Imitative Collaboration: A mirror-neuron inspired mixed reality collaboration method with remote hands and local replicas

Mixed reality can overlay and display 3D digital content in the real world, convey abstract concepts to users, and promote the understanding of complex tasks. However, the abstract graphics overlaid on the physical space may cause a certain cognitive load for local users and reduce the efficiency of collaboration. To improve the efficiency of remote collaboration, we conducted an elicitation study on assembly tasks, explored the user needs for collaboration, and defined the design goals of our remote collaboration method. Inspired by the mirror-neuron mechanism, we present an imitative collaboration method that allows local users to imitate the interaction behavior of remote users to complete tasks. We also propose a series of interaction methods for remote users to select, copy, and interact with the local point clouds to facilitate the expression of collaboration intentions. Finally, the results of a user study evaluating our imitative collaboration method on assembly tasks are reported, confirming that our method improves collaboration efficiency while reducing the cognitive load of local users.     

Theoretical investigation of intrinsic point defects and the oxygen migration behavior in rare earth hafnates

In this work, the composition-dependent point defect types and formation energies of RE₂Hf₂O₇ (RE = La, Ce, Pr, Nd, Pm, Sm, Eu and Gd) as well as the oxygen diffusion behavior are systematically investigated by first-principles calculations. The possible defect reactions and dominant defect complexes under stoichiometric and non-stoichiometric conditions are revealed. It is found that O Frenkel pairs are the predominant defect in stoichiometric pyrochlore hafnates. Hf-RE cation anti-site defects, accompanied by RE vacancies and/or oxygen interstitials, are stable in the non-stoichiometric case of HfO₂ excess. On the other hand, RE-Hf anti-site defects together with oxygen vacancies and/or RE interstitials are preferable in the case of RE₂O₃ excess. The energy barriers for the migration along the V_O48f - V_O48f pathway of pyrochlore hafnates were calculated to be between 0.81 eV and 0.89 eV. Based on these results, a defect engineering strategy is proposed and the pyrochlore hafnates investigated here are predicted to exhibit potential oxygen ionic conductivity.     

Why do people purchase virtual goods? A uses and gratification (U&G) theory perspective

Few literature studies have investigated the relationships between different uses and gratifications (U&Gs) of mobile instant messaging (MIM) apps, continuation, and purchase intentions. To address this gap, the researchers aimed to examine the influence of the content, social, process, and technology U&Gs of MIM on continuation intentions toward MIMs, and purchase intentions toward virtual goods available on MIMs. A comprehensive research model was developed based on the U&G theory, which was tested using cross-sectional data from 309 Japanese MIM users. The study considered six different U&Gs of MIM as independent variables and purchase intentions towards stickers and continuation intentions towards MIM as dependent variables. The study results suggest that exposure U&G has a significant positive association with MIM sticker purchase intentions. The entertainment and affection U&G are positively associated with continuation intentions towards MIM use. The study contributes to the literature by investigating U&Gs that motivate MIM users to have both positive purchase intentions toward virtual goods, such as stickers, and continuation intentions toward MIMs. The study has significant theoretical and practical implications for both researchers and practitioners who are interested in virtual goods, the virtual economy, MIM apps, social media, new media, and the service economy.     

Mapping gender and marital roles on customer delight by value perception for mobile technology in India

The Indian telephony industry is a diverse platform for product and service in customer value perception. The present study organizes and synthesizes the varied research streams for developing a customer value delight (CVD) framework for marketing decisions like segmentation and targeting. The conceptual framework is developed by using ten-value predictor variables and customer delight through divergent viewpoints identified from previous studies. The significance of the segregation proposition is tested through discriminant analysis in three different dimension runs i.e. delight, gender, and marital category. The scholarship behind the study provides insight into an imperative issue of segregating customer delight by perceived value predictors in categories. The perceptual mapping and vector magnitude analysis of value predictors were performed to club customers in two categories of Mid-Town (low/moderate delight) and Extremes (high delight). The analysis rigorously supports the discriminating power of perceived price, perceived benefit, and self-congruity. The salience of study unlocks psychographic and demographic perceptual maps of customer delight with its perceived value predictors for strategic and tactful planning in the mobile industry.     

A narrow-frame antenna for WWAN/LTE/WiMAX/WLAN mobile phones

In this paper, we present a novel narrow-frame antenna with a size of 75 × 8 × 5.8 mm³ for 5.7 in. mobile phones. The antenna mainly consists of a monopole with four branches that are coupled to a two-branch grounded strip. Our antenna is able to cover more bands than other narrow-frame antennas by excitation of several resonant modes. The improved range of the antenna covers the following eleven bands: LTE700, GSM850, GSM900, DCS, PCS, UMTS, LTE2300, LTE2500, LTE3400 (3400–3800 MHz)/WiMAX3.5 GHz (3400–3650 MHz), WLAN5.2 GHz (5150–5350 MHz) and WLAN5.8 GHz (5725–5875 MHz). Another advantage of the proposed antenna is that it does not need any lumped element to match the antenna. The working principles of the proposed antenna are thoroughly studied. A prototype of the proposed antenna is fabricated and measured, with the results in good agreement with the simulation results.     

增强现实场景下移动边缘计算资源分配优化方法

针对高速数据传输及计算所带来时延和终端设备能耗问题，提出了一种在上行链路采用等功率分配的传输方案。首先，依据增强现实（AR）业务的协作属性建立了针对AR特性的系统模型；其次，详细分析了系统帧结构，建立以最小化系统消耗总能量为优化目标的约束条件；最后，在保障延迟和功耗满足约束的条件下，建立了基于凸优化的移动边缘计算（MEC）资源优化求解数学模型，从而获得最优的通信和计算资源分配方案。与独立传输相比，该方案在最大延迟时间分别为0.1 s和0.15 s时的总能耗降幅均为14.6%。仿真结果表明，在相同条件下，与基于用户独立传输的优化方案相比，考虑用户间协作传输的等功率MEC优化方案能显著减少系统消耗的总能量。     

CLOI-NET: Class segmentation of industrial facilities’ point cloud datasets

Shape segmentation from point cloud data is a core step of the digital twinning process for industrial facilities. However, it is also a very labor intensive step, which counteracts the perceived value of the resulting model. The state-of-the-art method for automating cylinder detection can detect cylinders with 62% precision and 70% recall, while other shapes must then be segmented manually and shape segmentation is not achieved. This performance is promising, but it is far from drastically eliminating the manual labor cost. We argue that the use of class segmentation deep learning algorithms has the theoretical potential to perform better in terms of per point accuracy and less manual segmentation time needed. However, such algorithms could not be used so far due to the lack of a pre-trained dataset of laser scanned industrial shapes as well as the lack of appropriate geometric features in order to learn these shapes. In this paper, we tackle both problems in three steps. First, we parse the industrial point cloud through a novel class segmentation solution (CLOI-NET) that consists of an optimized PointNET++ based deep learning network and post-processing algorithms that enforce stronger contextual relationships per point. We then allow the user to choose the optimal manual annotation of a test facility by means of active learning to further improve the results. We achieve the first step by clustering points in meaningful spatial 3D windows based on their location. Then, we apply a class segmentation deep network, and output a probability distribution of all label categories per point and improve the predicted labels by enforcing post-processing rules. We finally optimize the results by finding the optimal amount of data to be used for training experiments. We validate our method on the largest richly annotated dataset of the most important to model industrial shapes (CLOI) and yield 82% average accuracy per point, 95.6% average AUC among all classes and estimated 70% labor hour savings in class segmentation. This proves that it is the first to automatically segment industrial point cloud shapes with no prior knowledge at commercially viable performance and is the foundation for efficient industrial shape modeling in cluttered point clouds.     

An architecture for digital hate content reduction with mobile edge computing

Mobile devices with social media applications are the prevalent user equipment to generate and consume digital hate content. The objective of this paper is to propose a mobile edge computing architecture for regulating and reducing hate content at the user's level. In this regard, the profiling of hate content is obtained from the results of multiple studies by quantitative and qualitative analyses. Profiling resulted in different categories of hate content caused by gender, religion, race, and disability. Based on this information, an architectural framework is developed to regulate and reduce hate content at the user's level in the mobile computing environment. The proposed architecture will be a novel idea to reduce hate content generation and its impact.     

Distributed privacy protection strategy for MEC enhanced wireless body area networks

With the rapid development and widespread application of Wireless Body Area Networks (WBANs), the traditional centralized system architecture cannot handle the massive data generated by the edge devices. Meanwhile, in order to ensure the security of physiological privacy data and the identity privacy of patients, this paper presents a privacy protection strategy for Mobile Edge Computing(MEC) enhanced WBANs, which leverages the blockchain-based decentralized MEC paradigm to support efficient transmission of privacy information with low latency, high reliability within a high-demand data security scenario. On this basis, the Merkle tree optimization model is designed to authenticate nodes and to verify the source of physiological data. Furthermore, a hybrid signature algorithm is devised to guarantee the node anonymity with unforgeability, data integrity and reduced delay. The security performance analysis and simulation results show that our proposed strategy not only reduces the delay, but also secures the privacy and transmission of sensitive WBANs data.     

Potential pitfalls of smart city development: A study on parking mobile applications (apps) in Hong Kong

Smart cities are built upon information and communication technologies (ICTs) to enable a broad range of advanced services. Through a comprehensive literature review, this study identified four pitfalls brought by the pervasive application of ICT, including information insecurity, privacy leakage, information islands, and digital divide. Therefore, a questionnaire survey together with 27 interviews was conducted in Hong Kong to investigate how the public perceived these pitfalls within the context of mobile apps providing real-time parking information which form a major part of smart mobility. System insecurity and privacy leakage were found to arouse worries among the app-users while their awareness of protecting personal data was found to have room for improvement. Islands of real-time parking information occur as a result of the lack of collaboration among private carpark operators. Digital divide existed widely among the disadvantaged groups and the problem cannot be solved by mere provision of ICT facilities. Overall, technologies alone cannot make a city smart or smarter. It is the suitable way in which ICTs are used to serve all citizens that matters.