Incremental Process Research Articles

Levering change: the contributory role of a mathematics teaching framework

Levering change is hard, and an incremental process. In the education process it requires an interaction between teachers, resources and learners. Levering change with human resources—teachers themselves, is a long term, time-intensive process requiring investment and commitment. The teacher–resources relationship is complex and not always optimal, particularly in disadvantaged educational environments where resources are constrained, and the education system is centralized and highly regulated. This article posits a mathematics teaching framework developed in a low-income educational context to make more transparent the relationship between teachers and resources to the benefit of learning both of teachers and of learners.

Online support vector quantile regression for the dynamic time series with heavy-tailed noise

In this paper, we propose an online support vector quantile regression approach with an ɛ-insensitive pinball loss function, called Online-SVQR, for dynamic time series with heavy-tailed noise. Online-SVQR is robust to heavy-tailed noise, as it can control the negative influence of heavy-tailed noise by using a quantile parameter. By using an incremental learning algorithm to update the new samples, the coefficients of Online-SVQR reflect the dynamic information in the examined time series. During each incremental training process, the nonsupport vector is ignored while the support vector continues training with new updated samples. Online-SVQR can select useful training samples and discard irrelevant samples. As a result, the training speed of Online-SVQR is accelerated. Experimental results on one artificial dataset and three real-world datasets indicate that Online-SVQR outperforms ɛ-support vector quantile regression in terms of both sample selection ability and training speed.

Adaptation of the Newton-Raphson and Potra-Pták methods for the solution of nonlinear systems

In this paper we adapt the Newton-Raphson and Potra-Pták algorithms by combining them with the modified Newton-Raphson method by inserting a condition. Problems of systems of sparse nonlinear equations are solved the algorithms implemented in Matlab® environment. In addition, the methods are adapted and applied to space trusses problems with geometric nonlinear behavior. Structures are discretized by the Finite Element Positional Method, and nonlinear responses are obtained in an incremental and iterative process using the Linear Arc-Length path-following technique. For the studied problems, the proposed algorithms had good computational performance reaching the solution with shorter processing time and fewer iterations until convergence to a given tolerance, when compared to the standard algorithms of the Newton-Raphson and Potra-Pták methods.

Secure and verifiable outsourced data dimension reduction on dynamic data

Dimensionality reduction aims at reducing redundant information in big data and hence making data analysis more efficient. Resource-constrained enterprises or individuals often outsource this time-consuming job to the cloud for saving storage and computing resources. However, due to inadequate supervision, the privacy and security of outsourced data have been a serious concern to data owners. In this paper, we propose a privacy-preserving and verifiable outsourcing scheme for data dimension reduction, based on incremental Non-negative Matrix Factorization (NMF) method. We emphasize the importance of incremental data processing, exploiting the properties of NMF to enable data dynamics in consideration of data updating in reality. Besides, our scheme can also maintain data confidentiality and provide verifiability of the computation result. Experiment evaluation has shown that the proposed scheme achieves high efficiency, saving about more than 80% computation time for clients.

Evolution of the universe from the perspective of entropy and information

Entropy is a key concept widely used in physics and other fields. At the same time, the meaning of entropy with different names and the relationship among them are confusing. In this paper, we discuss the relationship among the Clausius entropy, Boltzmann entropy and information entropy and further show that the three kinds of entropy are equivalent to each other to some extent. Moreover, we point out that the evolution of the universe is a process of entropy increment and life originates from the original low entropy of the universe. Finally, we discuss the evolution of the entire universe composed of the cosmological horizon and the space surrounded by it and interpret the entropy as a measure of information of all microstates corresponding to a certain macrostate. Under this explanation, the thermodynamic entropy and information entropy are unified and we can conclude that the sum of the entropy of horizon and the entropy of matter in the space surrounded by the horizon does not decrease with time if the second law of thermodynamics holds for the entire universe.

Between Novelty and Variability: Natufian Hunter-Gatherers (c. 15–11.7 kyr) Proto-Agrotechnology and the Question of Morphometric Variations of the Earliest Sickles

How hunter-gatherers manipulated and utilised their natural surroundings is a widely studied topic among anthropologists and archaeologists alike. This focuses on the Natufian culture of the Late Epipalaeolithic period (c.15–11.7 kyr), the last Levantine hunter-gatherer population, and specifically on the earliest composite tools designed for harvesting. These tools are widely referred to as sickles. They consisted of a haft into which a groove was cut and flint inserts affixed. This revolutionised harvesting and established it on new grounds. While the plants manipulated by these tools are yet to be identified with certainty, it is evident that these implements were rapidly integrated and dispersed throughout the Natufian interaction sphere, suggesting that they provided a significant advantage, which probably constituted a critical step toward agriculture. At the same time, the Natufian haft assemblage demonstrates high morphometric variability. We review the available data concerning Natufian hafts and offer three possible models to explain the noted variability. We conclude that while these models are not mutually exclusive, this varied technological pattern is best understood as deriving from a protracted formative phase of technological development, progressing through incremental processes of trial and error.

Studying Formability Limits By Combining Conventional and Incremental Sheet Forming Process

In this work it is assessed the potential of combining conventional and incremental sheet forming processes in a same sheet of metal. This so-called hybrid forming approach is performed through the manufacture of a pre-forming by conventional forming, followed by incremental sheet forming. The main objective is analyzing strain evolution. The pre-forming induced in the conventional forming stage will determine the strain paths, directly influencing the strains produced by the incremental process. To conduct the study, in the conventional processes, strains were imposed in three different ways with distinct true strains. At the incremental stage, the pyramid strategy was adopted with different wall slopes. From the experiments, the true strains and the final geometries were analyzed. Numerical simulation was also employed for the sake of comparison and correlation with the measured data. It could be observed that single-stretch pre-strain was directly proportional to the maximum incremental strains achieved, whereas samples subjected to biaxial pre-strain influenced the formability according to the degree of pre-strain applied. Pre-strain driven by the prior deep-drawing operation did not result, in this particular geometry, in increased formability.

Processing cataphors: Active antecedent search is persistent

Cataphors precede their antecedents, so they cannot be fully interpreted until those antecedents are encountered. Some researchers propose that cataphors trigger an active search during incremental processing in which the parser predictively posits potential antecedents in upcoming syntactic positions (Kazanina et al., Journal of Memory and Language, 56[3], 384–409, 2007). One characteristic of active search is that it is persistent: If a prediction is disconfirmed in an earlier position, the parser should iteratively search later positions until the predicted element is found. Previous research has assumed, but not established, that antecedent search is persistent. In four experiments in English and Norwegian, we test this hypothesis. Two sentence completion experiments show a strong off-line preference for coreference between a fronted cataphor and the first available argument position (the main subject). When the main subject cannot be the antecedent, participants posit the antecedent in the next closest position: object position. Two self-paced reading studies demonstrate that comprehenders actively expect the antecedent of a fronted cataphor to appear in the main clause subject position, and then successively in object position if the subject does not match the cataphor in gender. Our results therefore support the claim that antecedent search is active and persistent.

Principle B constrains the processing of cataphora: Evidence for syntactic and discourse predictions

We tested whether comprehenders can use Binding Principle B (Chomsky, 1981) to guide antecedent search during the processing of cataphoric pronouns. We ran two self-paced reading experiments using the gender mismatch paradigm (van Gompel & Liversedge, 2003) as an index of active prediction of coreference between a cataphor and a main clause subject. In both experiments, we find gender mismatch effects at the main clause subject when coreference with the cataphor is grammatically acceptable. We do not find comparable gender mismatch effects in conditions where coreference is ruled out by Principle B. Our results are broadly consistent with models in which grammatical constraints serve as early filters on anaphora resolution processes in comprehension. We illustrate how the parser can integrate syntactic and discourse-level information to achieve grammatical sensitivity during incremental referential processing.

Mechanisms for Financing Incremental Housing in Nigeria: Case study of Ibadan, Nigeria

Access to housing finance by all income groups is essential for the provision of adequate shelter for all. The study examined the mechanisms for financing incremental housing for the low and moderate income households in Ibadan, Nigeria and their effectiveness with a view to providing information that could inform policy towards effective incremental housing delivery in the study area. Primary data was collected with the use of questionnaire from 742 respondents from 4 randomly selected suburban local government areas of Ibadan, Nigeria. Two sets of questionnaires were used to obtain the data needed for the study. The results of the quantitative data were presented in both descriptive and inferential statistics while qualitative data were contextually reported. The results for housing development of the low and moderate income groups occurred in phases with the incremental process taking as much as 8-12 years for construction while improvement of the existing structure took about five and a half years. Chi-square analysis with values being significant at p<0.05indicated the financing mechanisms for incremental housing construction at the level of foundation (0.007), main structure (0.0005), roofing (0.002) and internal fixtures (0.000) vary significantly with the exception of land purchase and drainage cum sewage stages. Funding for the incremental housing process can be improved if the socio-economic and traditional attributes of the people in the area are promoted. This needs to be encouraged as a way of directing the financing mechanisms devoid of interest rate and default risks to incremental housing.

Automating incremental graph processing with flexible memoization

The ever-growing amount of dynamic graph data demands efficient techniques of incremental graph processing. However, incremental graph algorithms are challenging to develop. Existing approaches usually require users to manually design nontrivial incremental operators, or choose different memoization strategies for certain specific types of computation, limiting the usability and generality. In light of these challenges, we propose Ingress, an automated system for <u>in</u>cremental <u>g</u>raph proc<u>ess</u>ing. Ingress is able to incrementalize batch vertex-centric algorithms into their incremental counterparts as a whole, without the need of redesigned logic or data structures from users. Underlying Ingress is an automated incrementalization framework equipped with four different memoization policies, to support all kinds of vertex-centric computations with optimized memory utilization. We identify sufficient conditions for the applicability of these policies. Ingress chooses the best-fit policy for a given algorithm automatically by verifying these conditions. In addition to the ease-of-use and generalization, Ingress outperforms state-of-the-art incremental graph systems by 15.93X on average (up to 147.14X) in efficiency.

Engagement, involvement and empowerment: Three realms of a coproduction framework for climate services

While knowledge coproduction between climate scientists and climate information users has become a common theme in the climate services discourse, the interface between climate service providers and users is an aspect of climate services projects that still calls for more attention. This is due in part to the dominance of the physical sciences in these projects, as well as the prevalence of an instrumental and narrow interpretation of coproduction. Following up on the World Meteorological Organisation’s Guidance on Good Practices for Climate Services User Engagement, and incorporating insights from the social and human sciences, we develop a coproduction framework for climate services to help establish a smooth and effective interface between scientists and stakeholders. This framework is intended for research and innovation projects developing climate knowledge and services. The coproduction framework comprises three realms: (i) engagement using various communication channels; (ii) involvement through interviews, workshops and webinars; and (iii) empowerment of stakeholders and scientists through focused relationships. This incremental participatory process involves stakeholders in increasingly profound ways: from a broad stakeholder group identified through awareness-raising campaigns, on to potential users with whom we exchange knowledge, and then to a set of “champion users” who co-develop the service and pioneer its use in decision-making processes. This paper illustrates the application of the coproduction framework in PRIMAVERA, an EU H2020-funded project for designing, running and testing new high-resolution global climate models and evaluating their outputs. While PRIMAVERA provided ground breaking scientific findings that could potentially benefit various stakeholders and support climate risk assessment activities, these results are highly specialised and their added value has yet to be assessed. Accordingly, the user engagement component of the project faced the challenging task of both motivating stakeholders’ participation in the project and motivating future users of potential services based on PRIMAVERA data. The trial of the framework in PRIMAVERA provided key lessons for enhancing coproduction in research and innovation projects. We demonstrate how the role of scientists gradually shifted in this coproduction cycle from masters of knowledge(Roux et al., 2017) to co-learners, and how the involvement of the project’s interdisciplinary team and their interaction with stakeholders served to move the project towards transdisciplinary knowledge production.

Geometry Compensation Methods for Increasing the Accuracy of the SPIF Process

Despite years of supporting research, commercial use of the Single Point Incremental Forming process remains very limited. The promised flexibility and lack of specific tooling is contradicted by its highly complex deformation mechanics, resulting in a process that is easy to implement but where workpiece accuracy is very difficult to control. This paper looks at geometry compensation as a viable control strategy to increase the accuracy of produced workpieces. The input geometry of the process can be compensated using knowledge about the deformations occurring during production. The deviations between the nominal CAD geometry and the actual produced geometry can be calculated in a variety of different ways, thus directly influencing the compensation. Two different alignment methods and three deviation calculation methods are explained in detail. Six combined deviation calculation methods are used to generate compensated inputs, which are experimentally produced and compared to the uncompensated part. All different methods are able to noticeably improve the accuracy, with the production alignment and closest point deviation calculation achieving the best results

Stability analysis of incremental concept tree for concept cognitive learning

Incremental concept cognitive learning is an emerging active issue that concerning incremental concept learning and dynamic knowledge processing in the dynamic context environments. As the development of that, how to measure the stability of a concept structure in the view of concept cognitive learning has become an urgent issue need to be solved. Motivated by that, we propose a method to analyze the stability of incremental concept tree (ICT) for concept cognitive learning. First, the incremental concept cognitive learning process is visualized in the form of ICT, and then the structure similarity based on concept subtree and the node similarity based on concept importance are carried out to measure the similarity along the evolution of ICT. At last, the global similarity of ICT is obtained by integrating these two similarity measurements by the regulatory factor according to different scenarios. Some numerical experiments compared with classical tree similarity algorithm were conducted to evaluate the effectiveness of our method. The results show that our method is effective to analyze the stability of concept cognitive learning by measuring the similar of ICT and promising to expand it to the field of incremental concept cognitive learning.

Heat-assisted incremental bending of metal plates with unsymmetrical curvatures

Small-batched metal plates with free-form surfaces are widely used in different manufacturing industries; however, it is unrealistic to produce such metal plates based on traditional die stamping and rolling processes. Over the last few decades, numerous efforts have been adopted to produce the metal plates with free-form surfaces with acceptable quality, efficiency, and cost through flexible forming processes. In the present paper, a heat-assisted incremental bending process was proposed to manufacture metal plates with large unsymmetrical curvatures. The test metal plates were supported by some hydraulic cylinders, and the punch moved up and down to press the metal plates according to the loading path determined by the minimum energy method. In addition, an induction heating system was applied to heat the metal plates at the punching position. One objective metal plate with large unsymmetrical curvature is deformed based on the heat-assisted incremental bending experiments. The obtained results indicate that the proposed thermo-mechanical flexible forming process could produce complex metal plates with good accuracy and high efficiency.

Manufacture and mechanical properties of knee implants using SWCNTs/UHMWPE composites

This article focuses on obtaining ultra high molecular weight polyethylene (UHMWPE) material reinforced with functionalized single-walled carbon nanotubes (f-SWCNTs) and the manufacturing of unicompartmental knee implants via Single-Point Incremental Forming process (SPIF). The physicochemical properties of the developed UHMWPE reinforced with 0.01 and 0.1 wt% concentrations of f-SWCNTs are investigated using Raman and Thermogravimetic Analysis (TGA). Tensile mechanical tests performed in the nanocomposite material samples reveal a 12% improvement in their Young's modulus when compare to that of the pure UHMWPE material samples. Furthermore, the surface biocompatibility of the UHMWPE reinforced with f-SWCNTs materials samples was evaluated with human osteoblast cells. Results show cell viability enhancement with good cell growth and differentiation after 14 incubation days, that validates the usefulness of the developed nanocomposite material in the production of hip and knee artificial implants, and other biomedical applications.

Incremental Language Comprehension Difficulty Predicts Activity in the Language Network but Not the Multiple Demand Network.

What role do domain-general executive functions play in human language comprehension? To address this question, we examine the relationship between behavioral measures of comprehension and neural activity in the domain-general "multiple demand" (MD) network, which has been linked to constructs like attention, working memory, inhibitory control, and selection, and implicated in diverse goal-directed behaviors. Specifically, functional magnetic resonance imaging data collected during naturalistic story listening are compared with theory-neutral measures of online comprehension difficulty and incremental processing load (reading times and eye-fixation durations). Critically, to ensure that variance in these measures is driven by features of the linguistic stimulus rather than reflecting participant- or trial-level variability, the neuroimaging and behavioral datasets were collected in nonoverlapping samples. We find no behavioral-neural link in functionally localized MD regions; instead, this link is found in the domain-specific, fronto-temporal "core language network," in both left-hemispheric areas and their right hemispheric homotopic areas. These results argue against strong involvement of domain-general executive circuits in language comprehension.

Conditionally independent increment processes for modeling electricity prices with regard to renewable power generation

Renewable energies have become responsible for a large part of the variation in electricity prices. We offer a new approach that makes it possible to represent this dependency in a flexible way. This allows to vary especially price spikes both in direction and size according to the generation of wind and solar power. The proposed concept is based on the construction of a process with conditionally independent increment. We provide an estimation procedure for them and offer a test to verify the dependency on an external variable. Based on the theoretical results, we fit an electricity price model for the German intraday market and use it to analyze power cap/floor prices.

NFR‐aware prioritization of software requirements

AbstractNon‐functional requirements (NFRs) play a significant role in the software development process. However, the classical requirement prioritization methods for incremental software development, typically, consider the attributes of functional features only, often neglecting the non‐functional constraints. This might lead to catastrophic defects in the system design, as the conflicts among the NFRs are ignored. In this paper, a novel prioritization approach for functional requirements (FRs) is introduced within the incremental software development process. The proposed approach considers the conflicts among NFRs, in the prioritization process, to minimize the incon sistencies of software development. The devised NFR‐aware prioritization algorithm can be tuned according to the weights that the analyst assigns to NFR conflicts and FR‐NFR dependencies. We have assessed our prioritization approach using available requirements data sets and have compared the results in different scenarios.

The online processing of causal and concessive discourse connectives

AbstractWhile there is a substantial amount of evidence for language processing being a highly incremental and predictive process, we still know relatively little about how top-down discourse based expectations are combined with bottom-up information such as discourse connectives. The present article reports on three experiments investigating this question using different methodologies (visual world paradigm and ERPs) in two languages (German and English). We find support for highly incremental processing of causal and concessive discourse connectives, causing anticipation of upcoming material. Our visual world study shows that anticipatory looks depend on the discourse connective; furthermore, the German ERP study revealed an N400 effect on a gender-marked adjective preceding the target noun, when the target noun was inconsistent with the expectations elicited by the combination of context and discourse connective. Moreover, our experiments reveal that the facilitation of downstream material based on earlier connectives comes at the cost of reversing original expectations, as evidenced by a P600 effect on the concessive relative to the causal connective.