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Reports the dynamic modelling of garments on synthetic humans. Develops the model based on a physical analogue to a deep shell system for describing and predicting the real 3‐D shape of clothes. Determines the garment motion by fabric deformation energy, gravity and external constraints of the garment, such as collision forces, using the deformable node bar concept. Justifies the model by agreement between real fabric prediction of static and dynamic drapes using our newly developed drape metre. Demonstrates the garment simulation using garments from two different fabrics in a virtual fashion show. Also describes the work on modelling and animating a synthetic female. The advantages of this model are that engineering parameters can be used as model parameters directly and that the model is configured based on the surface co‐ordinate system, which are important for the next generation of fashion CAD systems incorporating virtual fashion shows. This consideration is fundamental in the context of global retailing and becomes an integral part of intelligent textile and garment manufacture. Proposes the consequences of this work in cinema, TV, advertising and in graphics and animation are also important, but does not examine these.

The China–Europe Railway Express (CR Express) in Chongqing has operated regularly and undergone large-scale development. Its impact on Chongqing’s economic growth has become increasingly evident, necessitating further research in this field.

This study employs the opening of CR Express as a quasi-natural experiment, designating Chongqing, which inaugurated the CR Express in 2011, as the treatment group. 13 provinces and cities that had not yet opened the CR Express until 2017 were selected as the control group. Utilizing panel data from 14 provinces across China spanning from 2006 to 2017, the synthetic control method (SCM) is employed to synthetically construct Chongqing. To quantify the difference in economic development levels between Chongqing with the operation of the CR express and Chongqing without its operation. Key metrics such as gross domestic product (GDP), per capita GDP, total retail sales of consumer goods, import and export value and the proportions of the secondary and tertiary industries are employed to measure urban economic development capabilities. Chongqing is designated as the experimental group, and a double-difference model is constructed to regress the operation of the CR Express against economic development capabilities. Robustness tests are conducted to validate the analytical results.

The results indicate that, compared to provinces without the operation of the CR Express, the initiation of the CR Express in Chongqing significantly enhances the economic development level of the city. The opening of the CR Express exhibits a pronounced positive impact on Chongqing’s economic development, and these findings remain robust and effective even after parallel trend tests and placebo tests.

The study represents an expansion of the theoretical framework. In contrast to previous studies that relied on a single indicator such as GDP, this study selects six indicators from the dimensions of economy, trade and industry to measure regional economic development capabilities. Furthermore, employing the grey relational analysis method, the study screens these indicators, thereby providing a theoretical basis for the selection of indicators for measuring regional economic development capabilities.

The rise in malaria deaths discloses a decline of global malaria eradication that shows that control measures and fund distribution have missed its right of way. Therefore, the purpose of this paper is to study and evaluate the impact and control of malaria on the independent states of the Sub-Saharan African (SSA) region over the time period of 2010–2017 using Deng’s Grey incidence analysis, absolute degree GIA and second synthetic degree GIA model.

The purposive data sampling is a secondary data from World Developmental Indicators indicating the incidence of new malaria cases (per 1,000 population at risk) for 45 independent states in SSA. GIA models were applied on array sequences into a single relational grade for ranking to be obtained and analyzed to evaluate trend over a predicted period.

Grey relational analysis classifies West Africa as the highly infectious region of malaria incidence having Burkina Faso, Sierra Leone, Ghana, Benin, Liberia and Gambia suffering severely. Also, results indicate Southern Africa to be the least of all affected in the African belt that includes Eswatini, Namibia, Botswana, South Africa and Mozambique. But, predictions revealed that the infection rate is expected to fall in West Africa, whereas the least vulnerable countries will experience a rise in malaria incidence through to the next ten years. Therefore, this study draws the attention of all stakeholders and interest groups to adopt effective policies to fight malaria.

The study is a pioneer to unravel the most vulnerable countries in the SSA region as far as the incidence of new malaria cases is a concern through the use of second synthetic GIA model. The outcome of the study is substantial to direct research funds to control and eliminate malaria.

True 3‐D garment design (CAD) systems are fundamental for the next generation of intelligent textile and garment manufacture and retailing. Reports a new approach for modelling fabric. The fabric model is developed based on a physical analogue to a deep shell system for describing and predicting the real 3‐D shape of clothes. The fabric motion is determined by deformation energy, gravity and external constraints, such as collision forces, using the deformable node bar concept. The advantages of this model are that engineering parameters can be used as model parameters directly and that the model is configured based on the surface co‐ordinate system, which is believed to be important as the basis of a powerful fashion CAD system. The model successfully simulated fabric drape and has been implemented on a synthetic female model.

This paper presents a new technique for collision detection between fabric and fabric or fabric and body, applied on our physical‐based fabric drape model. The technique can produce a realistic 3D virtual fashion show based on fabric mechanical properties and has the ability to handle the collision of clothing with an animated synthetic human. The collision technique appeared efficient and reliable when dealing with complex cases of fabric deformation. A full implementation of the drape model, collision detection with an animated human model is also described and discussed.

To improve power system peak dispatching ability, connecting energy-storage device such as electric vehicle (EV) and regenerative electric heater (REH) to power grid is a good choice.

This paper establishes a multi-energy combined peak dispatching system MCPDS which includes EV, REH and wind power. The matter-element extension model based on improved variable weight theory is applied to evaluate MCPDS synthetic benefit.

The research shows that the MCPDS established in this paper performs excellently in security benefit, economic benefit, social benefit and environmental benefit.

With the assistance of energy storage devices such as EV and REH, the electrical system peak dispatching ability and power system operation efficiency has improved. More devices with energy-storage ability should be introduced into electrical power system to improve its synthetic benefit.

The purpose of this paper is to explore knowledge-intensive business services (KIBS), to understand how they implement their service development (SD) processes and how these processes are related to their knowledge bases (KB) as not enough studies have focussed on the understanding of KIBS heterogeneity, by analysing the nature and essence of these firms’ activities.

The work adopts the case study approach involving 12 KIBS firms with different KB according to Bjorn Asheim and colleagues’ “synthetic, analytical, symbolic model”, which identifies synthetic, analytical and symbolic primary KB.

The research results showed how the SD processes are systemised in KIBS companies depending on the KB. The proposed empirical method for defining KB confirmed the assumed existence of a new type or subtype of KB for legal companies “Compliance/Interpretive”.

Further research, based on a larger number of companies, is needed to confirm or complement the results of this research, as well as to find more methods to define and evaluate KB on an empirical basis.

The correct classification of the applied KB can help a company to create effective processes for developing innovative services, while understanding of knowledge dynamic in general – to organise a working process that corresponds to employees’ needs and is more adaptable to the changes in society.

The study proposed a new empirical method for defining and evaluating KB in KIBS companies based on their SD processes. This study makes a significant contribution to research by identifying knowledge-integration practices needed to enhance innovation performance.

In this chapter, the author argues that Austrians are perhaps uniquely placed to be effective practitioners of causal inference techniques on observational data. This is because, while the methods are easy to implement, their validity and value lies in a detailed, “analytical/historical” narrative to accompany the findings. This is true for several reasons. (1) all the models have identifying assumptions (e.g., no spillovers and parallel trends) that are best addressed by an exposition of the institutional/economic/historical milieu in place before and after the treatment under study; (2) determination of external validity also requires detailed institutional and historical knowledge; and (3) researchers often want to know the mechanisms producing the reduced form result that comes out of most causal inference studies. Here again, institutional and historical learning is crucial. My conclusion is that Austrians should add the tools of causal inference with observational data to their arsenal of analysis. This would be good both for their publication prospects and for the profession at large.

This paper aims to propose an algorithm, location-aware opportunistic content forwarding (LOC), to improve message directivity using direction vectors in opportunistic networks. The LOC is based on the assumption that if approximate location of the destination node is known, then overall message delivery and cost can be improved. Efficient message delivery with low communication cost is a major challenge in current opportunistic networks. In these networks, nodes do not have prior knowledge of their recipients, and message forwarding can be achieved by selecting suitable forwarder based on some forwarding criteria, as compared to its ancestor mobile ad hoc networks.

In this paper, the authors tested LOC in two sets of mobility models, synthetic movement model and real mobility data sets. In the first set, working day movement is used as synthetic movement model, where proposed algorithm is compared against Lobby Influence (LI) and Epidemic algorithms. In the second set of experiments, the new algorithm is tested in three mobility data sets, namely, Cambridge, Reality and Sassy, and results compared against LI algorithm. The reason of using various movement models is to establish strengths and weaknesses of the proposed algorithm in different scenarios.

The experimental results show that the new algorithm performed extremely well in different scenarios, not only in terms of overall message delivery but also successfully managed to reduce the communication cost.

The new contribution increases the overall energy and storage efficiency of nodes by targeting relevant forwarding nodes in the network.