Integrated Computer-Aided Engineering最新文献

{"title":"Exploiting higher-order patterns for community detection in attributed graphs","authors":"Lun Hu, Xiangyu Pan, Hong Yan, Pengwei Hu, Tiantian He","doi":"10.3233/ica-200645","DOIUrl":"https://doi.org/10.3233/ica-200645","url":null,"abstract":"As a fundamental task in cluster analysis, community detection is crucial for the understanding of complex network systems in many disciplines such as biology and sociology. Recently, due to the increase in the richness and variety of attribute information associated with individual nodes, detecting communities in attributed graphs becomes a more challenging problem. Most existing works focus on the similarity between pairwise nodes in terms of both structural and attribute information while ignoring the higher-order patterns involving more than two nodes. In this paper, we explore the possibility of making use of higher-order information in attributed graphs to detect communities. To do so, we first compose tensors to specifically model the higher-order patterns of interest from the aspects of network structures and node attributes, and then propose a novel algorithm to capture these patterns for community detection. Extensive experiments on several real-world datasets with varying sizes and different characteristics of attribute information demonstrated the promising performance of our algorithm.","PeriodicalId":50358,"journal":{"name":"Integrated Computer-Aided Engineering","volume":"136 1","pages":"207-218"},"PeriodicalIF":6.5,"publicationDate":"2021-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"76165550","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":"How to maintain the highest quality standards of a leading journal after three decades: An extraordinary Editor-in-Chief leading by example","authors":"","doi":"10.3233/ica-200644","DOIUrl":"https://doi.org/10.3233/ica-200644","url":null,"abstract":"This is my deep honor and great pleasure to share my thoughts on the celebration of almost 3 decades of continuous publication of the Integrated ComputerAided Engineering (ICAE) Journal. Of course such an international journal is indebted to its Editorial Board, to the numerous reviewers, to the even more numerous authors who trusted the journal and to the readers, and I would like to thank them all for their willingness, their work and their trust. In the current case, the journal’s excellence is also in no small measure due to the work and personal involvement of its founder and Editorin-Chief, Professor Hojjat Adeli, and I would like to emphasize his vision and work in the next paragraphs. I was greatly honored when Prof. Adeli asked me to join the ICAE Editorial Advisory Board in 2000. This enrolment lasted until 2006. Around this date, I became the Chief of the French section of IEEE Signal Processing Society (2003–2013), then an Associate Editor of the IEEE Transactions on Signal Processing (2005–2008); since these commitments generated more demanding tasks, I had to resign from my ICAE duties. But I have been serving the ICAE journal as a member of the Editorial Board again since 2017, which is very motivating. Thus, in the light of my own experience, I can make several remarks. First, it is most unusual for scientific journals to keep the same Editor-in-Chief for such a long time: such a position must generate an enormous workload, obviously not compatible with a mere scientific activity, and the enthusiasm of any normally skilled scientist begins to fade over the years. When I compare my two terms with ICAE, I can assure that our EIC’s engagement in this journal has been constant over the years, albeit Prof. Adeli’s scientific outreach is one of the most prominent and influential researchers of our time. Second, one can see that, nowadays, high standard scientific journals have to cope with a couple of rather new challenges: the growing number of potential publications and the inevitable broadening of their scope. On the one hand, the number of papers spreading over the scientific and technical fields of the journal has been dramatically increasing over the last decades. Many new small conferences in touristic locations, many internetonly journals, without solid reviewing policy, generate a lot of papers, which is part of the equation. Concurrently, it is fairly easy for a scientist to upload preprints over the Internet which are made available without any review, which are sometimes unfinished papers (or papers without any verified result), all these materials making cross-references: this is another quite substantial part of the same equation. One of the risks in such an absence of sufficiently strict rules and sufficiently rigorous selection criteria is that excellent works may be drowned among the noise. Nevertheless, the ICAE journal has always maintained (almost) drastic selection rules. I have reviewed plenty of submissions myself","PeriodicalId":50358,"journal":{"name":"Integrated Computer-Aided Engineering","volume":"6 1","pages":"7-8"},"PeriodicalIF":6.5,"publicationDate":"2020-12-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"80501079","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 convolution-based distance measure for fuzzy singletons and its application in a pattern recognition problem","authors":"R. Naranjo, Matilde Santos, L. Garmendia","doi":"10.3233/ica-200629","DOIUrl":"https://doi.org/10.3233/ica-200629","url":null,"abstract":"A new method to measure the distance between fuzzy singletons (FSNs) is presented. It first fuzzifies a crisp number to a generalized trapezoidal fuzzy number (GTFN) using the Mamdani fuzzification method. It then treats an FSN as an impulse signal and transforms the FSN into a new GTFN by convoluting it with the original GTFN. In so doing, an existing distance measure for GTFNs can be used to measure distance between FSNs. It is shown that the new measure offers a desirable behavior over the Euclidean and weighted distance measures in the following sense: Under the new measure, the distance between two FSNs is larger when they are in different GTFNs, and smaller when they are in the same GTFN. The advantage of the new measure is demonstrated on a fuzzy forecasting trading system over two different real stock markets, which provides better predictions with larger profits than those obtained using the Euclidean distance measure for the same system.","PeriodicalId":50358,"journal":{"name":"Integrated Computer-Aided Engineering","volume":"1 1","pages":"51-63"},"PeriodicalIF":6.5,"publicationDate":"2020-12-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"87034813","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":"Real-time facial expression recognition using smoothed deep neural network ensemble","authors":"Nadir Kamel Benamara, Mikel Val-Calvo, José Ramón Álvarez-Sánchez, A. Díaz-Morcillo, J. M. Ferrández, E. Fernández-Jover, T. B. Stambouli","doi":"10.3233/ICA-200643","DOIUrl":"https://doi.org/10.3233/ICA-200643","url":null,"abstract":"Facial emotion recognition (FER) has been extensively researched over the past two decades due to its direct impact in the computer vision and affective robotics fields. However, the available datasets to train these models include often miss-labelled data due to the labellers bias that drives the model to learn incorrect features. In this paper, a facial emotion recognition system is proposed, addressing automatic face detection and facial expression recognition separately, the latter is performed by a set of only four deep convolutional neural network respect to an ensembling approach, while a label smoothing technique is applied to deal with the miss-labelled training data. The proposed system takes only 13.48 ms using a dedicated graphics processing unit (GPU) and 141.97 ms using a CPU to recognize facial emotions and reaches the current state-of-the-art performances regarding the challenging databases, FER2013, SFEW 2.0, and ExpW, giving recognition accuracies of 72.72%, 51.97%, and 71.82% respectively.","PeriodicalId":50358,"journal":{"name":"Integrated Computer-Aided Engineering","volume":"1 1","pages":"97-111"},"PeriodicalIF":6.5,"publicationDate":"2020-12-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"89859721","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":"Simplified binary cat swarm optimization","authors":"H. Siqueira, Clodomir J. Santana, M. Macedo, Elliackin M. N. Figueiredo, A. Gokhale, C. J. A. B. Filho","doi":"10.3233/ica-200618","DOIUrl":"https://doi.org/10.3233/ica-200618","url":null,"abstract":"Inspired by the biological behavior of domestic cats, the Cat Swarm Optimization (CSO) is a metaheuristic which has been successfully applied to solve several optimization problems. For binary problems, the Boolean Binary Cat Swarm Optimization (BBCSO) presents consistent performance and differentiates itself from most of the other algorithms by not considering the agents as continuous vectors using transfer and discretization functions. In this paper, we present a simplified version of the BBCSO. This new version, named Simplified Binary CSO (SBCSO) which features a new position update rule for the tracing mode, demonstrates improved performance, and reduced computational cost when compared to previous CSO versions, including the BBCSO. Furthermore, the results of the experiments indicate that SBCSO can outperform other well-known algorithms such as the Improved Binary Fish School Search (IBFSS), the Binary Artificial Bee Colony (BABC), the Binary Genetic Algorithm (BGA), and the Modified Binary Particle Swarm Optimization (MBPSO) in several instances of the One Max, 0/1 Knapsack, Multiple 0/1 Knapsack, SubsetSum problem besides Feature Selection problems for eight datasets.","PeriodicalId":50358,"journal":{"name":"Integrated Computer-Aided Engineering","volume":"448 ","pages":"35-50"},"PeriodicalIF":6.5,"publicationDate":"2020-12-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.3233/ica-200618","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"72495385","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":"Improving multi-class Boosting-based object detection","authors":"J. M. Buenaposada, L. Baumela","doi":"10.3233/ica-200636","DOIUrl":"https://doi.org/10.3233/ica-200636","url":null,"abstract":"In recent years we have witnessed significant progress in the performance of object detection in images. This advance stems from the use of rich discriminative features produced by deep models and the adoption of new training techniques. Although these techniques have been extensively used in the mainstream deep learning-based models, it is still an open issue to analyze their impact in alternative, and computationally more efficient, ensemble-based approaches. In this paper we evaluate the impact of the adoption of data augmentation, bounding box refinement and multi-scale processing in the context of multi-class Boosting-based object detection. In our experiments we show that use of these training advancements significantly improves the object detection performance.","PeriodicalId":50358,"journal":{"name":"Integrated Computer-Aided Engineering","volume":"27 1","pages":"81-96"},"PeriodicalIF":6.5,"publicationDate":"2020-12-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"84218641","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":"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}