Bifeng Zhu, Yuan Zheng, Manqi Ding, Jie Dai, Gebing Liu and Liting Miao
The application of massive open online courses (MOOCs) helps integrate sustainable development goals (SDGs) into architectural curricula. The essence of MOOC development is…
Abstract
Purpose
The application of massive open online courses (MOOCs) helps integrate sustainable development goals (SDGs) into architectural curricula. The essence of MOOC development is building an education platform that promotes the sharing and continuing of global education resources.
Design/methodology/approach
This study establishes a four-dimensional evaluation model based on the four characteristics of MOOCs. The quadrilateral area evaluation method is used to create an evaluation radar chart to comprehensively evaluate satisfaction and demand in the traditional teaching model of architectural technology. This study discusses whether the curriculum is suitable for the development of MOOCs and how to optimize the sustainable pedagogical mode according to its characteristics to meet future teaching needs and realize the sustainable development of education.
Findings
Satisfaction evaluation found that current education is not open enough from the students' perspective; therefore, MOOCs enhance students' participation and significantly reduce future learning costs. Through demand evaluation, it was found that both teachers and students believed that the lack of direct and effective communication between them and the difficulty in ensuring the learning effect were problems that must be addressed in MOOCs.
Originality/value
This study focused on the sustainability of MOOCs in curriculum development. It emphasizes the combination of MOOCs' teaching modes and the course itself and provides specific guidance and suggestions for improving the course. It uses an evaluation method for objective analysis and visualization.
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Considers the effects on the mass media of China’s transition to a more open economy and the strategies which advertisers might use to overcome the problems it presents. Describes…
Abstract
Considers the effects on the mass media of China’s transition to a more open economy and the strategies which advertisers might use to overcome the problems it presents. Describes the media available (including the unofficial “black route”, the official but restricted private sector “white route”, and the state “red route”) and lists the challenges which advertisers face in using them. Suggests some strategies and practices which can help to overcome them and some hypotheses on future media use. Calls for further research in this area.
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Rafiu King Raji, Xuhong Miao, Shu Zhang, Yutian Li, Ailan Wan and Charles Frimpong
The use of conductive yarns or wires to design and construct fabric-based strain sensors is a research area that is gaining much attention in recent years. This is based on a…
Abstract
Purpose
The use of conductive yarns or wires to design and construct fabric-based strain sensors is a research area that is gaining much attention in recent years. This is based on a profound theory that conductive yarns will have a variation in resistance if subjected to tension. What is not clear is to which types of conductive yarns are most suited to delivering the right sensitivity. The purpose of this paper is to look at strain sensors knitted with conductive composite and coated yarns which include core spun, blended, coated and commingled yarns. The conductive components are stainless steel and silver coating respectively with polyester as the nonconductive part. Using Stoll CMS 530 flat knitting machine, five samples each were knitted with the mentioned yarn categories using 1×1 rib structure. Sensitivity tests were carried out on the samples. Piezoresistive response of the samples reveals that yarns with heterogeneous external structures showed both an increase and a decrease in resistance, whereas those with homogenous structures responded linearly to stress. Stainless steel based yarns also had higher piezoresistive range compared to the silver-coated ones. However, comparing all the knitted samples, silver-coated yarn (SCY) proved to be more suitable for strain sensor as its response to tension was unidirectional with an appreciable range of change in resistance.
Design/methodology/approach
Conductive composite yarns, namely, core spun yarn (CSY1), core spun yarn (CSY2), silver-coated blended yarn (SCBY), staple fiber blended yarn (SFBY) and commingled yarn (CMY) were sourced based on specifications and used to knit strain sensor samples. Electro-mechanical properties were investigated by stretching on a fabric tensile machine to ascertain their suitability for a textile strain sensor.
Findings
In order to generate usable signal for a strain sensor for a conductive yarn, it must have persistent and consistent conductive links, both externally and internally. In the case of composite yarns such as SFBY, SCBY and CMY where there were no consistent alignment and inter-yarn contact, resistance change fluctuated. Among all six different types of yarns used, SCY presented the most suitable result as its response to tension was unidirectional with an appreciable range of change in resistance.
Originality/value
This is an original research carried out by the authors who studied the electro-mechanical properties of some composite conductive yarns that have not been studied before in textile strain sensor research. Detailed research methods, results and interpretation of the results have thus been presented.
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Fei Sun, Haisang Liu, Yuqin Din, Honglian Cong and Zhijia Dong
The purpose of this research is to propose a flexible sensor with a weft-knitted float stitch structure and to explore knitting techniques that allow conductive yarns to be…
Abstract
Purpose
The purpose of this research is to propose a flexible sensor with a weft-knitted float stitch structure and to explore knitting techniques that allow conductive yarns to be skin-tight and less exposed, reducing production processes and increasing productivity. Study its electrical conductivity in different yarn materials, knit processes and deformation ranges. The analysis is compared to provide some basis for the design of the electrodes.
Design/methodology/approach
The method includes five operations: (1) Analysis of the morphological appearance, tensile variation, fiber material properties and electrical conductivity of high-elastic and filament silver-plated conductive yarns. (2) Based on the knitting process of the floating yarn structure, three-dimensional modeling of the flexible sensor was carried out to explore the influence of knitting process changes on appearance characteristics. (3) The fabric samples are knitted by different silver-plated conductive yarns with different structures. Processing of experimental samples to finished size by advance shrinkage. (4) Measure the resistance of the experimental sample after the machine has been lowered and after pre-shrinking. Use the stretching machine to simulate a wearing experiment and measure the change in resistance of the sample in the 0–15% stretching range. (5) Analyze the influence factors on the conductive performance of the flexible sensor to determine whether it is suitable for textile flexible sensors.
Findings
For the float knitted flexible sensors, the floating wire projection is influenced by the elasticity of the fabric and the length of the floating wire. Compared to the plain knitted flexible sensors, it has less resistance variation and better electrical properties, making it suitable for making electrodes for textile structures. In addition, the knitting method is integrated with the intelligent monitoring clothing, which saves the process for the integration of the flexible sensor, realizes positioning and fixed-point knitting.
Practical implications
The sensor technology of the designed weft-knitted float structure is varied and can be freely combined and designed in a wide range. Within the good electrical conductivity, the flexible sensor can realize integrated knitting, positioning monitoring, integrating into the appearance of clothing. It can also focus on the wearing experience of wearable products so that the appearance of the monitoring clothing is close to the clothes we wear in our daily life.
Originality/value
In this paper, an integrated positioning knitting flexible sensor based on the weft knitting float structure is studied. The improved knitting process allows the sensing contact surface to be close to the skin and reduces the integration process. The relationship between the exposure of the silver-plated yarn on the clothing surface and the electrical conductivity is analyzed. Within a certain conductive performance, reduces the exposed area of the conductive yarn on the clothing surface and proposes a design reference for the flexible sensor appearance.
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Vandana Srivastava, Sanjeev Kishore and Deepika Dhingra
Over the last decade, customer experience management has gradually emerged as the most important activity for organisations. Organisations have turned towards leveraging the…
Abstract
Over the last decade, customer experience management has gradually emerged as the most important activity for organisations. Organisations have turned towards leveraging the ubiquitous and easy-to-use technology in enhancing and enabling experience for the time-crunched customers of today who are looking for greater convenience and choices. It is therefore not surprising that disruptive technologies such as smartphones, virtual and augmented reality, cloud computing, big data analytics, Internet of things, artificial intelligence and robotics have also found their way into the design of customer experience. This chapter aims to present an overview of the technologies that have transformed the customer experience landscape. This chapter contributes by showcasing two illustrative cases from very diverse domains, a private sector bank and a public sector transportation organisation, to elucidate how India, a rapidly developing economy, is embracing technology to enhance the customer experience.
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Abstract
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Miao Yanzi, Wang Xiaolin, Zhang Yuanhao, Ji Liang, Wang Yizhou and Xu Zhiyang
The purpose of this paper is to improve the precision of gangue detection. In the real production environment, some gangue features are not obvious, and it is difficult to…
Abstract
Purpose
The purpose of this paper is to improve the precision of gangue detection. In the real production environment, some gangue features are not obvious, and it is difficult to distinguish between coal and gangue. The color of the conveyor belt is similar to the gangue, the background noise also brings challenge to gangue detection. To address the above problems, we propose a feature aggregation method based on optical flow (FAOF).
Design/methodology/approach
An FAOF is proposed. First, to enhance the feature representation of the current frame, FAOF applies the timing information of video stream, propagates the feature information of the past few frames to the current frame by optical flow. Second, the coordinate attention (CA) module is adopted to suppress the noise impact brought by the background of convey belt. Third, the Mish activation function is used to replace rectified linear unit to improve the generalization capability of our model.
Findings
The experimental results show that the gangue detection model proposed in this paper improve 4.3 average precision compared to baseline. This model can effectively improve the accuracy of gangue detection in real production environment.
Originality/value
The key contributions are as follows: this study proposes an FAOF; this study adds CA module and Mish to reduce noise from the background of the conveyor belt; and this study also constructs a large gangue data set.
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The purpose of this paper is to improve the D* algorithm which has been used usually in robotics for mobile robot navigation in unknown or dynamic environments.
Abstract
Purpose
The purpose of this paper is to improve the D* algorithm which has been used usually in robotics for mobile robot navigation in unknown or dynamic environments.
Design/methodology/approach
First, the model of 2D workspace with some obstacles is expressed in regularity grids. The optimal path is planned by using the improved D* algorithm by searching in the neighbor grid cells in 16 directions. It makes the robot that the smallest turning angle drops to π/8. The robot moving angle discrete precision is raised and the unnecessary cost of path planning is reduced so the robot motion path is smoother. Then, the improved D* algorithm is simulated in MOBOTSIM software environment and is tested by the WiRobotX80 mobile robot.
Findings
To search in the neighbor grid cells in 16 directions instead of eight directions by using D* algorithms for path planning.
Research limitations/implications
The map should be expressed in regularity grids.
Originality/value
The improved D* algorithm is effective and it can result in a higher quality path than the conventional D* algorithm at the same map environment.
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Valeriia Izhboldina and Igor Lebedev
The successful application of the group of unmanned aerial vehicles (UAVs) in the tasks of monitoring large areas is becoming a promising direction in modern robotics. This paper…
Abstract
Purpose
The successful application of the group of unmanned aerial vehicles (UAVs) in the tasks of monitoring large areas is becoming a promising direction in modern robotics. This paper aims to study the tasks related to the control of the UAV group while performing a common mission.
Design/methodology/approach
This paper discusses the main tasks solved in the process of developing an autonomous UAV group. During the survey, five key tasks of group robotics were investigated, namely, UAV group control, path planning, reconfiguration, task assignment and conflict resolution. Effective methods for solving each problem are presented, and an analysis and comparison of these methods are carried out. Several specifics of various types of UAVs are also described.
Findings
The analysis of a number of modern and effective methods showed that decentralized methods have clear advantages over centralized ones, since decentralized methods effectively perform the assigned mission regardless of on the amount of resources used. As for the method of planning the group movement of UAVs, it is worth choosing methods that combine the algorithms of global and local planning. This combination eliminates the possibility of collisions not only with static and dynamic obstacles, but also with other agents of the group.
Originality/value
The results of scientific research progress in the tasks of UAV group control have been summed up.
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Huaxiang Song, Hanjun Xia, Wenhui Wang, Yang Zhou, Wanbo Liu, Qun Liu and Jinling Liu
Vision transformers (ViT) detectors excel in processing natural images. However, when processing remote sensing images (RSIs), ViT methods generally exhibit inferior accuracy…
Abstract
Purpose
Vision transformers (ViT) detectors excel in processing natural images. However, when processing remote sensing images (RSIs), ViT methods generally exhibit inferior accuracy compared to approaches based on convolutional neural networks (CNNs). Recently, researchers have proposed various structural optimization strategies to enhance the performance of ViT detectors, but the progress has been insignificant. We contend that the frequent scarcity of RSI samples is the primary cause of this problem, and model modifications alone cannot solve it.
Design/methodology/approach
To address this, we introduce a faster RCNN-based approach, termed QAGA-Net, which significantly enhances the performance of ViT detectors in RSI recognition. Initially, we propose a novel quantitative augmentation learning (QAL) strategy to address the sparse data distribution in RSIs. This strategy is integrated as the QAL module, a plug-and-play component active exclusively during the model’s training phase. Subsequently, we enhanced the feature pyramid network (FPN) by introducing two efficient modules: a global attention (GA) module to model long-range feature dependencies and enhance multi-scale information fusion, and an efficient pooling (EP) module to optimize the model’s capability to understand both high and low frequency information. Importantly, QAGA-Net has a compact model size and achieves a balance between computational efficiency and accuracy.
Findings
We verified the performance of QAGA-Net by using two different efficient ViT models as the detector’s backbone. Extensive experiments on the NWPU-10 and DIOR20 datasets demonstrate that QAGA-Net achieves superior accuracy compared to 23 other ViT or CNN methods in the literature. Specifically, QAGA-Net shows an increase in mAP by 2.1% or 2.6% on the challenging DIOR20 dataset when compared to the top-ranked CNN or ViT detectors, respectively.
Originality/value
This paper highlights the impact of sparse data distribution on ViT detection performance. To address this, we introduce a fundamentally data-driven approach: the QAL module. Additionally, we introduced two efficient modules to enhance the performance of FPN. More importantly, our strategy has the potential to collaborate with other ViT detectors, as the proposed method does not require any structural modifications to the ViT backbone.