Journal articles: 'Process Similarity'

1

Lu, Junde, and Furong Gao. "Process Modeling Based on Process Similarity." Industrial & Engineering Chemistry Research 47, no. 6 (March 2008): 1967–74. http://dx.doi.org/10.1021/ie0704851.

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Lu, Junde, and Furong Gao. "BATCH PROCESS MODELING BASED ON PROCESS SIMILARITY." IFAC Proceedings Volumes 40, no. 5 (2007): 379–84. http://dx.doi.org/10.3182/20070606-3-mx-2915.00111.

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Amiri, Mohammad Javad, and Mahnaz Koupaee. "Data‐driven business process similarity." IET Software 11, no. 6 (December 2017): 309–18. http://dx.doi.org/10.1049/iet-sen.2016.0256.

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Yan, Zhiqiang, Remco Dijkman, and Paul Grefen. "Fast business process similarity search." Distributed and Parallel Databases 30, no. 2 (February 24, 2012): 105–44. http://dx.doi.org/10.1007/s10619-012-7089-z.

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Nosofsky, R. M. "Similarity Scaling and Cognitive Process Models." Annual Review of Psychology 43, no. 1 (January 1992): 25–53. http://dx.doi.org/10.1146/annurev.ps.43.020192.000325.

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Chiappe, Dan L. "Similarity, Relevance, and the Comparison Process." Metaphor and Symbol 13, no. 1 (March 1998): 17–30. http://dx.doi.org/10.1207/s15327868ms1301_2.

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Neumuth, Thomas, Frank Loebe, and Pierre Jannin. "Similarity metrics for surgical process models." Artificial Intelligence in Medicine 54, no. 1 (January 2012): 15–27. http://dx.doi.org/10.1016/j.artmed.2011.10.001.

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Lu, Junde, Ke Yao, and Furong Gao. "Process similarity and developing new process models through migration." AIChE Journal 55, no. 9 (September 2009): 2318–28. http://dx.doi.org/10.1002/aic.11822.

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Song, Guoli, Shuhui Wang, Qingming Huang, and Qi Tian. "Multimodal Similarity Gaussian Process Latent Variable Model." IEEE Transactions on Image Processing 26, no. 9 (September 2017): 4168–81. http://dx.doi.org/10.1109/tip.2017.2713045.

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LI, Ming, and Fan YANG. "Web service capability matching based on process-similarity." Journal of Computer Applications 31, no. 5 (June 20, 2011): 1370–73. http://dx.doi.org/10.3724/sp.j.1087.2011.01370.

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Yahya, Bernardo N., Jae-Hun Park, Hye-Rim Bae, and Jung-Kwan Mo. "Similarity Measurement Using Ontology in Vessel Clearance Process." Journal of Korean Institute of Industrial Engineers 37, no. 2 (June 1, 2011): 153–62. http://dx.doi.org/10.7232/jkiie.2011.37.2.153.

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Hayashi, Kohei, Takashi Takenouchi, Ryota Tomioka, and Hisashi Kashima. "Self-measuring Similarity for Multi-task Gaussian Process." Transactions of the Japanese Society for Artificial Intelligence 27, no. 3 (2012): 103–10. http://dx.doi.org/10.1527/tjsai.27.103.

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Eckert, E. R. G. "Similarity Analysis Applied to the Die Casting Process." Journal of Engineering Materials and Technology 111, no. 4 (October 1, 1989): 393–98. http://dx.doi.org/10.1115/1.3226485.

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Detailed studies of the filling process of the die with liquid metal and the solidification are necessary to put this technology on a firm scientific basis. An experimental study of the fluid flow, heat transfer, and solidification encounters, however, enormous difficulties. It is extremely fast [in order of milliseconds], the small scale of the die makes local measurements difficult, and the temperature range and the nature of the liquid metal does not lend itself readily to experimentation. This paper explores whether similarity analysis is useful for the design of model experiments which reduce these difficulties and which reproduce the actual occurrence faithfully. The study is carried out in two steps. During the initial period, the whole cavity of the die is available for the fluid. Reynolds and Weber numbers which have to have the same value for the model experiment and for the die casting process permit the use of any fluid and of a large scale model which decreases the injection velocity and increases the filling time. During the later period of the filling process the cavity available for the liquid is reduced by the solidified metal. The energy conservation equation results in two more dimensionless numbers, the Prandtl and Jakob numbers which prescribe that model experiments have now to use a liquid metal but use of a metal with a low melting point and of a large scale decrease again the required injection velocity and increase the filling time by orders of magnitude, conditions beneficial for detailed and accurate experiments.

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Heller, Patrice E., and Beatrice Wood. "THE PROCESS OF INTIMACY: SIMILARITY, UNDERSTANDING AND GENDER." Journal of Marital and Family Therapy 24, no. 3 (July 1998): 273–88. http://dx.doi.org/10.1111/j.1752-0606.1998.tb01085.x.

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Becker, Michael, and Ralf Laue. "A comparative survey of business process similarity measures." Computers in Industry 63, no. 2 (February 2012): 148–67. http://dx.doi.org/10.1016/j.compind.2011.11.003.

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Montani, Stefania, Giorgio Leonardi, Silvana Quaglini, Anna Cavallini, and Giuseppe Micieli. "A knowledge-intensive approach to process similarity calculation." Expert Systems with Applications 42, no. 9 (June 2015): 4207–15. http://dx.doi.org/10.1016/j.eswa.2015.01.027.

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Zharkova, N. A., and L. R. Botvina. "Self-similarity of the radiation defects accumulation process." Scripta Materialia 38, no. 12 (May 1998): 1829–33. http://dx.doi.org/10.1016/s1359-6462(98)00109-2.

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Dijkman, Remco, Marlon Dumas, Boudewijn van Dongen, Reina Käärik, and Jan Mendling. "Similarity of business process models: Metrics and evaluation." Information Systems 36, no. 2 (April 2011): 498–516. http://dx.doi.org/10.1016/j.is.2010.09.006.

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Bao, Yunxia, Faming Lu, Yanxiao Wang, Qingtian Zeng, and Cong Liu. "Student Performance Prediction Based on Behavior Process Similarity." Chinese Journal of Electronics 29, no. 6 (November 1, 2020): 1110–18. http://dx.doi.org/10.1049/cje.2020.02.012.

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Lloyd, P., and P. Scott. "Difference in similarity: interpreting the architectural design process." Environment and Planning B: Planning and Design 22, no. 4 (1995): 383–406. http://dx.doi.org/10.1068/b220383.

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Pérez-Castillo, Ricardo, Danilo Caivano, and Mario Piattini. "Ontology-based similarity applied to business process clustering." Journal of Software: Evolution and Process 26, no. 12 (May 20, 2014): 1128–49. http://dx.doi.org/10.1002/smr.1652.

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Cahyapratama, Afrianda, Kelly Rosa Sungkono, and Riyanarto Sarno. "Gap analysis business process model by using structural similarity." Indonesian Journal of Electrical Engineering and Computer Science 18, no. 1 (April 1, 2020): 124. http://dx.doi.org/10.11591/ijeecs.v18.i1.pp124-134.

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<span>Gap analysis process model is a study that can help an institution to determine differences between business process models, such as a model of Standard Operating Procedure and a model of activities in an event log. Gap analysis is used for finding incomplete processes and can be obtained by using structural similarity. Structural similarity measures the similarity of activities and relationships depicting in the models. This research introduces a graph-matching algorithm as the structural similarity algorithm and compares it with dice coefficient algorithms. Graph-matching algorithm notices parallel relationships and invisible tasks, on the contrary dice coefficient algorithms only measure closeness between activities and relationships. The evaluation shows that the graph-matching algorithm produces 76.76 percent similarity between an SOP model and a process model generating from an event log; while, dice coefficient algorithms produces 70 percent similarity. The ability in detecting parallel relationships and invisible tasks causes the graph-matching algorithm produces a higher similarity value than dice coefficient algorithms.</span>

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MISAKI, Daigo, and Shigeru AOMURA. "Searching Sheet Metal Parts Based on Bending Process Similarity for Process Planning." Transactions of the Japan Society of Mechanical Engineers Series C 68, no. 672 (2002): 2486–93. http://dx.doi.org/10.1299/kikaic.68.2486.

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MaCken, William, Sebastien Tremblay, David Alford, and Dylan Jones. "Attentional Selectivity in Short-term Memory: Similarity of Process, Not Similarity of Content, Determines Disruption." International Journal of Psychology 34, no. 5-6 (October 1999): 322–27. http://dx.doi.org/10.1080/002075999399639.

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Hoffmann, Maximilian, and Ralph Bergmann. "Using Graph Embedding Techniques in Process-Oriented Case-Based Reasoning." Algorithms 15, no. 2 (January 18, 2022): 27. http://dx.doi.org/10.3390/a15020027.

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Similarity-based retrieval of semantic graphs is a core task of Process-Oriented Case-Based Reasoning (POCBR) with applications in real-world scenarios, e.g., in smart manufacturing. The involved similarity computation is usually complex and time-consuming, as it requires some kind of inexact graph matching. To tackle these problems, we present an approach to modeling similarity measures based on embedding semantic graphs via Graph Neural Networks (GNNs). Therefore, we first examine how arbitrary semantic graphs, including node and edge types and their knowledge-rich semantic annotations, can be encoded in a numeric format that is usable by GNNs. Given this, the architecture of two generic graph embedding models from the literature is adapted to enable their usage as a similarity measure for similarity-based retrieval. Thereby, one of the two models is more optimized towards fast similarity prediction, while the other model is optimized towards knowledge-intensive, more expressive predictions. The evaluation examines the quality and performance of these models in preselecting retrieval candidates and in approximating the ground-truth similarities of a graph-matching-based similarity measure for two semantic graph domains. The results show the great potential of the approach for use in a retrieval scenario, either as a preselection model or as an approximation of a graph similarity measure.

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Dewi, Meira Parma, and Nurtami Soedarsono. "The Similarity Measurement of Human DNA Profile Using Fuzzy Similarity." Eksakta : Berkala Ilmiah Bidang MIPA 21, no. 1 (April 30, 2020): 46–53. http://dx.doi.org/10.24036/eksakta/vol21-iss1/216.

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This research investigated the similarity of human DNA profile using fuzzy similarity measure. The similarity measurement of DNA profile had been done by measuring the similarity between query’s DNA profile and its biological family such as father, mother, brother, sister, grandmother and grandfather. The similarity measurement had been done to the short tandem repeat (STR) alleles in sixteen loci. The result of the experiment showed that each simulation gave matching result. This research is useful for Indonesian National Police (POLRI) in identifying process of disaster victim, terrorism victim and other criminal conduct.

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LIU, Cong, Qingtian ZENG, Hua DUAN, Shangce GAO, and Chanhong ZHOU. "Towards Comprehensive Support for Business Process Behavior Similarity Measure." IEICE Transactions on Information and Systems E102.D, no. 3 (March 1, 2019): 588–97. http://dx.doi.org/10.1587/transinf.2018edp7127.

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HUANG, Zi-Cheng, Jin-Peng HUAI, Xu-Dong LIU, Xiang LI, and Jiang-Jun ZHU. "Automatic Service Discovery Framework Based on Business Process Similarity." Journal of Software 23, no. 3 (April 28, 2012): 489–503. http://dx.doi.org/10.3724/sp.j.1001.2012.04010.

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29

Misaki, D., and S. Aomura. "Searching sheet metal parts based on bending process similarity." Proceedings of the Institution of Mechanical Engineers, Part B: Journal of Engineering Manufacture 217, no. 3 (March 1, 2003): 427–38. http://dx.doi.org/10.1243/095440503321590587.

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Sheet metal parts have been widely used in industry and much information for parts has been accumulated in a database. In planning the manufacturing process of a sheet metal part, if the process plan of a similar part can be retrieved from the database, the process planning would be faster and more consistent. In this paper, an effective method of searching the sheet metal parts based on bending process similarity is proposed. This method consists of two stages. In the first stage, flat pattern drawings of the parts with the same set-up numbers are classified into several topological structures. In the second stage, the parts that possess a similar bending process to the target part are selected. The bending process similarity is defined by the grasping position of a robot gripper. The number of reposition and grasping positions are decided by taking the geometric element of the flat pattern into consideration. The effectiveness of this method is described and illustrative examples are shown.

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Lenz, Juergen, Timo Denner, Michael Lickefett, and Thomas Bauernhansl. "Similarity-based Product Search for Next Generation Process Planning." Procedia CIRP 33 (2015): 59–63. http://dx.doi.org/10.1016/j.procir.2015.06.012.

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Tsumoto, Shusaku, Haruko Iwata, Shoji Hirano, and Yuko Tsumoto. "Similarity-based behavior and process mining of medical practices." Future Generation Computer Systems 33 (April 2014): 21–31. http://dx.doi.org/10.1016/j.future.2013.10.014.

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Shi, Yongjun, Hong Shen, Zhenqiang Yao, Jun Hu, and Lei Xia. "Application of similarity theory in the laser forming process." Computational Materials Science 37, no. 3 (September 2006): 323–27. http://dx.doi.org/10.1016/j.commatsci.2005.09.002.

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Deng, Xiaogang, and Xuemin Tian. "Multimode Process Fault Detection Using Local Neighborhood Similarity Analysis." Chinese Journal of Chemical Engineering 22, no. 11-12 (November 2014): 1260–67. http://dx.doi.org/10.1016/j.cjche.2014.09.022.

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Avramenko, Yuri, and Andrzej Kraslawski. "Similarity concept for case-based design in process engineering." Computers & Chemical Engineering 30, no. 3 (January 2006): 548–57. http://dx.doi.org/10.1016/j.compchemeng.2005.10.011.

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FARJOUN, MOSHE, and LINDA LAI. "SIMILARITY JUDGMENTS IN STRATEGY FORMULATION: ROLE, PROCESS AND IMPLICATIONS." Strategic Management Journal 18, no. 4 (April 1997): 255–73. http://dx.doi.org/10.1002/(sici)1097-0266(199704)18:4<255::aid-smj875>3.0.co;2-j.

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Li, Jun, Yun Hui Lei, and Min Zhou. "Similarity Evaluation for Magnetic Materials Sintering." Advanced Materials Research 557-559 (July 2012): 785–88. http://dx.doi.org/10.4028/www.scientific.net/amr.557-559.785.

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ABSTRACT. The evaluation of the sintering quality of magnetic materials is an important issue. Similarity measures between curves have a broad prospect in the prediction of process industry. A new algorithm was presented in this paper to calculate the similarity between the designed process curve and the acquired one. The limitation of traditional similarity measures was avoided and the characteristics of process and the curve form were taken into account. Then, the similarity measure was applied to valuate the actual process performance of magnetic materials sintering. It shows that the proposed similarity evaluation methods can be used to effectively predict or analyze the control performance.

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Carmona, Josep, Lluís Padró, and Luis Delicado. "Flexible Process Model Mapping using Relaxation Labeling." Fundamenta Informaticae 175, no. 1-4 (September 28, 2020): 123–41. http://dx.doi.org/10.3233/fi-2020-1950.

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Computing a mapping between two process models is a crucial technique, since it enables reasoning and operating across processes, like providing a similarity score between two processes, or merging different process variants to generate a consolidated process model. In this paper we present a new flexible technique for process model mapping, based on the relaxation labeling constraint satisfaction algorithm. The technique can be instantiated so that different modes are devised, depending on the context. For instance, it can be adapted to the case where one of the mapped process models is incomplete, or it can be used to ground an adaptable similarity measure between process models. The approach has been implemented inside the open platform NLP4BPM, providing a visualization of the performed mappings and computed similarity scores. The experimental results witness the flexibility and usefulness of the technique proposed.

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Zhang, Feng, Lulu Li, Cong Liu, and Qingtian Zeng. "Flow Chart Generation-Based Source Code Similarity Detection Using Process Mining." Scientific Programming 2020 (July 7, 2020): 1–15. http://dx.doi.org/10.1155/2020/8865413.

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Source code similarity detection has extensive applications in computer programming teaching and software intellectual property protection. In the teaching of computer programming courses, students may utilize some complex source code obfuscation techniques, e.g., opaque predicates, loop unrolling, and function inlining and outlining, to reduce the similarity between code fragments and avoid the plagiarism detection. Existing source code similarity detection approaches only consider static features of source code, making it difficult to cope with more complex code obfuscation techniques. In this paper, we propose a novel source code similarity detection approach by considering the dynamic features at runtime of source code using process mining. More specifically, given two pieces of source code, their running logs are obtained by source code instrumentation and execution. Next, process mining is used to obtain the flow charts of the two pieces of source code by analyzing their collected running logs. Finally, similarity of the two pieces of source code is measured by computing the similarity of these two flow charts. Experimental results show that the proposed approach can deal with more complex obfuscation techniques including opaque predicates and loop unrolling as well as function inlining and outlining, which cannot be handled by existing work properly. Therefore, we argue that our approach can defeat commonly used code obfuscation techniques more effectively for source code similarity detection than the existing state-of-the-art approaches.

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Soboleva, N. S., and A. K. Efremov. "Elastic-plastic Shock Processes Similarity." Mechanical Engineering and Computer Science, no. 2 (March 8, 2019): 1–12. http://dx.doi.org/10.24108/0219.0001459.

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In the process of working out the design of the object, preliminary studies are carried out, including modeling (mathematical, physical or a combination of them) and comprehensive tests. In physical modeling, based on the methods of the theory of similarity and dimensions, the preparatory stages are implemented on the basis of an adequate mathematical model of the object or an in-depth description of its physical features. During stand testing the most complex problem is the problem of simulating an excitation in the form of intense single shock pulse. In stand shock testing in the contact is usually set an elastic-plastic, impact deformed element (crusher). The semi-empirical theory of impact is based on the assumption that only local elastic-plastic deformations could be taken into account. The study of the impact process is first illustrated using the method of physical modeling. In this two independent criteria of similarity of the shock processes are substantiated. Then, based on the analysis and numerical solution of the differential equation of impact, it is shown that the dimensionless complex arising from the theory of similarity and dimensions can be used to separately determine the main parameters of the shock process for given shock conditions – the duration of the load front and the maximum values of the contact force (overload) and local deformation. The experimental data obtained by means of a vertical pneumatic shock stand, having a small spread relative to the calculated results, are presented. The features of the process in the case of elastic-plastic impact of an elongated, rod type body are briefly considered. The criterion allowing to estimate quantitatively the relative role of wave processes in this variant of impact is offered which enables to validate conditions of considering the impacting body as a solid one.

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Akhil, Shekkari. "Understanding Question Pair Similarity." International Journal for Research in Applied Science and Engineering Technology 9, no. VI (June 25, 2021): 2632–38. http://dx.doi.org/10.22214/ijraset.2021.35575.

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One of the most important areas where the Natural Language Process of Machine Learning may help is determining if two questions are similar. The model we create can instantly detect if a question is similar to one that has already been posed. To find the underlying patterns in our data, we'll do a complete Exploratory Data Analysis. Based on our observations, we will do feature engineering. We'll try out a few different modelling strategies to determine which one works the best and keeps the greatest outcomes.

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Feng, Jin Feng, Jin Ma, Jie Hu, and Ying Hong Peng. "Research on Feature Based IC Process Modeling and Clustering." Applied Mechanics and Materials 397-400 (September 2013): 2391–97. http://dx.doi.org/10.4028/www.scientific.net/amm.397-400.2391.

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In order to make effective reuse of existing integrated circuit (IC) process cases, improve design efficiency, robustness of design resolutions and overcome knowledge famine and knowledge orientation problems in design process, a feature based hierarchical framework of knowledge modeling and similarity measurements based knowledge clustering method of IC process cases are proposed. In this paper, IC process cases knowledge is represented into four types: sequential type, textual type, crisp type and interval type. According to knowledge classification, sequential similarity measurement for process sequence knowledge and content similarity measurement for the rest types are listed. Finally, existing IC wafer handling process cases of an IC manufacturing enterprise are employed to verify the proposed methods.

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Agishev, T. Kh, V. N. Filippov, and T. M. Levina. "METHODS FOR ASSESSING POPULATION HEALTH STATUS BASED ON PROCESS SIMILARITY." Современные наукоемкие технологии (Modern High Technologies), no. 3 2021 (2021): 16–21. http://dx.doi.org/10.17513/snt.38524.

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Khemissa, Hamid, Mohamed Ahmed-nacer, and Abdelkader Belkhir. "Adaptive Guidance Model Based Similarity for Software Process Development Programming." International Journal of Software Engineering & Applications 5, no. 2 (March 31, 2014): 67–84. http://dx.doi.org/10.5121/ijsea.2014.5205.

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Zhai, Shulei. "Research on process route matching mechanism based on similarity calculation." Journal of Physics: Conference Series 2229, no. 1 (March 1, 2022): 012015. http://dx.doi.org/10.1088/1742-6596/2229/1/012015.

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Abstract Enterprises accumulate successful process route cases in actual production activities. This paper gives a case-based process route matching mechanism by determining process route feature attribute weights and similarity calculation methods to achieve efficient design of process routes with new requirements.

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Guo, Wenyan, Qingtian Zeng, Hua Duan, Weijian Ni, and Cong Liu. "Process-extraction-based text similarity measure for emergency response plans." Expert Systems with Applications 183 (November 2021): 115301. http://dx.doi.org/10.1016/j.eswa.2021.115301.

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Belhajjame, Khalid, and Marco Brambilla. "Ontological Description and Similarity-Based Discovery of Business Process Models." International Journal of Information System Modeling and Design 2, no. 2 (April 2011): 47–66. http://dx.doi.org/10.4018/jismd.2011040103.

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Project repositories are a central asset in software development, as they preserve the knowledge gathered in past development activities. Locating relevant information in a vast project repository is problematic, because it requires manually tagging projects with accurate metadata, an activity which is time consuming and prone to errors and omissions. Just like any other artifact or web service, business processes can be stored in repositories to be shared and used by third parties, e.g., as building blocks for constructing new business processes. The success of such a paradigm depends partly on the availability of effective search tools to locate business processes that are relevant to the user purposes. A handful of researchers have investigated the problem of business process discovery using as input syntactical and structural information that describes business processes. This work explores an additional source of information encoded in the form of annotations that semantically describe business processes. Business processes can be semantically described using the so called abstract business processes. These are designated by concepts from an ontology which additionally captures their relationships. This ontology can be built in an automatic fashion from a collection of (concrete) business processes, and this work illustrates how it can be refined by domain experts and used in the discovery of business processes, with the purpose of reuse and increase in design productivity.

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Ujlayan, Anshul, and Manisha Sharma. "A study to enhance candidate screening process using similarity analysis." International Journal of Business and Data Analytics 1, no. 1 (2019): 41. http://dx.doi.org/10.1504/ijbda.2019.098832.

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Sharma, Manisha, and Anshul Ujlayan. "A study to enhance candidate screening process using similarity analysis." International Journal of Business and Data Analytics 1, no. 1 (2019): 41. http://dx.doi.org/10.1504/ijbda.2019.10020201.

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Zhou, Changhong, Cong Liu, Qingtian Zeng, Zedong Lin, and Hua Duan. "A Comprehensive Process Similarity Measure Based on Models and Logs." IEEE Access 7 (2019): 69257–73. http://dx.doi.org/10.1109/access.2018.2885819.

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Um, Moon-Kwang, Joon-Hyung Byun, and Isaac M. Daniel. "Similarity Relations of Resin Flow in Resin Transfer Molding Process." Advanced Composite Materials 18, no. 2 (January 2009): 135–52. http://dx.doi.org/10.1163/156855109x428745.

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Journal articles on the topic 'Process Similarity'

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