The rise of urbanization, overpopulation, and resource depletion in recent years has triggered interest in developing more efficient solutions that could offer sustainable development and improve the quality of life in cities. The increasingly wider and more advanced availability of computational power throughout the anthropic space—which saw the emergence of the so-called “ubiquitous computing” paradigm—has opened new possibilities for the design of smart cities. In particular, the emergence of Extended Reality technologies (XR), such as Virtual Reality and Augmented Reality, has provided a new interface to bridge the gap between the physical and digital realms, enabling immersive experiences and interactions within Smart City environments. This paper, based on three case studies at different scales of smart environments, explores the current and prospected relevance of XR to both design and experience spaces enriched and characterized by layers of digital information and sensorial interactions.

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This paper proposes an efficient direction of departure (DOD) and direction of arrival (DOA) estimation method for multi-input multi-output (MIMO) systems. For uncorrelated scenarios, the redundancy of the covariance matrix is first exploited by establishing its concise representation through redundancy reduction, which transforms the original large-size covariance matrix into a smaller-size matrix without loss of useful angle information. Then, the resulting transformed matrix, which retains a salient structure, permits efficient two-dimensional (2D) angle estimators working on a reduced-size problem for DOD and DOA estimation. Compared with conventional subspace-based methods, the proposed method incorporating an appropriate 2D angle estimator is more computationally efficient and can achieve higher estimation accuracy for small numbers of snapshots and low signal-to-noise ratios, which are verified by simulation results.

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This paper develops an enhanced low-rank structured covariance reconstruction (LRSCR) method based on the decoupled atomic norm minimization (D-ANM), for super-resolution two-dimensional (2D) harmonic retrieval with multiple measurement vectors. This LRSCR-D-ANM approach exploits a potential structure hidden in the covariance by transferring the basic LRSCR to an efficient D-ANM formulation, which permits a sparse representation over a matrix-form atom set with decoupled 1D frequency components. The new LRSCR-D-ANM method builds upon the existence of a generalized Vandermonde decomposition of its solution, which otherwise cannot be guaranteed by the basic LRSCR unless a very conservative condition holds. Further, a low-complexity solution of the LRSCR-D-ANM is provided for fast implementation with negligible performance loss. Simulation results verify the advantages of the proposed LRSCR-D-ANM over the basic LRSCR, in terms of the wider applicability and the lower complexity.@en

The usability now serves as a fundamental quality of a computational device, e.g. smartphone. Moreover, the smartphone has firmly embedded into our daily life as an indispensable part, so the context and style that user may interact with them are largely different from a decade ago. Nowadays, testing usability with end user has become a common sense. Thus, how valid a usability evaluation method could assess the ‘extent to which a product can be used by specified users’ (ISO 9241-11) to facilitate software design becomes an interesting question to explore. In this research, three usability evaluation methods are compared. Among these methods, IsoMetrics is a standard questionnaire aiming at offer usability data for summative and formative evaluation; SUMI aims to assess quality of software product from end users perspective; User Model Checklist is a method based on user’s cognition-motor chain in specific tasks. The coverage and amount of usability issues, user’s effort of evaluation and software developer’s feedback on evaluation result are compared under a simulated usability test on SMS function with a smartphone. The result indicate that User Model Checklist could cover 90.4% of the usability issues found by IsoMetrics and SUMI, while 26.3% usability issues found by User Model Checklist could not be covered by IsoMetrics and SUMI. Users put highest effort on accomplish IsoMetrics and lowest effort on User Model Checklist. Moreover, the feedbacks from the developers show that the User Model Checklist requires lower usability knowledge, offers clearer improvement points and supports detailed design better.

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Elliptic Cu-Ag nanoflakes were syntheszied via facile in situ galvanic replacement between prepared Cu particles and Ag ions. Alloy nanoflakes with high purity and uniformity present a size of 700 × 500 nm, with a thinness of 30 nm. Nontoxic and low-cost polyvinyl pyrrolidone was used as a dispersant and structure-directing agent, promoting the formation of the remarkable structure. Synthesized nanoflakes were utilized as a filler for conductive paste in an epoxy resin matrix. Conductive patterns on flexible substrates with a resistivity of 3.75 × 10 ^-5 ηcm could be achieved after curing at 150 °C for 2 h. Compared with traditional silver microflakes, smart alloy nanoflakes provide much improved conductive interconnection, whose advantage could be attributed to their nanoscale thicknesses. It is also noteworthy that the conductive patterns are able to tolerate multiple bendings at different angles, having good conductivity even after 200 repeated bendings. Therefore, alloy nanoflakes could be a promising candidate conductive filler for flexible printing electronics, electronic packaging, and other conductive applications.

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This paper develops efficient channel estimation techniques for millimeter-wave (mmWave) massive multiple-input multiple-output (MIMO) systems under practical hardware limitations, including an arbitrary array geometry and a hybrid hardware structure. Taking on an angle-based approach, this work adopts a generalized array manifold separation approach via Jacobi-Anger approximation, which transforms a non-ideal, non-uniform array manifold into a virtual array domain with a desired uniform geometric structure to facilitate super-resolution angle estimation and channel acquisition. Accordingly, structure-based optimization techniques are developed to effectively estimate both the channel covariance and the instantaneous channel state information (CSI) within a short sensing time. The different time-varying scales of channel path angles versus path gains are capitalized to design a two-step CSI estimation scheme that can quickly sense fading channels. Theoretical results are provided on the fundamental limits of the proposed technique in terms of sample efficiency. For computational efficiency, a fast iterative algorithm is developed via the alternating direction method of multipliers. Other related issues such as spurious-peak cancellation in non-uniform linear arrays and extensions to higher-dimensional cases are also discussed. Simulations testify the effectiveness of the proposed approaches in hybrid mmWave massive MIMO systems with arbitrary arrays.

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Smartphone is nowadays the most prevalent computer system, thus a lot of attention from academia and industries has been put to evaluate its quality of use. However, Smartphone has more complex interaction modes and usage scenarios than PC and laptop. And therefore assessing its quality using a conventional usability evaluation is not sufficient. Meanwhile, the mental load serves as an acknowledged index of effort that operators have put in human-machine interaction, especially under high-demanding context. Mental load contains a set of parameters in multiple dimensions, such as primitive task performance, biological measurement(s) and subjective mental load scale, which assesses the efforts of tasks under a particular environment and operating conditions. Thus, it is suitable for evaluating complex mental work, and may indicate the use of Smartphones. The aim of this paper is to apply a multi-dimensional method to assess the mental load of users, and find out which measurement(s) is the most suitable one to evaluate the efforts for using a smartphone. During this study, the effort on conducting tasks with four difficulty levels were assessed using measurements in three dimensions, which were (1) user performance (task accomplishment and secondary task), (2) subjective rating (NASA-TLX scale) and (3) physiological function (EDA). The values of these measurements were compared across novice, average and skilled users. The results show that: task duration and number of usability error are significantly related with mental load and change with the difficulty level of tasks; in subjective rating, Mental Demand, Effort and Frustration were highly related with mental load.@en