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Journal articles on the topic 'Incremental approaches'

Author: Grafiati

Published: 4 June 2021

Last updated: 19 February 2022

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1

Kurzban, Robert, Mary L. Rigdon, and Bart J. Wilson. "Incremental approaches to establishing trust." Experimental Economics 11, no. 4 (September 29, 2007): 370–89. http://dx.doi.org/10.1007/s10683-007-9173-1.

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Racz, G. S., V. S. Oleksik, and R. E. Breaz. "Incremental forming – CAE/CAM approaches and results." IOP Conference Series: Materials Science and Engineering 591 (August 14, 2019): 012065. http://dx.doi.org/10.1088/1757-899x/591/1/012065.

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3

Etheredge, J. "Incremental Approaches to Increasing Health Care Coverage." JAMA: The Journal of the American Medical Association 289, no. 9 (March 5, 2003): 1166. http://dx.doi.org/10.1001/jama.289.9.1166.

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Zhou, Xun, Jing He, Guangyan Huang, and Yanchun Zhang. "SVD-based incremental approaches for recommender systems." Journal of Computer and System Sciences 81, no. 4 (June 2015): 717–33. http://dx.doi.org/10.1016/j.jcss.2014.11.016.

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Kolpakov, Aleksey, and Lachezar G. Anguelov. "Decision-making approaches to contracting out." Journal of Strategic Contracting and Negotiation 4, no. 3 (September 2018): 148–66. http://dx.doi.org/10.1177/2055563620918811.

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This article compares and contrasts two classical decision-making approaches used in outsourcing specific public services. We perform content analysis of semi-structured interviews with public managers who are engaged in contracting for different public services, and find that incremental or small step-by-step decision-making is more likely to be observed in the outsourcing of “soft” or human services. Rational decision-making on the hand is more likely for “hard” services including janitorial services, public works, bridge design, street striping, parks maintenance, strategic planning, refrigeration experts, and food services. Our findings also indicate that some services can be outsourced using both decision-making approaches in certain cases. Using comparative analysis, we identify three factors associated with incremental decision-making across the organizations in our sample. All organizations that outsourced services using incremental models of decision-making had a for-profit business partner, experienced managers, and exhibited desire for cooperation and coordination.

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Ferreira, Artur J., and Mário A. T. Figueiredo. "Incremental filter and wrapper approaches for feature discretization." Neurocomputing 123 (January 2014): 60–74. http://dx.doi.org/10.1016/j.neucom.2012.10.036.

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7

Gruber, Jonathan. "Evaluating Alternative Approaches to Incremental Health-Insurance Expansion." American Economic Review 93, no. 2 (April 1, 2003): 271–76. http://dx.doi.org/10.1257/000282803321947182.

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8

Pensa, Ruggero G., Dino Ienco, and Rosa Meo. "Hierarchical co-clustering: off-line and incremental approaches." Data Mining and Knowledge Discovery 28, no. 1 (September 25, 2012): 31–64. http://dx.doi.org/10.1007/s10618-012-0292-8.

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9

Mortlock, Robert. "Studying Acquisition Strategy Formulation of Incremental Development Approaches." Return on Investement (ROI) of New Approaches to Defense Acquisition 27, no. 93 (July 1, 2020): 264–311. http://dx.doi.org/10.22594/dau.19-845.27.03.

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This is a study of the challenges that acquisition professionals confront in formulating the Department of Defense’s preferred acquisition–incremental development. The research surveys acquisition professionals to recommend the components of an acquisition strategy associated with a typical acquisition program undergoing program/project milestone review and approval. This work provides insights into how program managers use typical programmatic decision inputs (requirements, technology maturity, risk, urgency, and funding) to formulate the components of an acquisition strategy. The results suggest that acquisition policy should perhaps require a justification for most programs of record if an incremental development approach is not planned. Adoption of the recommended acquisition policy changes would make the defense acquisition system more responsive to the warfighter by fielding improved capability as quickly as possible and reducing risk of the eventual delivery of the full required capability.

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Cai, Mingjie, Guangming Lang, Hamido Fujita, Zhenyu Li, and Tian Yang. "Incremental approaches to updating reducts under dynamic covering granularity." Knowledge-Based Systems 172 (May 2019): 130–40. http://dx.doi.org/10.1016/j.knosys.2019.02.014.

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do Nascimento, Dimas Cassimiro, Carlos Eduardo Santos Pires, and Demetrio Gomes Mestre. "Heuristic-based approaches for speeding up incremental record linkage." Journal of Systems and Software 137 (March 2018): 335–54. http://dx.doi.org/10.1016/j.jss.2017.11.074.

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Chazal, Claude, and Rostand Mouto Pitti. "Viscoelastic incremental formulation using creep and relaxation differential approaches." Mechanics of Time-Dependent Materials 14, no. 2 (October 27, 2009): 173–90. http://dx.doi.org/10.1007/s11043-009-9101-1.

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13

Lang, Guangming, Qingguo Li, Mingjie Cai, Tian Yang, and Qimei Xiao. "Incremental approaches to knowledge reduction based on characteristic matrices." International Journal of Machine Learning and Cybernetics 8, no. 1 (November 26, 2014): 203–22. http://dx.doi.org/10.1007/s13042-014-0315-4.

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14

Kushwah, Arun Pratap Singh, Shailesh Jaloree, and Ramjeevan Singh Thakur. "Computational analysis of incremental clustering approaches for Large Data." International Journal of Computers and Communications 15 (May 28, 2021): 14–18. http://dx.doi.org/10.46300/91013.2021.15.3.

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Clustering is an approach of data mining, which helps us to find the underlying hidden structure in the dataset. K-means is a clustering method which usages distance functions to find the similarities or dissimilarities between the instances. DBSCAN is a clustering algorithm, which discovers the arbitrary shapes & sizes of clusters from huge volume of using spatial density method. These two approaches of clustering are the classical methods for efficient clustering but underperform when the data is updated frequently in the databases so, the incremental or gradual clustering approaches are always preferred in this environment. In this paper, an incremental approach for clustering is introduced using K-means and DBSCAN to handle the new datasets dynamically updated in the database in an interval.

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WANG, TING, SHENG-UEI GUAN, KA LOK MAN, T. O. TING, and ALEXEI LISITSA. "OPTIMIZED NEURAL INCREMENTAL ATTRIBUTE LEARNING FOR CLASSIFICATION BASED ON STATISTICAL DISCRIMINABILITY." International Journal of Computational Intelligence and Applications 13, no. 04 (December 2014): 1450019. http://dx.doi.org/10.1142/s1469026814500199.

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Feature ordering is a significant data preprocessing method in incremental attribute learning (IAL), where features are gradually trained according to a given order. Previous research showed feature ordering is crucial to the IAL performance. It is relevant to each feature's discrimination ability, which can be calculated by single discriminability (SD). However, when feature dimensions increase, feature discrimination ability should also be calculated incrementally, because discrimination ability in lower dimensional spaces is different from that in higher spaces. Thus based on SD, accumulative discriminability (AD), a new statistical metric for incremental feature discrimination ability estimation, is designed. Moreover, a criterion that summarizes all the produced values of AD is employed to obtain the optimum feature ordering for classification problems based on neural networks by means of IAL. In addition, in order to reduce the time consumption, an effective feature ordering approach is developed. Compared with the feature ordering obtained by other approaches, the method outlined in this paper obtained good final classification results, which indicates that, firstly, feature discrimination ability should be incrementally estimated in IAL; and secondly, feature ordering derived by AD and its corresponding approaches are applicable with IAL.

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Phung, Quang-Ngoc, and Eunseok Lee. "Incremental Formula-Based Fix Localization." Applied Sciences 11, no. 1 (December 30, 2020): 303. http://dx.doi.org/10.3390/app11010303.

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Automatically fixing bugs in software programs can significantly reduce the cost and improve the productivity of the software. Toward this goal, a critical and challenging problem is automatic fix localization, which identifies program locations where a bug fix can be synthesized. In this paper, we present AgxFaults, a technique that automatically identifies minimal subsets of program statements at which a suitable modification can remove the error. AgxFaults works based on dynamically encoding semantic of program parts that are relevant to an observed error into an unsatisfiable logical formula and then manipulating this formula in an increasingly on-demand manner. We perform various experiments on faulty versions of the traffic collision avoidance system (TCAS) program in the Siemens Suite, programs in Bekkouche’s benchmark, and server real bugs in the Defects4J benchmark. The experimental results show that AgxFaults outperforms single-path-formula approaches in terms of effectiveness in finding fix localization and fault localization. AgxFaults is better than program-formula-based approaches in terms of efficiency and scalability, while providing similar effectiveness. Specifically, the solving time of AgxFaults is 28% faster, and the running time is 45% faster, than the program-formula-based approach, while providing similar fault localization results.

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Nilashi, Mehrbakhsh, Othman Bin Ibrahim, Abbas Mardani, Ali Ahani, and Ahmad Jusoh. "A soft computing approach for diabetes disease classification." Health Informatics Journal 24, no. 4 (November 14, 2016): 379–93. http://dx.doi.org/10.1177/1460458216675500.

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As a chronic disease, diabetes mellitus has emerged as a worldwide epidemic. The aim of this study is to classify diabetes disease by developing an intelligence system using machine learning techniques. Our method is developed through clustering, noise removal and classification approaches. Accordingly, we use expectation maximization, principal component analysis and support vector machine for clustering, noise removal and classification tasks, respectively. We also develop the proposed method for incremental situation by applying the incremental principal component analysis and incremental support vector machine for incremental learning of data. Experimental results on Pima Indian Diabetes dataset show that proposed method remarkably improves the accuracy of prediction and reduces computation time in relation to the non-incremental approaches. The hybrid intelligent system can assist medical practitioners in the healthcare practice as a decision support system.

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18

Lang, Guangming, Duoqian Miao, Mingjie Cai, and Zhifei Zhang. "Incremental approaches for updating reducts in dynamic covering information systems." Knowledge-Based Systems 134 (October 2017): 85–104. http://dx.doi.org/10.1016/j.knosys.2017.07.020.

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19

Thorpe, Kenneth E. "Incremental Approaches to Covering Uninsured Children: Design and Policy Issues." Health Affairs 16, no. 4 (July 1997): 64–78. http://dx.doi.org/10.1377/hlthaff.16.4.64.

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20

Saadon, Afaf G. Bin, and Hoda M. O. Mokhtar. "Survey on iterative and incremental approaches in distributed computing environment." International Journal of Data Science 4, no. 1 (2019): 18. http://dx.doi.org/10.1504/ijds.2019.098359.

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Mokhtar, Hoda M. O., and Afaf G. Bin Saadon. "Survey on iterative and incremental approaches in distributed computing environment." International Journal of Data Science 4, no. 1 (2019): 18. http://dx.doi.org/10.1504/ijds.2019.10019815.

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22

Sang, Binbin, Hongmei Chen, Tianrui Li, Weihua Xu, and Hong Yu. "Incremental approaches for heterogeneous feature selection in dynamic ordered data." Information Sciences 541 (December 2020): 475–501. http://dx.doi.org/10.1016/j.ins.2020.06.051.

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23

Petek, A., B. Jurisevic, K. Kuzman, and M. Junkar. "Comparison of alternative approaches of single point incremental forming processes." Journal of Materials Processing Technology 209, no. 4 (February 2009): 1810–15. http://dx.doi.org/10.1016/j.jmatprotec.2008.04.033.

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24

Bullock, Zach, Abbie B. Liel, Keith A. Porter, and Shideh Dashti. "Site‐specific liquefaction fragility analysis: Cloud, stripe, and incremental approaches." Earthquake Engineering & Structural Dynamics 50, no. 9 (April 29, 2021): 2529–50. http://dx.doi.org/10.1002/eqe.3458.

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25

Wang, Xiang-Yang, Li-Yang Dai, Hua-Zi Xu, and Yong-Long Chi. "A comparison of single and incremental impact approaches for producing experimental thoracolumbar burst fractures." Journal of Neurosurgery: Spine 7, no. 2 (August 2007): 199–204. http://dx.doi.org/10.3171/spi-07/08/199.

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Object. Experimental burst fracture models are often developed by using either single or incremental impacts. In both protocols, the weight-drop technique produces the impact. However, to the authors' knowledge in no study have researchers attempted to compare the equivalence of the spine burst fracture produced using the different impact protocols. This study was performed to investigate whether the single and incremental trauma approaches produce equivalent degrees of severity in thoracolumbar burst fractures. Methods. Twenty bovine thoracolumbar spines comprising three vertebrae were divided evenly into the single impact and incremental impact groups. The specimens in the incremental impact group were subjected to three axial compressive impacts of increasing energy (78.4, 107.8, and 137.2 J), whereas specimens in the other group were subjected to a single impact (137.2 J). Before and after the final trauma, multidirectional flexibility of each specimen was measured under flexion/extension, right/left lateral bending, and right/left axial rotation, thus quantifying the instability of the fracture. The flexibility parameters were then compared between the two groups. Results. A significant increase in flexibility parameters was found after the final trauma in both groups, indicating the instability of the spine (p < 0.01). No significant differences in flexibility parameters were observed in either intact status or injured status between the two groups (p > 0.05). Conclusions. In this study the authors have confirmed that the single and incremental impact protocols produced a similar degree of severity in producing an in vitro bovine burst fracture. The results of this study support the use of the incremental impact protocol in future experimental biomechanical studies.

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Kaibicheva, E. I. "Methodological approaches to the development of inter-municipal strategies in the context of core-periphery relations." Regional Economics: Theory and Practice 18, no. 6 (June 16, 2020): 1036–51. http://dx.doi.org/10.24891/re.18.6.1036.

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Subject. This article deals with the issues of development of inter-municipal strategies. Objectives. The article aims to identify methodological approaches to the development of inter-municipal strategies. Methods. For the study, I used the methods of analysis, synthesis, and generalization, as well as systems, geoeconomic, and incremental approaches. The core-periphery theory forms the methodological basis of the study. Results. The article substantiates the use of systems, geoeconomic, and incremental approaches to the development of inter-municipal strategies. The combination of these approaches will take into account the internal and external factors of a municipal units group. Conclusions. The geoeconomic approach helps consider municipal entities in the context of economic ties. The systems approach opens up opportunities for analysis of a selected group of municipalities. The incremental approach helps take into account the dynamic nature of the core-periphery relationships.

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Teljeur, Conor, Patricia Harrington, and Máirín Ryan. "OP53 Comparing Approaches To Univariate Sensitivity Analysis." International Journal of Technology Assessment in Health Care 34, S1 (2018): 20. http://dx.doi.org/10.1017/s0266462318001022.

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Introduction:Fully probabilistic analyses are now standard for economic models, with all parameters varied according to probability distributions. Using univariate sensitivity analyses to explore the influence of different parameters on the model results are also standard. Although there are several approaches available, there has been little discussion of the merits of each or justification for the method used in any given analysis. The aim of this study was to compare three approaches to univariate sensitivity analysis using a case study.Methods:We considered three univariate sensitivity analysis approaches: (i) set one parameter at its upper and lower bounds while all others are set at their mean value; (ii) analysis of variance; and (iii) set one parameter at its mean and vary all others. We compared these approaches using an economic model of mechanical thrombectomy for the treatment of acute ischemic stroke, considering outcomes of incremental costs, incremental quality-adjusted life-years (QALYs), and net monetary benefit (NMB).Results:For incremental costs and QALYs the correlation between the approaches was moderate to high, with correlation coefficients between 0.46 and 0.94. For NMB the correlation between approaches was also high (range 0.89 to 0.98), but some of the most influential parameters were ranked differently. Setting one parameter at its upper and lower bounds was the only method that facilitated an analysis of direction of influence.Conclusions:The three approaches addressed different but relevant questions. Setting individual parameters at their bounds is effectively a systematic scenario analysis and may be misleading to decision makers. Analysis of variance may be more easily interpreted, but it has disadvantages. Setting a parameter at its mean, while varying other parameters, is similar to value of information analysis. As with any sensitivity analysis, it is imperative that the uncertainty associated with each parameter is adequately captured in the model.

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MOUHOUB, MALEK, and SAMIRA SADAOUI. "SOLVING INCREMENTAL SATISFIABILITY." International Journal on Artificial Intelligence Tools 16, no. 01 (February 2007): 139–47. http://dx.doi.org/10.1142/s0218213007003254.

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Propositional satisfiability (SAT) problem is fundamental to the theory of NP-completeness. Indeed, using the concept of "polynomial-time reducibility" all NP-complete problems can be polynomially reduced to SAT. Thus, any new technique for satisfiability problems will lead to general approaches for thousands of hard combinatorial problems. In this paper, we introduce the incremental propositional satisfiability problem that consists of maintaining the satisfiability of a propositional formula anytime a conjunction of new clauses is added. More precisely, the goal here is to check whether a solution to a SAT problem continues to be a solution anytime a new set of clauses is added and if not, whether the solution can be modified efficiently to satisfy the old formula and the new clauses. We will study the applicability of systematic and approximation methods for solving incremental SAT problems. The systematic method is based on the branch and bound technique while the approximation methods rely on stochastic local search and genetic algorithms. Experimental tests, conducted on randomly generated SAT instances, demonstrate the efficiency in time of the approximation methods over the branch and bound algorithm. However these approximation methods do not always guarantee the completeness of the solution returned. We show that a method we propose that uses non systematic search in a limited form together with branch and bound has the best compromise, in practice, between time and quality of the solution returned (success ratio).

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Hann, David W., and Mark L. Hanus. "Evaluation of nonspatial approaches and equation forms used to predict tree crown recession." Canadian Journal of Forest Research 34, no. 10 (October 1, 2004): 1993–2003. http://dx.doi.org/10.1139/x04-076.

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Two nonspatial approaches for modeling tree crown recession (ΔHCB) were evaluated by using 5341 observations from Douglas-fir (Pseudotsuga menziesii (Mirb.) Franco). The first approach applies a static height-to-crown-base (HCB) equation at the start and end of the growth period and uses the difference in these predictions as an estimate of ΔHCB. This allometric method can be applied to species lacking ΔHCB data from permanent plots. The incremental method directly predicts ΔHCB from an equation developed from adequate permanent plot data. Two allometric and six incremental equation forms were examined. Also examined were three approaches for determining the end-of-growth-period tree and plot attributes used by the allometric method. Although the allometric method can produce unbiased estimates of ΔHCB, the best allometric equation forms explained about one-half of the variation explained by the best incremental equation form. The two best incremental equation forms were modifications of a nonlinear logistic equation form previously developed for Douglas-fir. The modifications included using measured stand age (BHA) or predicted tree growth effective age (GEA) instead of measured tree age. The best equation form used BHA, which limits its application to modeling data collected from just even-aged stands. The equation form using GEA could be applied to modeling data sets from both even- and uneven-aged stands.

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AÏT-MOKHTAR, S., J. P. CHANOD, and C. ROUX. "Robustness beyond shallowness: incremental deep parsing." Natural Language Engineering 8, no. 2-3 (June 2002): 121–44. http://dx.doi.org/10.1017/s1351324902002887.

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Robustness is a key issue for natural language processing in general and parsing in particular, and many approaches have been explored in the last decade for the design of robust parsing systems. Among those approaches is shallow or partial parsing, which produces minimal and incomplete syntactic structures, often in an incremental way. We argue that with a systematic incremental methodology one can go beyond shallow parsing to deeper language analysis, while preserving robustness. We describe a generic system based on such a methodology and designed for building robust analyzers that tackle deeper linguistic phenomena than those traditionally handled by the now widespread shallow parsers. The rule formalism allows the recognition of n-ary linguistic relations between words or constituents on the basis of global or local structural, topological and/or lexical conditions. It offers the advantage of accepting various types of inputs, ranging from raw to chunked or constituent-marked texts, so for instance it can be used to process existing annotated corpora, or to perform a deeper analysis on the output of an existing shallow parser. It has been successfully used to build a deep functional dependency parser, as well as for the task of co-reference resolution, in a modular way.

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Akrichi, Sofien, Amira Abbassi, Sabeur Abid, and Noureddine Ben yahia. "Roundness and positioning deviation prediction in single point incremental forming using deep learning approaches." Advances in Mechanical Engineering 11, no. 7 (July 2019): 168781401986446. http://dx.doi.org/10.1177/1687814019864465.

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This article proposes a deep learning technique for the prevision of the geometric accuracy in single point incremental forming. Moreover, predicting geometric accuracy is one of the most crucial measures of part quality. Accordingly, roundness and positioning deviation are two indicators for measuring geometric accuracy and presenting two output variables. Two types of artificial intelligence learning approaches, that is, shallow learning and deep learning, are investigated and compared for forecasting geometrical accuracy in the single point incremental forming process. Therefore, the back-propagation neural network with one hidden layer is selected as the representative for shallow learning and deep belief network and stack autoencoder are chosen as the representatives for deep learning. Accurate prediction is closely related to the feature learning of single point incremental forming process parameters. The following six parameters were considered as input variables: sheet thickness, tool path direction, step depth, speed rate, feed rate, and wall angle. The results of these studies indicate that deep learning could be a powerful tool in the current search for geometric accuracy prediction in single point incremental forming. Otherwise, the deep learning approach shows the best performance prediction with shallow learning. In addition, the deep belief network model achieves superior performance accuracy for the prediction of roundness and position deviation in comparison with the stack autoencoder approach.

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Mehrotra, Rahul, ShowkatHussain Bhat, and Abinav Jain. "Recent trials exploring newer approaches for incremental reduction in cardiovascular risk." Journal of Clinical and Preventive Cardiology 7, no. 2 (2018): 79. http://dx.doi.org/10.4103/jcpc.jcpc_11_18.

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Sang, Binbin, Hongmei Chen, Lei Yang, Dapeng Zhou, Tianrui Li, and Weihua Xu. "Incremental attribute reduction approaches for ordered data with time-evolving objects." Knowledge-Based Systems 212 (January 2021): 106583. http://dx.doi.org/10.1016/j.knosys.2020.106583.

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Heinrich, Janet. "Incremental approaches to necessary health care reform lead to more chaos." Nursing Outlook 46, no. 3 (May 1998): 137–39. http://dx.doi.org/10.1016/s0029-6554(98)90042-2.

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35

Luo, Chuan, Tianrui Li, Hongmei Chen, and Dun Liu. "Incremental approaches for updating approximations in set-valued ordered information systems." Knowledge-Based Systems 50 (September 2013): 218–33. http://dx.doi.org/10.1016/j.knosys.2013.06.013.

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Yang, Xin, Dun Liu, Xibei Yang, Keyu Liu, and Tianrui Li. "Incremental fuzzy probability decision-theoretic approaches to dynamic three-way approximations." Information Sciences 550 (March 2021): 71–90. http://dx.doi.org/10.1016/j.ins.2020.10.043.

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Prevedello, Daniel M., Amin B. Kassam, Ricardo Carrau, Paul Gardner, Adam Zanation, Arlan Mintz, and Carl Snyderman. "The expanded endoscopic endonasal approaches for the skull base." JBNC - JORNAL BRASILEIRO DE NEUROCIRURGIA 19, no. 2 (March 7, 2018): 18–29. http://dx.doi.org/10.22290/jbnc.v19i2.663.

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Background: Endoscopic endonasal approach (EEA) for skull base surgery (SBS) is a significant modification of the current practice. Methods: We reviewed our experience at the University of Pittsburgh with EEAs for 800 patients from 1998 to July 2007. Results: Modular approaches to multiple pathologies of the skull base were designed totally based on intrinsic anatomy. Stages of training were established based on the level of technical difficulty and potential risk of vascular and neural injury. Five levels were defined in an incremental manner. Conclusions: Practice standardization with modular, incremental training is projected to facilitate the gaining of knowledge and skills to safely master EEAs for SBS in an organized manner. We suggest adherence to the systematic acquisition of endoscopic skills, to work as an integrated team of surgeons and to have a thorough perspective of conventional SBS and endoscopic surgery. Therefore, the choice of approach must be a specific function of the anatomy and pathology rather than the surgeon’s bias or lack of experience with alternative approaches.

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Patel, Sanjay, and Dr Ketan Kotecha. "Incremental Frequent Pattern Mining using Graph based approach." INTERNATIONAL JOURNAL OF COMPUTERS & TECHNOLOGY 4, no. 2 (November 30, 2005): 731–36. http://dx.doi.org/10.24297/ijct.v4i2c2.4191.

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Extracting useful information from huge amount of data is known as Data Mining. It happens at the intersection of artificial intelligence and statistics. It is also defined as the use of computer algorithms to discover hidden patterns and interesting relationships between items in large datasets. Candidate generation and test, Pattern Growth etc. are the common approaches to find frequent patterns from the database. Incremental mining is a crucial requirement for the industries nowadays. Many tree based approaches have tried to extend the frequent pattern mining as an incremental approach, but most of the research was limited to interactive mining only. Here, instead of tree based approach, graph based approach is presented which also gives good results for incremental mining. Â

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Takacs, Lawrence L., Max J. Suárez, and Ricardo Todling. "The Stability of Incremental Analysis Update." Monthly Weather Review 146, no. 10 (September 18, 2018): 3259–75. http://dx.doi.org/10.1175/mwr-d-18-0117.1.

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Abstract A recent attempt to downscale the 50-km MERRA-2 analyses to 7 km revealed an instability associated with the incremental analysis update (IAU) procedure that has thus far gone unnoticed. A theoretical study based on a simple damped harmonic oscillator with complex frequency provides the framework to diagnose the problem and suggests means to avoid it. Three possible approaches to avoid the instability are to (i) choose an “ideal” ratio of the lengths of the predictor and corrector steps of IAU based on a theoretical stability diagram, (ii) time average the background fields used to construct the IAU tendencies with given frequency, or (iii) apply a digital filter modulation to the IAU tendencies. All these are shown to control the instability for a wide range of resolutions when doing up- or downscaling, experiments with the NASA GMAO atmospheric general circulation model. Furthermore, it is found that combining IAU with the ensemble recentering step typical of hybrid ensemble–variational approaches also results in an instability based on the same mechanisms in the members of the ensemble. An example of such occurrence arises in an experiment performed with the GMAO 12.8-km hybrid 4D-EnVar system. Modulation of the ensemble IAU tendencies with a digital filter is shown to avoid the instability. In addition, the stability of certain 4D incremental analysis update (4DIAU) implementations is analyzed and a suggestion is made to improve its results, though a complete study of this subject is postponed to a follow-up work.

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Ansari, Fazel, Madjid Fathi, and Ulrich Seidenberg. "Problem-solving approaches in maintenance cost management: a literature review." Journal of Quality in Maintenance Engineering 22, no. 4 (October 10, 2016): 334–52. http://dx.doi.org/10.1108/jqme-04-2015-0012.

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Purpose The purpose of this paper is to investigate the use of problem-solving approaches in maintenance cost management (MCM). In particular, the paper aims to examine characteristics of MCM models and to identify patterns for classification of problem-solving approaches. Design/methodology/approach This paper reflects an extensive and detailed literature survey of 68 (quantitative or qualitative) cost models within the scope of MCM published in the period from 1969 to 2013. The reviewed papers have been critically examined and classified based on implementing a morphological analysis which employs eight criteria and associated expressions. In addition, the survey identified two main perspectives of problem solving: first, synoptic/incremental and second, heuristics/meta-heuristics. Findings The literature survey revealed the patterns for classification of the MCM models, especially the characteristics of the models for problem-solving in association with the type of modeling, focus of purpose, extent and scope of application, and reaction and dynamics of parameters. Majority of the surveyed approaches is mathematical, respectively, synoptic. Incremental approaches are much less and only few are combined (i.e. synoptic and incremental). A set of features is identified for proper classification, selection, and coexistence of the two approaches. Research limitations/implications This paper provides a basis for further study of heuristic and meta-heuristic approaches to problem-solving. Especially the coexistence of heuristic, synoptic, and incremental approaches needs to be further investigated. Practical implications The detected dominance of synoptic approaches in literature – especially in the case of specific application areas – contrasts to some extent to the needs of maintenance managers in practice. Hence the findings of this paper particularly address the need for further investigation on combining problem-solving approaches for improving planning, monitoring, and controlling phases of MCM. Continuous improvement of MCM, especially problem-solving and decision-making activities, is tailored to the use of maintenance knowledge assets. In particular, maintenance management systems and processes are knowledge driven. Thus, combining problem-solving approaches with knowledge management methods is of interest, especially for continuous learning from past experiences in MCM. Originality/value This paper provides a unique study of 68 problem-solving approaches in MCM, based on a morphological analysis. Hence suitable criteria and their expressions are provided. The paper reveals the opportunities for further interdisciplinary research in the maintenance cost life cycle.

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LETOMBE, FLORIAN, and JOAO MARQUES-SILVA. "HYBRID INCREMENTAL ALGORITHMS FOR BOOLEAN SATISFIABILITY." International Journal on Artificial Intelligence Tools 21, no. 06 (December 2012): 1250025. http://dx.doi.org/10.1142/s021821301250025x.

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Boolean Satisfiability (SAT) solvers have been successfully applied to a wide range of practical applications, including hardware model checking, software model finding, equivalence checking, and planning, among many others. SAT solvers are also the building block of more sophisticated decision procedures, including Satisfiability Modulo Theory (SMT) solvers. The large number of applications of SAT yields ever more challenging problem instances, and motivate the development of more efficient algorithms. Recent work studied hybrid approaches for SAT, which involves integrating incomplete and complete SAT solvers. This paper proposes a number of improvements to hybrid SAT solvers. Experimental results demonstrate that the proposed optimizations are effective. The resulting algorithms in general perform better and, more importantly, are significantly more robust.

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Flechas Chaparro, Ximena Alejandra, Leonardo Augusto de Vasconcelos Gomes, and Paulo Tromboni de Souza Nascimento. "The evolution of project portfolio selection methods: from incremental to radical innovation." Revista de Gestão 26, no. 3 (July 15, 2019): 212–36. http://dx.doi.org/10.1108/rege-10-2018-0096.

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Purpose The purpose of this paper is to identify how project portfolio selection (PPS) methods have evolved and which approaches are more suitable for radical innovation projects. This paper addressed the following research question: how have the selection approaches evolved to better fit within radical innovation conditions? The current literature offers a number of selection approaches with different and, in some cases, conflicting nature. Therefore, there is a lack of understanding regarding when and how to use these approaches in order to select a specific type of innovation projects (from incremental to more radical ones). Design/methodology/approach Given the nature of the research question, the authors perform a systematic literature review method and analyze 48 portfolio selection approaches. The authors then classified and characterized these articles in order to identify techniques, tools, required data and types of examined projects, among other aspects. Findings The authors identify four key features related to the selection of radical innovation projects: dynamism, interdependency management, uncertainty treatment and required input data. Based on the content analysis, the authors identified that approaches based on different sources and nature of data are more appropriated for uncertain conditions, such as behavioral methods, information gap theory, real options and integrated approaches. Originality/value The research provides a comprehensive framework about PPS methods and how they have been evolving over time. This portfolio selection framework considers the particular aspects of incremental and radical innovation projects. The authors hope that the framework contributes to reinvigorating the literature on selection approaches for innovation projects.

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Wang, Ting, Sheng-Uei Guan, Sadasivan Puthusserypady, and Prudence W. H. Wong. "Statistical Discriminability Estimation for Pattern Classification Based on Neural Incremental Attribute Learning." International Journal of Applied Evolutionary Computation 5, no. 2 (April 2014): 37–57. http://dx.doi.org/10.4018/ijaec.2014040103.

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Feature ordering is a significant data preprocessing method in Incremental Attribute Learning (IAL), a novel machine learning approach which gradually trains features according to a given order. Previous research has shown that, similar to feature selection, feature ordering is also important based on each feature's discrimination ability, and should be sorted in a descending order of their discrimination ability. However, such an ordering is crucial for the performance of IAL. As the number of feature dimensions in IAL is increasing, feature discrimination ability also should be calculated in the corresponding incremental way. Based on Single Discriminability (SD), where only the feature discrimination ability is computed, a new filter statistical feature discrimination ability predictive metric, called the Accumulative Discriminability (AD), is designed for the dynamical feature discrimination ability estimation. Moreover, a criterion that summarizes all the produced values of AD is employed with a GA (Genetic Algorithm)-based approach to obtain the optimum feature ordering for classification problems based on neural networks by means of IAL. Compared with the feature ordering obtained by other approaches, the method proposed in this paper exhibits better performance in the final classification results. Such a phenomenon indicates that, (i) the feature discrimination ability should be incrementally estimated in IAL, and (ii) the feature ordering derived by AD and its corresponding approaches are applicable with IAL.

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Hu, Chengxiang, and Li Zhang. "Efficient approaches for maintaining dominance-based multigranulation approximations with incremental granular structures." International Journal of Approximate Reasoning 126 (November 2020): 202–27. http://dx.doi.org/10.1016/j.ijar.2020.08.005.

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Medina-Sanchez, Gustavo, Alberto Garcia-Collado, Diego Carou, and Rubén Dorado-Vicente. "Force Prediction for Incremental Forming of Polymer Sheets." Materials 11, no. 9 (September 3, 2018): 1597. http://dx.doi.org/10.3390/ma11091597.

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Incremental sheet forming (ISF) is gaining attention as a low cost prototyping and small batch production solution to obtain 3D components. In ISF, the forming force is key to define an adequate setup, avoiding damage and reducing wear, as well as to determine the energy consumption and the final shape of the part. Although there are several analytical, experimental and numerical approaches to estimate the axial forming force for metal sheets, further efforts must be done to extend the study to polymers. This work presents two procedures for predicting axial force in Single Point Incremental Forming (SPIF) of polymer sheets. Particularly, a numerical model based on the Finite Element Model (FEM), which considers a hyperelastic-plastic constitutive equation, and a simple semi-analytical model that extends the known specific energy concept used in machining. A set of experimental tests was used to validate the numerical model, and to determine the specific energy for two polymer sheets of polycarbonate (PC) and polyvinyl chloride (PVC). The approaches provide results in good agreement with additional real examples. Moreover, the numerical model is useful for accurately predicting temperature and thickness.

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Martinez-Gil, Jorge. "Accurate Semantic Similarity Measurement of Biomedical Nomenclature by Means of Fuzzy Logic." International Journal of Uncertainty, Fuzziness and Knowledge-Based Systems 24, no. 02 (April 2016): 291–305. http://dx.doi.org/10.1142/s0218488516500148.

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Semantic similarity measurement of biomedical nomenclature aims to determine the likeness between two biomedical expressions that use different lexicographies for representing the same real biomedical concept. There are many semantic similarity measures for trying to address this issue, many of them have represented an incremental improvement over the previous ones. In this work, we present yet another incremental solution that is able to outperform existing approaches by using a sophisticated aggregation method based on fuzzy logic. Results show us that our strategy is able to consistently beat existing approaches when solving well-known biomedical benchmark data sets.

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Kumar, Manoj, and Hemant Kumar Soni. "A Comparative Study of Tree-Based and Apriori-Based Approaches for Incremental Data Mining." International Journal of Engineering Research in Africa 23 (April 2016): 120–30. http://dx.doi.org/10.4028/www.scientific.net/jera.23.120.

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Association rule mining is an iterative and interactive process of discovering valid, novel, useful, understandable and hidden associations from the massive database. The Colossal databases require powerful and intelligent tools for analysis and discovery of frequent patterns and association rules. Several researchers have proposed the many algorithms for generating item sets and association rules for discovery of frequent patterns, and minning of the association rules. These proposals are validated on static data. A dynamic database may introduce some new association rules, which may be interesting and helpful in taking better business decisions. In association rule mining, the validation of performance and cost of the existing algorithms on incremental data are less explored. Hence, there is a strong need of comprehensive study and in-depth analysis of the existing proposals of association rule mining. In this paper, the existing tree-based algorithms for incremental data mining are presented and compared on the baisis of number of scans, structure, size and type of database. It is concluded that the Can-Tree approach dominates the other algorithms such as FP-Tree, FUFP-Tree, FELINE Alorithm with CATS-Tree etc.This study also highlights some hot issues and future research directions. This study also points out that there is a strong need for devising an efficient and new algorithm for incremental data mining.

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D., Karthika. "A Comparative Study of Incremental Semi-Supervised Subspace Clustering Ensemble Approaches and Performance Outcomes for High Dimensional Data." Journal of Advanced Research in Dynamical and Control Systems 24, no. 4 (March 31, 2020): 195–202. http://dx.doi.org/10.5373/jardcs/v12i4/20201433.

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Madsen, Diana, Ove Christiansen, and Carolin König. "Anharmonic vibrational spectra from double incremental potential energy and dipole surfaces." Physical Chemistry Chemical Physics 20, no. 5 (2018): 3445–56. http://dx.doi.org/10.1039/c7cp07190f.

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Suntaxi, Carlos, Gabriel Centeno, M. Beatriz Silva, Carpóforo Vallellano, and Paulo A. F. Martins. "Tube Expansion by Single Point Incremental Forming: An Experimental and Numerical Investigation." Metals 11, no. 9 (September 17, 2021): 1481. http://dx.doi.org/10.3390/met11091481.

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In this paper, we revisit the formability of tube expansion by single point incremental forming to account for the material strain hardening and the non-proportional loading paths that were not taken into consideration in a previously published analytical model of the process built upon a rigid perfectly plastic material. The objective is to provide a new insight on the reason why the critical strains at failure of tube expansion by single point incremental forming are far superior to those of conventional tube expansion by rigid tapered conical punches. For this purpose, we replaced the stress triaxiality ratio that is responsible for the accumulation of damage and cracking by tension in monotonic, proportional loading paths, by integral forms of the stress triaxiality ratio that are more adequate for the non-proportional paths resulting from the loading and unloading cycles of incremental tube expansion. Experimental and numerical simulation results plotted in the effective strain vs. stress triaxiality space confirm the validity of the new damage accumulation approach for handling the non-proportional loading paths that oscillate cyclically from shearing to biaxial stretching, as the single point hemispherical tool approaches, contacts and moves away from a specific location of the incrementally expanded tube surface.

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