (OR 3.38; 95 per cent CI 1.45, 7.85) or currently lived with a substance user (OR 3.74; 95 per cent CI 1.29, 10.84). In multiple logistic regression, only living with a substance user (OR 3.42; 95 per cent CI 1.08, 10.86) and a history of childhood abuse (OR 2.87; 95 per cent CI 1.05, 7.86) remained significant in the model examining intimate partner violence victimisation.
Research limitations/implications
The small sample size, together with the fact that the study was not originally powered to examine differences in intimate partner violence may have increased the possibility of type II errors.
Originality/value
Histories of psychiatric disorders, intimate partner violence and childhood abuse are common in female substance users in treatment. Research suggests that such histories result in poorer treatment outcomes. Histories of intimate partner violence and childhood abuse should be identified and addressed in substance abuse treatment to enhance treatment outcomes.