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To reduce the electricity consumption in our homes, a first step is to make the user aware of it. Reading a meter once in a month is not enough, instead, it requires real-time meter reading. Smart electricity meter (SEM) is capable of providing a quick and exact meter reading in real-time at regular time intervals. SEM generates a considerable amount of household electricity consumption data in an incremental manner. However, such data has embedded load patterns and hidden information to extract and learn consumer behavior. The extracted load patterns from data clustering should be updated because consumer behaviors may be changed over time. The purpose of this study is to update the new clustering results based on the old data rather than to re-cluster all of the data from scratch.

This paper proposes an incremental clustering with nearness factor (ICNF) algorithm to update load patterns without overall daily load curve clustering.

Extensive experiments are implemented on real-world SEM data of Irish Social Science Data Archive (Ireland) data set. The results are evaluated by both accuracy measures and clustering validity indices, which indicate that proposed method is useful for using the enormous amount of smart meter data to understand customers’ electricity consumption behaviors.

ICNF can provide an efficient response for electricity consumption patterns analysis to end consumers via SEMs.

A new spatial reasoning algorithm that can be used in multi‐body contact detection is presented. The algorithm achieves the partitioning of N bodies of arbitrary shape and size into N lists in order O(N) operations, where each list consists of bodies spatially near to the target object. The algorithm has been tested for objects of arbitrary shape and size, in two and three dimensions. However, we believe that it can be extended to dimensions of four and higher. The algorithm (CGRID) is a binning algorithm that extends traditional binning algorithms so that the arbitrary sizes and shapes can be handled efficiently. The algorithm has applications in discrete element, finite element, molecular dynamics, meshless methods, and lattice‐Boltzmann codes and also in domains such as path planning, target acquisition and general clustering problems.

The feasibility and desirability of reverse logistics in market-motivated contexts are examined in China. Interactions between the major barriers, that hinder or prevent the application of reverse logistics in China are analyzed. Management’s key task is to diagnose barriers to the application of reverse logistics that could be crucial to the organization’s future survival. Simultaneity, a value delivery system exists to create value for customers and environments by supplying needed products and services. Value delivery systems are at the heart of every firm and, more than anything else, determine that, whether the firm survives in the marketplace or disappears into bankruptcy or takeover. The processes and model of market-motivated reverse logistics value delivery system are discussed, and the processes content and model are presented. Simultaneity, based on the advantage of the Third Party Reverse Logistics Providers (3PRLs) and Outsourced Service Providers, an integrated evaluation model is built to select 3PRLs by using the integrated decision-making methods. Reflecting the comprehensive information requirement, the Analytic Hierarchy Process and entropy approaches are applied to calculate the objective weights. A new kind of relative similarity degree is established by combining the Euclidean distance with the grey correlation degree. An example demonstrates the model’s efficiency.

The purpose of this paper is to overcome the shortcomings of existing multivariate grey incidence models that cannot analyze the similarity of behavior matrixes.

First, the feasibility of using gradient to measure the similarity of continuous functions is analyzed theoretically and intuitively. Then, a grey incidence degree is constructed for multivariable continuous functions. The model employs the gradient to measure the local similarity, as incidence coefficient function, of two functions, and combines local similarity into global similarity, as grey incidence degree by double integral. Third, the gradient incidence degree model for behavior matrix is proposed by discretizing the continuous models. Furthermore, the properties and satisfaction of grey incidence atom of the proposed model are research, respectively. Finally, a financial case is studied to examine the validity of the model.

The proposed model satisfies properties of invariance under mean value transformation, multiple transformation and linear transformation, which proves it is a model constructed from similarity perspective. Meanwhile, the case study shows that proposed model performs effectively.

The method proposed in the paper could be used in financial multivariable time series clustering, personalized recommendation in e-commerce, etc., when the behavior matrixes need to be analyzed from trend similarity perspective.

It will promote the accuracy of multivariate grey incidence model.

To determine how the correlational structure of emotion differs for individuals age 60 and above, compared to those under age 60, and to discuss the profound implications these differences may have for the experience and management of emotion.

Structural equation modeling and shortest path analysis of emotion items from the General Social Survey (GSS)’s (1996) emotions module.

Some positive and negative emotion pairs are more distant for individuals over age 60, while others are in fact closer. This variability leads to differences in available shortest paths between emotions, especially when emotional transitions require segueing through intermediary feelings. The segueing emotions most readily available to those over 60 are limited to the poles of affective meaning, whereas those used by ones under age 60 are more variable. The majority of negative emotions are more tightly correlated, whereas the majority of positive emotions are less so, among those over age 60.

Although the measures are limited to 18 of the 19 emotions recorded by the GSS, and are based on self-report data regarding feelings felt over a period of seven days, these results suggest that attempts at intrapersonal and interpersonal emotion management may differ depending up the age of the actor/object.

Addresses the need for more nuanced analyses of emotional experience that goes moves beyond simple frequencies. Also suggests potential bridges between sociological and psychological approaches to the study of emotion.

Research on price extremes and overreactions as potential violations of market efficiency has a long tradition in investment literature. Arguably, very few studies to date have addressed this issue in cryptocurrencies trading. The purpose of this paper is to consider the extreme value modelling for forecasting COVID-19 effects on cryptocoin markets. Additionally, this paper examines the importance of technical trading indicators in predicting the extreme price behaviour of cryptocurrencies.

This paper decomposes the daily-time series returns of four cryptocurrency returns into potential maximum gains (PMGs) and potential maximum losses (PMLs) at first and then tests their lead–lag relations under an econometric framework. This paper also investigates the non-random properties of cryptocoins by computing the incremental explanatory power of PML–PMG modelling with technical trading indicators controlled. Besides, this paper executes an event study to identify significant changes caused by COVID-19-related events, which is capable of analysing the cryptocoin market overreactions.

The findings of this paper produce the evidence of both market overreactions and trend persistence in the potential gains and losses from coins trading. Extreme price behaviour explains volatility and price trends in crypto markets before and after the outbreak of a pandemic that substantiate the non-random walk behaviour of crypto returns. The presence of technical trading indicators as control variables in the extreme value regressions significantly improves the predictive power of models. COVID-19 crisis affects the market efficiency of cryptocurrencies that improves the usefulness of extreme value predictions with technical analysis.

This paper strongly supports for the robustness of technical trading strategies in cryptocurrency markets. However, the “beast is moving quick” and uncertainty as to the new normalcy about the post-COVID-19 world puts constraint on making best predictions.

The paper contributes substantially to our understanding of the pricing efficiency of cryptocurrency markets after the COVID-19 outbreak. The findings of continuing return predictability and price volatility during COVID-19 show that profitable investment opportunities for cryptocoin traders are prevailing in pandemic times.

The paper is unique to understand extreme return reversals behaviour of cryptocurrency markets regarding events related to COVID-19 breakout.

The purpose of this paper is to assess whether the temporal evolution of the normalized web distance (NWD) between significant terms concerning, e.g., a case of online activism can be used as a meta-data technique to measure evolution over time of, e.g., progress or decline of social empowerment.

The NWD between two terms has been identified as a quantitative measure for semantic proximity, ascertaining a defining relation between them. A trend analysis is made by performing on the internet a time window restrained series measurement of NWD of all combinations of key-terms and classifier-terms. Case defining key-terms, positive and negative discourse polarizing classifier-terms, and neutral classifier-terms for negative control need to be determined by discourse analysis of information on a targeted case. An example of NWD evolution from 1994 until 2013 is presented to measure the empowerment effects of the Wirikuta online movement on the Huichol people in Mexico.

The application of the NWD temporal evolution method to the Wirikuta case shows a slight but significant semantic change of the key-terms with respect to some of the positive and negative classifier-terms. The neutral classifier correctly shows no significant distance variation, as required for valid application of the method. The method provides indications for a complex image of empowerment of the Huichol identity.

The accuracy of the method is limited due to short-term and between-user variability of the search tool’s page counts. More reliable access to a web-index will be required for more accurate NWD-based trend analysis.

The monitoring of temporal NWD evolution provides a potential tool for more comprehensive trend description compared to classical frequency based methods.

Trend analysis is key to internet research, to which the temporal NWD method provides an innovative contribution.

This paper aims to describe three exploratory field studies investigating which characteristics add to later time to market and/or low product functionality of newly developed products. The studies are conducted at the level of developments tasks, or work packages. The first and second studies investigate to what extent the unpredictability of the project's outcome is the result of the unpredictability of the completion time of individual work packages, and of the instability of the total network of work packages.

Statistical analysis of the empirical data about the progress of three design projects carried out in the development department of a high‐tech capital equipment manufacturer was used. The third study examines the reasons that members of the product development teams in this firm give for the unpredictability of time and quality of the project's outcome.

The results result indicate the existence of three very different sources of unpredictability: the usual uncertainty about the duration of a design task, the discovery of unexpected new problems in a design task, and the reprioritization of a work package by project leaders due to new problems in other work packages.

Together the three studies provide a detailed account of the operational characteristics of time‐paced product development projects in a particular firm and suggest ways to effectively manage such a project.

The purpose of this paper is to summarize the advances in grey system theory research and various application achievements in science and engineering. At the same time, it commemorates the 40th anniversary of the birth of grey system theory and the 10th anniversary of Grey Systems–Theory and Application.

Firstly, the innovations of theoretical research in grey system theory were summarized and some of the widely recognized new results are briefly described. By searching and combing the research results of grey system theory in China national knowledge infrastructure (CNKI) database and Web of Science by Institute for Scientific Information (ISI), this paper shows the rapid development trend of grey system theory in the past 40 years, and the successful applications of grey system theory in the fields of social sciences, natural sciences and engineering technologies.

More than 227 thousands literature were found by input 10 phrases such as grey system, grey number and sequence operator etc. in CNKI database. After entering the new century, the number of grey system papers included in CNKI database is increasing rapidly. Since 2008, more than 10 thousands papers have been included per year and more than 15 thousands papers have been included per year since 2014. Grey system method and model are widely used in physics, chemistry, biology and other fields of natural science, as well as transportation, electric power, machinery and other fields of engineering technology, and a large number of valuable results have been achieved.

It can be seen that the grey system theory plays an important role in promoting China’s scientific and technological progress, innovation and development and high-level talent training from tens of thousands of literatures marked with important national science and technology projects and a large number of grey system literatures published by China’s double first-class universities and double first-class discipline construction universities.

Both innovations of theoretical research and practical application play important role in the growth of new theory. The innovations of theoretical research provide methods and tools for practical application, which is conducive to improve application efficiency and broaden application fields. A large number of practical applications needs have become the source of theoretical innovation and the solid background for the birth of theoretical innovation achievements.

For solving the dilemma between the cognitive cost and value of the uncertainty and negative feedback loop formed by them in the knowledge transfer process, the purpose of this paper is to attempt to construct a new web‐based knowledge flow model to find an alternative diffusion path which had become the inevitable choice in achieving Industry‐University collaboration.

In view of this, based on the statistical data compilation of the Universities of Science and Technology of China from 2002 to 2008, the visual diagrams, econometric model and grey incidence model were used to analyze the situation of the technology innovation and technology transformation on the combined learning with research in Jiangsu. Then, the conceptual model and the organization management pattern for network‐based Industry‐University‐Research collaboration was put forward.

The results are convincing: the new web‐based knowledge flow model in this paper could overcome barriers in the knowledge flow process of the Industry‐University collaboration with the innovation and the integration of the cross‐border and also promote the exchange of knowledge especially for tacit knowledge and value‐added mobile and can also improve the regional technological innovation ability and technology transformation capabilities.

The paper succeeds in constructing the web‐based knowledge flow model to develop the Industry‐University collaboration and help improve regional innovation and technology transformation.