Integrated Computer-Aided Engineering最新文献

{"title":"An outstanding platform for ground-breaking cross-disciplinary research","authors":"","doi":"10.3233/ica-200642","DOIUrl":"https://doi.org/10.3233/ica-200642","url":null,"abstract":"According to the Cambridge Dictionary, “engineering” is the study of using scientific principles to design and build machines, structures, and other things, including bridges, roads, vehicles, and buildings. Some ingenious examples of early and yet advanced engineering solutions are the automatic sliding doors powered by steam engines designed by Heron of Alexandria in the first century AD or the qanat irrigation system in Persia in the eighth century BC at the time of the Assyrian king Sargon II. In a broad sense, engineering has been with us for millennia and is a distinctive trait of human nature. The design of engineering solutions for even relatively simple tasks very often requires the use/assistance of intermediate tools. As demonstrated in experiments on animal psychology and in particular on a famous chimpanzee called Sultan [1], while animals of other species can use tools to solve tasks they appear to be incapable to build tools to solve tasks. Thus, humans apparently are the only species able to apply a creative approach to problem solving which may involve multiple phases of planning and the construction of intermediate tools. In modern times, a very important and widely used tool in engineering is the computer. Since its theoretical definition by Alan Turing [2], computers have undergone major changes in their hardware, e.g. in power and size, and the ways they are used. Over the past decades, computers are considered multipurpose devices that can usefully assist an engineer in their work. According to the Encyclopedia Britannica, Computer-Aided Engineering (CAE) is the integration of design and manufacturing into a system under the direct control of digital computers. Of course, the meaning of CAE and what a computer can do for an engineer changed over the past decades and continues to change. Founded by a visionary, impactful and highly influential scholar of modern times, “based on the premise that interdisciplinary thinking and synergistic collaboration of disciplines can solve complex problems, open new frontiers, and lead to true innovations and breakthroughs with a focus on the integration of leading edge and emerging computer technologies for innovative solution of engineering problems,” as noted in the introduction to the inaugural issue of the journal published in July 1993, Integrated Computer-Aided Engineering (ICAE) publishes the latest research about CAE. Professor Hojjat Adeli, as the founder and Editor-in-Chief of ICAE, led the evolution of CAE while shaping the subject and anticipating its coming trends. ICAE is a forum of outstanding quality that has the reputation of being a top journal in Computer Science and Engineering. For example, ICAE has been consistently for many years in the first Quartile according to the Web of Science in the categories of Computer Science, Artificial Intelligence, and Computer Science Interdisciplinary Applications. Professor Adeli achieved this extraordinary result thanks to his metic","PeriodicalId":50358,"journal":{"name":"Integrated Computer-Aided Engineering","volume":"1 1","pages":""},"PeriodicalIF":6.5,"publicationDate":"2020-12-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.3233/ica-200642","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"49247707","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Write Right for ICAE","authors":"Icae Integraded, H. Adeli","doi":"10.3233/ica-200630","DOIUrl":"https://doi.org/10.3233/ica-200630","url":null,"abstract":"should include a concise description of the problems you worked on, the methods you developed, and the results you obtained, both theoretical and experimental. This may take a few back-and-forths until you have come up with a satisfactory abstract. You may then focus on using one sentence to describe what your paper is really about and draw up a catchy title. Avoid long titles if at all possible. Do not reuse sentences between the abstract and the introduction. for doing so shows sloppiness and gives the reader a bad","PeriodicalId":50358,"journal":{"name":"Integrated Computer-Aided Engineering","volume":"8 1","pages":"11-14"},"PeriodicalIF":6.5,"publicationDate":"2020-12-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"75676172","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Shallow buried improvised explosive device detection via convolutional neural networks","authors":"Simon Colreavy-Donnelly, Fabio Caraffini, Stefan Kuhn, M. Gongora, Johana Florez-Lozano, C. Parra","doi":"10.3233/ica-200638","DOIUrl":"https://doi.org/10.3233/ica-200638","url":null,"abstract":"The issue of detecting improvised explosive devices, henceforth IEDs, in rural or built-up urban environments is a persistent and serious concern for governments in the developing world. In many cases, such devices are plastic, or varied metallic objects containing rudimentary explosives, which are not visible to the naked eye and are difficult to detect autonomously. The most effective strategy for detecting land mines also happens to be the most dangerous. This paper intends to leverage the use of a Convolutional Neural Network (CNN) to aid in the discovery of such IEDs. As part of a related project, an autonomous sensor array was used to detect the devices in terrains too hazardous for a human to survey. This paper presents a CNN and its training methodology, suitable to make use of the sensor system. This convolutional neural network can accurately distinguish between a potential IED and surrounding undergrowth and natural features of the environment in real-time. The training methodology enabled the CNN to successfully recognise the IEDs with an accuracy of 98.7%, in well-lit conditions. The results are evaluated against other convolutional neural systems as well as against a deterministic algorithm, showing that the proposed CNN outperforms its competitors including the deterministic method.","PeriodicalId":50358,"journal":{"name":"Integrated Computer-Aided Engineering","volume":"3 1","pages":"403-416"},"PeriodicalIF":6.5,"publicationDate":"2020-07-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"80366985","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Design of reliable virtual human facial expressions and validation by healthy people","authors":"Arturo S. García, P. Fernández-Sotos, Miguel A. Vicente-Querol, G. Lahera, R. Rodríguez-Jiménez, A. Fernández-Caballero","doi":"10.3233/ica-200623","DOIUrl":"https://doi.org/10.3233/ica-200623","url":null,"abstract":"","PeriodicalId":50358,"journal":{"name":"Integrated Computer-Aided Engineering","volume":"21 1","pages":"287-299"},"PeriodicalIF":6.5,"publicationDate":"2020-05-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"75058351","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"EvoAAA: An evolutionary methodology for automated neural autoencoder architecture search","authors":"F. Charte, A. J. Rivera, F. Martínez, M. J. Jesús","doi":"10.3233/ICA-200619","DOIUrl":"https://doi.org/10.3233/ICA-200619","url":null,"abstract":"Machine learning models work better when curated features are provided to them. Feature engineering methods have been usually used as a preprocessing step to obtain or build a proper feature set. In late years, autoencoders (a specific type of symmetrical neural network) have been widely used to perform representation learning, proving their competitiveness against classical feature engineering algorithms. The main obstacle in the use of autoencoders is finding a good architecture, a process that most experts confront manually. An automated autoencoder architecture search procedure, based on evolutionary methods, is proposed in this paper. The methodology is tested against nine heterogeneous data sets. The obtained results show the ability of this approach to find better architectures, able to concentrate most of the useful information in a minimized coding, in a reduced time.","PeriodicalId":50358,"journal":{"name":"Integrated Computer-Aided Engineering","volume":"15 1","pages":"211-231"},"PeriodicalIF":6.5,"publicationDate":"2020-05-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"84339121","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Semantic visual recognition in a cognitive architecture for social robots","authors":"Francisco Martín, Francisco Gomez-Donoso, Félix Escalona, J. G. Rodríguez, M. Cazorla","doi":"10.3233/ica-200624","DOIUrl":"https://doi.org/10.3233/ica-200624","url":null,"abstract":"This work has been funded by the Spanish Government TIN2016-76515-R grant for the COMBAHO project, supported with Feder funds. This work has also been supported by a Spanish grant for PhD studies ACIF/2017/243 and FPU16/00887.","PeriodicalId":50358,"journal":{"name":"Integrated Computer-Aided Engineering","volume":"46 1","pages":"301-316"},"PeriodicalIF":6.5,"publicationDate":"2020-05-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"80608719","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Depth and thermal information fusion for head tracking using particle filter in a fall detection context","authors":"Imen Halima, Jean-Marc Laferté, Geoffroy Cormier, A. Fougères, J. Dillenseger","doi":"10.3233/ica-190615","DOIUrl":"https://doi.org/10.3233/ica-190615","url":null,"abstract":"The security of elderly people living alone is a major issue. A system that detects anomalies can be useful for both individual and retirement homes. In this paper, we present an adaptive human tracking method built on particle filter, using depth and thermal information based on the velocity and the position of the head. The main contribution of this paper is the fusion of information to improve tracking. For each frame, there is a new combination of coefficients for each particle based on an adaptive weighting. Results show that the tracking method can deal with the cases of fast motion (fall), partial occultation and scale variation. To assess the impact of fusion on the tracking process, the robustness and accuracy of the method are tested on a variety of challenging scenarios with or without depth-thermal fusion.","PeriodicalId":50358,"journal":{"name":"Integrated Computer-Aided Engineering","volume":"45 1","pages":"195-208"},"PeriodicalIF":6.5,"publicationDate":"2020-02-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"76638149","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A membrane parallel rapidly-exploring random tree algorithm for robotic motion planning","authors":"Ignacio Pérez-Hurtado, Miguel A. Martínez-del-Amor, Gexiang Zhang, Ferrante Neri, M. Pérez-Jiménez","doi":"10.3233/ica-190616","DOIUrl":"https://doi.org/10.3233/ica-190616","url":null,"abstract":"In recent years, incremental sampling-based motion planning algorithms have been widely used to solve robot motion planning problems in high-dimensional configuration spaces. In particular, the Rapidly-exploring Random Tree (RRT) algorithm and its asymptotically-optimal counterpart called RRT* are popular algorithms used in real-life applications due to its desirable properties. Such algorithms are inherently iterative, but certain modules such as the collision-checking procedure can be parallelized providing significant speedup with respect to sequential implementations. In this paper, the RRT and RRT* algorithms have been adapted to a bioinspired computational framework called Membrane Computing whose models of computation, a.k.a. P systems, run in a non-deterministic and massively parallel way. A large number of robotic applications are currently using a variant of P systems called Enzymatic Numerical P systems (ENPS) for reactive controlling, but there is a lack of solutions for motion planning in the framework. The novel models in this work have been designed using the ENPS framework. In order to test and validate the ENPS models for RRT and RRT*, we present two ad-hoc implementations able to emulate the computation of the models using OpenMP and CUDA. Finally, we show the speedup of our solutions with respect to sequential baseline implementations. The results show a speedup up to 6x using OpenMP with 8 cores against the sequential implementation and up to 24x using CUDA against the best multi-threading configuration.","PeriodicalId":50358,"journal":{"name":"Integrated Computer-Aided Engineering","volume":"1 1","pages":"121-138"},"PeriodicalIF":6.5,"publicationDate":"2020-02-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"76020285","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Content based image retrieval by ensembles of deep learning object classifiers","authors":"Safa Hamreras, Bachir Boucheham, Miguel A. Molina-Cabello, Rafaela Benítez-Rochel, Ezequiel López-Rubio","doi":"10.3233/ica-200625","DOIUrl":"https://doi.org/10.3233/ica-200625","url":null,"abstract":"","PeriodicalId":50358,"journal":{"name":"Integrated Computer-Aided Engineering","volume":"54 1","pages":"317-331"},"PeriodicalIF":6.5,"publicationDate":"2020-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"84656654","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A domain-specific modeling approach supporting tool-chain development with Bayesian network models","authors":"Jinzhi Lu, Guoxin Wang, Xin Tao, Jian Wang, Martin Törngren","doi":"10.3233/ica-190612","DOIUrl":"https://doi.org/10.3233/ica-190612","url":null,"abstract":"Constructing and evaluating a comprehensive tool-chain with commercial off-the-shelf and proprietary tools for the deployment of model-based systems engineering (MBSE) is a challenging and complex ...","PeriodicalId":50358,"journal":{"name":"Integrated Computer-Aided Engineering","volume":"44 1","pages":"153-171"},"PeriodicalIF":6.5,"publicationDate":"2020-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"90216695","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}