246 research outputs found

    Forward and Reverse Process Models for the Squeeze Casting Process Using Neural Network Based Approaches

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    The present research work is focussed to develop an intelligent system to establish the input-output relationship utilizing forward and reverse mappings of artificial neural networks. Forward mapping aims at predicting the density and secondary dendrite arm spacing (SDAS) from the known set of squeeze cast process parameters such as time delay, pressure duration, squeezes pressure, pouring temperature, and die temperature. An attempt is also made to meet the industrial requirements of developing the reverse model to predict the recommended squeeze cast parameters for the desired density and SDAS. Two different neural network based approaches have been proposed to carry out the said task, namely, back propagation neural network (BPNN) and genetic algorithm neural network (GA-NN). The batch mode of training is employed for both supervised learning networks and requires huge training data. The requirement of huge training data is generated artificially at random using regression equation derived through real experiments carried out earlier by the same authors. The performances of BPNN and GA-NN models are compared among themselves with those of regression for ten test cases. The results show that both models are capable of making better predictions and the models can be effectively used in shop floor in selection of most influential parameters for the desired outputs

    Casting Process Improvement by the Application of Artificial Intelligence

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    On the way to building smart factories as the vision of Industry 4.0, the casting process stands out as a specific manufacturing process due to its diversity and complexity. One of the segments of smart foundry design is the application of artificial intelligence in the improvement of the casting process. This paper presents an overview of the conducted research studies, which deal with the application of artificial intelligence in the improvement of the casting process. In the review, 37 studies were analyzed over the last 15 years, with a clear indication of the type of casting process, the field of application of artificial intelligence techniques, and the benefits that artificial intelligence brought. The goals of this paper are to bring to attention the great possibilities of the application of artificial intelligence for the improvement of manufacturing processes in foundries, and to encourage new ideas among researchers and engineers

    An Algorithmic Framework for Multiobjective Optimization

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    Multiobjective (MO) optimization is an emerging field which is increasingly being encountered in many fields globally. Various metaheuristic techniques such as differential evolution (DE), genetic algorithm (GA), gravitational search algorithm (GSA), and particle swarm optimization (PSO) have been used in conjunction with scalarization techniques such as weighted sum approach and the normal-boundary intersection (NBI) method to solve MO problems. Nevertheless, many challenges still arise especially when dealing with problems with multiple objectives (especially in cases more than two). In addition, problems with extensive computational overhead emerge when dealing with hybrid algorithms. This paper discusses these issues by proposing an alternative framework that utilizes algorithmic concepts related to the problem structure for generating efficient and effective algorithms. This paper proposes a framework to generate new high-performance algorithms with minimal computational overhead for MO optimization

    Review of Intelligent Control Systems with Robotics

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    Interactive between human and robot assumes a significant job in improving the productivity of the instrument in mechanical technology. Numerous intricate undertakings are cultivated continuously via self-sufficient versatile robots. Current automated control frameworks have upset the creation business, making them very adaptable and simple to utilize. This paper examines current and up and coming sorts of control frameworks and their execution in mechanical technology, and the job of AI in apply autonomy. It additionally expects to reveal insight into the different issues around the control frameworks and the various approaches to fix them. It additionally proposes the basics of apply autonomy control frameworks and various kinds of mechanical technology control frameworks. Each kind of control framework has its upsides and downsides which are talked about in this paper. Another kind of robot control framework that upgrades and difficulties the pursuit stage is man-made brainpower. A portion of the speculations utilized in man-made reasoning, for example, Artificial Intelligence (AI) such as fuzzy logic, neural network and genetic algorithm, are itemized in this paper. At long last, a portion of the joint efforts between mechanical autonomy, people, and innovation were referenced. Human coordinated effort, for example, Kinect signal acknowledgment utilized in games and versatile upper-arm-based robots utilized in the clinical field for individuals with inabilities. Later on, it is normal that the significance of different sensors will build, accordingly expanding the knowledge and activity of the robot in a modern domai

    Transdisciplinary Creative Ecologies in Contemporary Art within Emergent Processes

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    This research is composing in the moving with affective speeds and rhythms, instead of unfolding direct and in linear ways. It is important to come across different planes of composition in movement. There are so many planes of voices spinning around in relation. Research-creation seems as forms of relations and an invitation to appreciate the collectivity at the heart of thinking. The many entering-into relation within a differential thought in the making of its own. Emergent properties in non-human interactions, such as those presented in Steven Shaviro Ģs Against Self-Organization (2009) and Brain Massumi, are symptomatic of how individualities relate to creative tendencies in relation to the human, non-human dynamism, and emergence as a state or condition. Emergence can be co-joined around the notion of self-organization, ā€œthe spontaneous production of a level of reality having its own rules of formation and order of connectionā€ (Massumi, 2002). Self-organization emphasizes on matter-energy which Gilles Deleuze conceives of as the difference or line variation running through all things. Therefore, Deleuze focuses on immanence, how new forms are created, and on the ways in which material bodyings self-organize rather than being forced to do so. Moreover, the research in this dissertation seeks to generate a charged environment where human and non-human emergent processes activate creative encounters that co-create and co-shape each other (Delueze and Guattari, 2003; Stangers, 2017; Manning 2009). This study investigates how complexities and relations expand as an attractor of potentialities, that informs a matrix as movement, and recognizes nodes of the matrix as connections for such movements. My research is transdisciplinary, where experimental work interconnects art, science- zoology, architecture and process philosophy, and conjoins such with non-human emergent processes which are complex systems that activate intermodalities in their doing. These areas of research focus on, thread processes and transdisciplinary art doings.Textiles seen as intensities, transformations, movements, multiplicities of sensations experienced by familiar bodies in resonance with the world in acts of co-composing

    Opinions and Outlooks on Morphological Computation

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    Morphological Computation is based on the observation that biological systems seem to carry out relevant computations with their morphology (physical body) in order to successfully interact with their environments. This can be observed in a whole range of systems and at many different scales. It has been studied in animals ā€“ e.g., while running, the functionality of coping with impact and slight unevenness in the ground is "delivered" by the shape of the legs and the damped elasticity of the muscle-tendon system ā€“ and plants, but it has also been observed at the cellular and even at the molecular level ā€“ as seen, for example, in spontaneous self-assembly. The concept of morphological computation has served as an inspirational resource to build bio-inspired robots, design novel approaches for support systems in health care, implement computation with natural systems, but also in art and architecture. As a consequence, the field is highly interdisciplinary, which is also nicely reflected in the wide range of authors that are featured in this e-book. We have contributions from robotics, mechanical engineering, health, architecture, biology, philosophy, and others

    Are abstract concepts like dinosaur feathers? Objectification as a conceptual tool: evidence from language and gesture of English and Polish native speakers

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    Studies based on the Contemporary Theory of Metaphor (Lakoff & Johnson, 1980, 1999) usually identify conceptual metaphors by analysing linguistic expressions and creating a post hoc interpretation of the findings. This method has been questioned for a variety of reasons, including its circularity (MĆ¼ller, 2008), lack of falsifiability (Vervaeke & Kennedy, 1996, 2004), and lack of predictive power (Ritchie, 2003). It has been argued that CTM requires additional constraints to improve its applicability for empirical research (Gibbs, 2011; Ritchie, 2003). This paper sets out to propose additional methodological structure to CTM, a theory of conceptual metaphor in which much of abstract thought is generated by metaphorical mapping from embodied experience (Ruiz de Mendoza IbƔƱez & PĆ©rez HernĆ”ndez, 2011). Introducing Objectification Theory defined by Szwedek (2002, 2007, 2011) ameliorates a number of methodological issues in CTM. First, the embodiment claim of CTM in its current form cannot be empirically proven incorrect (Vervaeke & Kennedy, 2004) as any mapping within it is possible (although only some actually happen). Objectification introduces pre-metaphorical structure of the kind suggested by Glucksberg (2001), constraining source and target domain selection, predicting which mappings are more likely to happen. Second, while many claim that metaphors trace back to a literal concept based on embodied physical experience (Gibbs, Costa Lima, & Francozo, 2004), it is unclear what criteria are used to define ā€žphysicalā€. Metaphorical domains are often described using the terms ā€žabstractā€ and ā€žconcreteā€, Objectification proposes objective criteria for deciding whether a concept is experientially grounded. Finally, Objectification provides grounds for introducing a hierarchical framework for metaphor typology, preventing post-hoc addition of metaphor types if and when suitable for the explanation of a phenomenon; thus increasing the consistency of the CTM framework, both internally and with other cognitive science disciplines. This thesis focuses on providing evidence for Objectification Theory and identifying its applications in metaphor and gesture research
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