Successive Refinement Research Articles

Integrating Intelligent Reflecting Surface Into Base Station: Architecture, Channel Model, and Passive Reflection Design

Intelligent reflecting surface (IRS) has emerged as a cost-efficient technique to improve the wireless network’s capacity and performance. Existing works on IRS have mainly considered IRS being deployed in the environment to dynamically control the wireless channels between the base station (BS) and its served users in favor of their communications. In contrast, we propose in this paper a new integrated IRS-BS architecture by deploying IRSs inside the BS’s antenna radome to directly reconfigure the signal radiation to/from the BS’s antennas. In other words, the IRSs can be considered as auxiliary passive arrays with real-time reconfigurability equipped at the BS to enhance its communication performance cost-effectively. Since the distance between the integrated IRSs and BS’s antenna array is practically small (in the order of several to tens of wavelengths), the path loss among them is significantly reduced as compared to conventional IRS deployed much farther away from the BS, while the real-time control of the IRS’s reflection by the BS becomes easier to implement. However, the resultant near-field channel model also becomes drastically different from its far-field counterpart for conventional far-away IRSs in the literature. Thus, we propose an element-wise channel model for IRS to characterize the channel vector between each single-antenna user and the antenna array of the BS, which includes the direct (without any IRS’s reflection) as well as the single and double IRS-reflection channel components. Based on this channel model, we formulate a problem to optimize the reflection coefficients of all IRS reflecting elements for maximizing the uplink sum-rate of the users. By considering two typical cases with/without perfect channel state information (CSI) at the BS, the formulated problem is solved efficiently by adopting the successive refinement method and iterative random phase algorithm (IRPA), respectively. Numerical results validate the substantial capacity gain of the integrated IRS-BS architecture over the conventional multi-antenna BS without integrated IRS. Moreover, the proposed algorithms significantly outperform other benchmark schemes in terms of sum-rate, and the IRPA without CSI can approach the performance upper bound with perfect CSI as the training overhead increases.

Cryptomelane nanocrystals: Pseudosymmetry causes anisotropic peak broadening in Rietveld refinement

Cryptomelane (□2-xKx)[Mn8O16] is an octahedral molecular sieve with the hollandite framework, a strongly correlated electron system with tunnel structure. Rietveld refinement using powder X-ray diffraction patterns of a nanocrystalline sample was undertaken to assess both structural and morphological details which might be tuned for specific applications. The distribution of peak widths was highly anisotropic but successful refinement of the tetragonal structure could be achieved assuming both grain shape and microstrain anisotropy. The microstrain hypothesis appeared flawed from high uncertainties and correlations and was in conflict with the negative slope of a Williamson-Hall plot. As an alternative, lattice desymmetrization from tetragonal to monoclinic was considered. Comparison of calculated and observed hkl dependence of line broadening confirmed that the pseudosymmetry hypothesis was more appropriate, improving results for both structure and particle shape. This is the first time that lattice desymmetrization was used to explain anisotropic diffraction line broadening, a major issue in nanomaterials where peaks are intrinsically broad and the new model helps to abate correlations which afflict Rietveld refinement in these systems.

Achievable Refined Asymptotics for Successive Refinement Using Gaussian Codebooks

We study the mismatched successive refinement problem where one uses Gaussian codebooks to compress an arbitrary memoryless source with successive minimum Euclidean distance encoding under the quadratic distortion measure. Specifically, we derive achievable refined asymptotics under both the joint excess-distortion probability (JEP) and the separate excess-distortion probabilities (SEP) criteria. For both second-order and moderate deviations asymptotics, we consider two types of codebooks: the spherical codebook where each codeword is drawn independently and uniformly from the surface of a sphere and the i.i.d. Gaussian codebook where each component of each codeword is drawn independently from a Gaussian distribution. We establish the achievable second-order rate-region under JEP and we show that under SEP any memoryless source satisfying mild moment conditions is strongly successively refinable. When specialized to a Gaussian memoryless source (GMS), our results provide an alternative achievability proof with specific code design. We show that under JEP and SEP, the same moderate deviations constant is achievable. For large deviations asymptotics, we only consider the i.i.d. Gaussian codebook since the i.i.d. Gaussian codebook has better performance than the spherical codebook in this regime for the one layer mismatched rate-distortion problem (Zhou, Tan, Motani, TIT, 2019). We derive achievable exponents of both JEP and SEP and specialize our results to a GMS, which appears to be a novel result of independent interest.

RIS-Aided Cell-Free Massive MIMO System: Joint Design of Transmit Beamforming and Phase Shifts

This article studies a reconfigurable intelligent surface (RIS)-aided cell-free massive multiple-input multiple-output system and formulate the max–min fairness problem that maximizes the minimum achievable rate among all the users by jointly optimizing the transmit beamforming at access points and the phase shifts at RISs. To address such a challenging problem, we first study the special single-user scenario and propose an algorithm that can transform the optimization problem into a semidefinite program (SDP) or an integer linear program for the cases of continuous or discrete phase shifts, respectively. Then, in order to solve the optimization problem for the multiuser scenario with continuous phase shifts, we propose an alternating optimization algorithm, which can alternately transform the problem into a second-order-cone program and an SDP. Finally, for the multiuser scenario with discrete phase shifts, we design a zero-forcing-based successive refinement algorithm, which can find the suboptimal transmit beamforming and phase shifts by means of alternating optimization. Numerical results show that compared with the benchmark schemes of random phase shifts and without using the RIS, the proposed algorithms can significantly increase the minimum achievable rate. It is also demonstrated that, compared with the case of programming continuous phase shifts, using 2-bit discrete phase shifts can practically achieve the same performance.

Implementation of Discovery Learning Model on the Learning Motivation of Sixth Grade Students

The research objective was to determine the effect of the discovery learning model on the student learning motivation. This study employed the classroom action research method. The research population were MI PUI Cigadog students, involving sixth-grade students (30 students) as samples. The sampling technique used was the total sampling. The instruments utilized were observations and questionnaires. The results of the first cycle of learning showed an achievement of 65.04%, as derived from data tabulation, falling into the category of satisfactory. Meanwhile, in the second cycle, through the evaluation and the successful refinement of the implementation of the discovery learning model, a significant improvement was observed. The percentage of learning motivation questionnaire results in the second cycle was 73.47%. The learning motivation outcomes fell into the "good" category, within the range of 70% to 79%. In conclusion, there was an evident enhancement in student learning outcomes in Physical Education from cycle to cycle, where both Cycle I and Cycle II showed an improvement. The discovery learning model can be employed by teachers as an alternative method to elevate the student motivation in learning Physical Education.

A product-form network for systems with job stealing policies

In this paper, we introduce a new product-form queueing network model where servers are always busy. This is obtained by defining a job movement policy that admits instantaneous migrations of jobs from non-empty waiting buffers to empty ones. Thus, the resulting routing scheme is statedependent. This class of networks tends to maximize the system throughput and can be used to model situations where successive refinements on jobs improve the processes quality but are not strictly required to obtain a result.

멀티 블록 격자 재분할이 자동차 공기역학에 미치는 영향

The impact of multi-block mesh refinement on automobile aerodynamics was investigated using three refinement methods: (1) overall mesh refinement, (2) ground mesh refinement, and (3) prism layer control. The open source CFD code, OpenFOAM V10, was utilized and simulations were conducted on the full-scale Notchback DrivAer model. For each method, the effects of mesh refinement were analyzed by refining different regions. In the overall mesh refinement study, successive multi-block grid refinement regions were established - the grid size becomes finer as the block is closer to the car surface. The lift coefficient was affected by grid refinement in regions near the automobile body. The ground mesh refinement study was conducted by controlling two grid sizes related to the ground region: volume mesh and surface mesh. The prediction of drag coefficient was fairly robust with ground region refinement, and the lift coefficient was more accurate with a smaller ground region grid. However, an excessively small surface grid reduced the accuracy of both drag and lift coefficients. In the prism layer study, the accuracy of the drag coefficient was independent of the prism layer setup, while the layer thickness and expansion ratio had a significant impact on the lift coefficient.

MIMO radar design with joint constant-modulus and any p-norm similarity constraints

MIMO radar plays a key role in many applications, e.g., autonomous driving, smart parking, and gesture recognition. The similarity waveform constraint is an important constraint for radar waveform design. However, the joint constant-modulus and similarity constraints pose a big challenge in MIMO radar design. Only the special case with ∞-norm similarity and constant-modulus constraints is tackled by the semidefinite relaxation (SDR) and the successive quadratic refinement (SQR) methods. In this paper, the joint constant-modulus and any p-norm (1≤p≤∞) similarity constraints are tackled by the proposed relax-and-retract algorithm. In particular, the nonconvex constant-modulus constraint is first relaxed to a convex constraint, and then the retract operation is guaranteed to recover a constant-modulus solution within a fixed iteration number. Extensive simulation results show that full range similarity control and constant-modulus constraints are satisfied under different p-norms. For the special case with 1-norm, it is firstly found to be a constant-modulus-inducing norm. For the special case with ∞-norm, the proposed relax-and-retract method has less computational complexity than the SDR and SQR approaches.

Crystal-chemical characterisation and spectroscopy of fluorcarletonite and carletonite

AbstractThe minerals of carletonite group, fluorcarletonite, KNa4Ca4[Si8O18](CO3)4(F,OH)·H2O and carletonite, Na4Ca4[Si8O18](CO3)4(OH,F)·H2O, were investigated using a multi-method approach. A detailed comparative chemical study of the minerals was carried out using electron probe microanalysis and Fourier transform infrared spectroscopy. Using X-ray techniques and the results obtained, geometrical and distortion characteristics of the mineral structures are calculated and the successful crystal-structure refinement of these two natural compounds are given. Using spectroscopic and luminescence methods and ab initio calculations, it is shown that hole defects (CO3)•– are responsible for the colouration of the samples studied. Luminescence due to 5d–4f transition in Ce3+ ions is observed in both investigated compounds. Moreover, luminescence attributed to intrinsic luminescence, corresponding to the decay of electronic excitations of (CO3)2– complexes in the carletonite sample, is registered for the first time in phyllosilicates. An analysis of the optical absorption spectra and g-tensor values suggests that (CO3)•– defects in the crystal structure are localised in the C1 positions. Identification of these specific properties for these sheet silicates, with a two-dimensional infinite tetrahedral polymerisation, indicates that carletonites could be prospective materials for novel phosphors and luminophores.

Differential Gains in Surgical Outcomes for High-Risk vs Low-Risk Pancreaticoduodenectomy with Successive Refinements of Risk-Stratified Care Pathways.

The use of risk-stratified pancreatectomy care pathways (RSPCPs) is associated with reduced length of stay (LOS). This study sought to evaluate the impact of successive pathway revisions with the hypothesis that high-risk patients require iterative pathway revisions to optimize outcomes. A prospectively maintained database (October 2016 to December 2021) was evaluated for pancreaticoduodenectomy patients managed with RSPCPs preoperatively assigned based on postoperative pancreatic fistula (POPF) risk. Launched in October 2016 (version [V] 1), RSPCPs were optimized in February 2019 (V2) and November 2020 (V3). Targeted pathway components included earlier nasogastric tube removal, diet advancement, reduced intravenous fluids and opioids, institution-specific drain fluid amylase cutoffs for early day 3 removal, and patient education. Primary outcome was LOS. Secondary outcomes included major complication (Accordion grade 3+), POPF (International Study Group for Pancreatic Surgery Grade B/C), and delayed gastric emptying (DGE). Of 481 patients, 234 were managed by V1 (83 high-risk), 141 by V2 (43 high-risk), and 106 by V3 (43 high-risk). Median LOS reduction was greatest in high-risk patients with a 7-day reduction (pre-RSPCP, 12 days; V1, 9 days; V2, 7 days; V3, 5 days), compared with low-risk patients (pre-pathway, 10 days; V1, 6 days; V2, 5 days; V3, 4 days). Complications decreased significantly among high-risk patients (V1, 45%; V2, 33%; V3, 19%; p < 0.001), approaching rates in low-risk patients (V1, 21%; V2, 20%; V3, 14%). POPF (V1, 33%; V2, 23%; V3, 16%; p < 0.001) and DGE (V1, 23%; V2, 22%; V3, 14%; p < 0.001) improved among high-risk patients. Risk-stratified pancreatectomy care pathways are associated with reduced LOS, major complication, Grade B/C fistula, and DGE. The easiest gains in surgical outcomes are generated from the immediate improvement in the patients most likely to be fast-tracked, but high-risk patients benefit from successive application of the learning health system model.

Stochastic chaining and strengthened information-theoretic generalization bounds

We propose a new approach to apply the chaining technique in conjunction with information-theoretic measures to bound the generalization error of machine learning algorithms. Different from the deterministic chaining approach based on hierarchical partitions of a metric space, previously proposed by Asadi et al., we propose a stochastic chaining approach, which replaces the hierarchical partitions with an abstracted Markovian model borrowed from successive refinement source coding. This approach has three benefits over deterministic chaining: (1) the metric space is not necessarily bounded, (2) facilitation of subsequent analysis to yield more explicit bound, and (3) further opportunity to optimize the bound by removing the geometric rigidity of the partitions. The proposed approach includes the traditional chaining as a special case, and can therefore also utilize any deterministic chaining construction. We illustrate these benefits using the problem of estimating Gaussian mean and that of phase retrieval. For the former, we derive a bound that provides an order-wise improvement over previous results, and for the latter we provide a stochastic chain that allows optimization over the chaining parameter.

IRS Aided MEC Systems With Binary Offloading: A Unified Framework for Dynamic IRS Beamforming

In this paper, we develop a unified dynamic intelligent reflecting surface (IRS) beamforming framework to boost the sum computation rate of an IRS-aided mobile edge computing (MEC) system, where each device follows a binary offloading policy. Specifically, the task of each device has to be either executed locally or offloaded to MEC servers as a whole with the aid of given number of IRS beamforming vectors available. By flexibly controlling the number of IRS reconfiguration times, the system can achieve a balance between the performance and associated signalling overhead. We aim to maximize the sum computation rate by jointly optimizing the computational mode selection for each device, offloading time allocation, and IRS beamforming vectors across time. Since the resulting optimization problem is non-convex and NP-hard, there are generally no standard methods to solve it optimally. To tackle this problem, we first propose a penalty-based successive convex approximation algorithm, where all the associated variables in the inner-layer iterations are optimized simultaneously and the obtained solution is guaranteed to be locally optimal. Then, we further derive the offloading activation condition for each device by deeply exploiting the intrinsic structure of the original optimization problem. According to the offloading activation condition, a low-complexity algorithm based on the successive refinement method is proposed to obtain high-quality solutions, which is more appealing for practical systems with a large number of devices and IRS elements. Moreover, the optimal condition for the proposed low-complexity algorithm is revealed. Numerical results demonstrate the effectiveness of our proposed algorithms and also unveil the fundamental performance-cost tradeoff of the proposed dynamic IRS beamforming framework.

Spin-glass behavior and redox catalytic properties of room temperature produced ZnCrMnO4

Recognizing the multifunctional capability of spinels, synthesis, and properties of oxide spinel with an equal concentration of Jahn Teller active Mn 3+ and geometrically frustrated Cr 3+ with non-magnetic Zn 2+ have been explored. ZnCrMnO 4 , resulting from the room temperature oxidation reaction, has an average crystallite size of 16 nm. Nearly 25% of Zn occupies the octahedral sites along with Cr and Mn, as revealed by the successful structural refinement in the Fd-3m space group. Electron microscopic results confirm cubic spinel formation. Raman spectrum shows the disordered nature of the spinel. X-ray photoelectron spectral (XPS) analysis establishes mixed valences of manganese ((III), (IV)) and chromium ((III) and (VI)). ZnCrMnO 4 displays electronic transitions typical of Mn 3+ and Cr 3+ in its UV–Visible diffuse reflectance spectrum. Spin-glass frustration at 26 K, followed by an antiferromagnetic ordering at 10 K, is noticed for the sample from the magnetic measurements. The sample exhibits a surface area of 138 m 2 /g (BET measurements) and catalyzes the oxidation of aromatic alcohols (phenol, benzyl alcohol) and reduction of nitroaromatics efficiently.

Evaluation of quality of online shopping services in times of COVID-19 based on E-S-QUAL model and Fuzzy TOPSIS method.

This paper aims to propose an approach to evaluate the quality of online shopping services in times of pandemic COVID-19, from the ordering of quality attributes taking into account customers' perception. The proposed approach was developed from a structured questionnaire containing 25 quality attributes adapted from the E-S-QUAL model and applied to consumers of online shopping services. Fuzzy set theory was used in the approach to simplify the subjectivity of human judgment, along with the extension of Technique for Order Performance by Similarity to Ideal Solution (TOPSIS). Therefore, this research was classified as applied, exploratory, quantitative and survey. To achieve the research objective, 819 questionnaires were collected. Among the main findings, it is highlighted that the attributes "product availability", "products with excellent quality", "confidence in online shopping processes" and "ease of buying online" were the ones that presented the best perceptions of quality by the respondents. At the other end, the attributes "opinion sharing on social networks", "buying online is a good option when you have little time", "distraction in online shopping searches" and "shopping online is a pleasure" showed the highest level of dissatisfaction with the service. Thus, this article highlights the importance of online shopping services in times of the pandemic caused by COVID-19, and its main contribution and originality is the development of an approach that aims to support the decision-making process, establishing strategic actions for the continuous improvement of online shopping services with the reduction of subjectivity in customer perception and with successive refinements.

Strategic Successive Refinement With Interdependent Decoders Cost Functions

In decentralized and decision-oriented communication paradigms, autonomous devices strategically implement information compression policies. In this work, we study a strategic communication game between an encoder and two decoders. An i.i.d. information source, observed by the encoder, is transmitted to the decoders via two perfect links, one reaching the first decoder only and the other reaching both decoders, as in the successive refinement setup. All three communicating devices are assumed to be rational, i.e. they want to minimize their respective cost functions, that depend on the source variable and the output symbols of both decoder. The game takes place as follows: the encoder commits to implementing an encoding strategy which induces a Bayesian game among the two decoders. The encoder is the Stackelberg leader and the two decoders are the Stackelberg followers, they select simultaneously the output sequences that minimize their respective long-run costs. We characterize the asymptotic behavior of the long-run optimal cost of the encoder, when the decoders implement decoding strategies that form a Bayes-Nash equilibrium. We show that this optimal cost converges to a single-letter expression which involves two auxiliary random variables and single-letter incentive constraints of the decoders.

Hypergraph-Based Source Codes for Function Computation Under Maximal Distortion

This work investigates functional source coding problems with maximal distortion, motivated by approximate function computation in many modern applications. The maximal distortion treats imprecise reconstruction of a function value as good as perfect computation if it deviates less than a tolerance level, while treating reconstruction that differs by more than that level as a failure. Using a geometric understanding of the maximal distortion, we propose a hypergraph-based source coding scheme for function computation that is constructive in the sense that it gives an explicit procedure for finding optimal or good auxiliary random variables. Moreover, we find that the hypergraph-based coding scheme achieves the optimal rate-distortion function in the setting of coding for computing with side information and achieves the Berger-Tung sum-rate inner bound in the setting of distributed source coding for computing. It also achieves the El Gamal-Cover inner bound for multiple description coding for computing and is optimal for successive refinement and cascade multiple description problems for computing. Lastly, the benefit of complexity reduction of finding a forward test channel is shown for a class of Markov sources.

Surrogate Model for Design Uncertainty Estimation of Nonlinear Electromagnetic Vibration Energy Harvester

The paper proposes a solution to the problem of estimating the uncertainty of the output power with respect to the design parameters for an electromagnetic vibration energy harvesting converter. Due to costly utilisation of time-domain mathematical models involved in the procedure of determination of the average output power of the system, an algorithm for developing the surrogate model that enables rapid estimation of this quantity within the prescribed frequency band limits is proposed. As a result, the metamodel sensitive to the most impactful design parameters is developed using Kriging with successive refinement of the design grid for gaining the accuracy. Under operational conditions with a constant magnitude of the acceleration signal and the prescribed frequency band limits, the surrogate model enables evaluation of the average output power of the system at 105 design points in less than 2 s of computer execution time. The consistency and accuracy of the results obtained from the surrogate model is confirmed by comparison of selected results of computations with measurements carried out on the manufactured prototype. Based on the latter and the surrogate model, the confidence intervals for the design procedure were determined and the most important spread quantities were estimated, providing quantitative information on the accuracy of the design procedure developed for the considered system.

Outcomes of different stem sizes in shoulder arthroplasty

BackgroundThe successive refinement in implant design and operative technique alongwith improved understanding has resulted in increased incidence of total shoulder arthroplasty (TSA). Simultaneously, the indications of TSA have widened and include a range of shoulder pathologies. MethodsUsing the keywords and relevant literature, we have described an overview of the different stem sizes used in shoulder arthroplasty. Relevant description of clinical and radiological outcome is done with regards to different stem sizes. DiscussionThere are plethora of shoulder replacement systems, based on unique philosophy and having their own advantages and disadvantages. Additionally, the rise in ageing population had increased the need for revision TSA, thereby necessitating the judicious choice of implant at primary TSA. We further present the role of cemented and uncemented humeral stems and discuss the findings of finite element analysis. The choice of humeral stem size and use of cemented or uncemented stems have been reported to affect the clinical and radiological outcomes.

Teacher strategies that foster students’ boundary-crossing expertise when addressing problems with wicked tendencies

ABSTRACT Professionals are increasingly involved in attempts to understand and address problems with wicked tendencies, which require crossing boundaries between disciplines, organisations and stakeholder perspectives. This multiple-case study investigated six higher professional education courses in order to develop better understanding of how teachers foster the development of students’ boundary-crossing expertise through enhancing relevant learning processes in courses focussing on wicked-problem-solving in interdisciplinary and multi-stakeholder contexts. We viewed students’ relevant learning processes as learning mechanisms that foster boundary awareness (identification and reflection) and boundary work (coordination and transformation) and considered teachers to be enablers of such learning processes. Data came from semi-structured interviews with teachers, students and stakeholders, observations and document study. We identified nine interrelated enabling strategies teachers used. To foster students’ observation of wickedness through boundary awareness, they encouraged mutual acquaintance, open exploration, opportunities for learning, and multi-perspectivity. To foster students’ action through boundary work, they encouraged initial contact, joint action and multifaceted perspectives on value creation. To foster the interplay between boundary awareness and work, they encouraged successive refinement and structure while embracing wickedness. Balancing the tension that students experience at boundaries when navigating complexity, uncertainty and value divergence was identified as an important element of these enabling strategies.

Evolution of microstructure and mechanical properties of ZK60 magnesium alloy processed by asymmetric lowered-temperature rolling

Asymmetric lowered-temperature rolling was applied to the fabrication of fine-grained ZK60 magnesium alloy sheet with weak basal texture along the rolling direction (RD). The results showed that multi-pass lowered- temperature rolling could significantly improve the microstructure homogeneity and refine the grain size. Meanwhile, a fiber texture along the transverse direction (TD) gradually developed during rolling process. Importantly, the shear deformation along the RD made the c-axis of basal plane rotate to the RD, weakening the basal texture along this direction. Influenced by such microstructure variation, the yield strength along the TD continuously increased due to the successive grain refinement and the increased activation of prismatic slips, whereas the uniform elongation decreased owing to the decline of strain hardening ability. In contrast, the continuous weakening of basal texture along the RD increased the activation of soft basal slips, greatly offsetting the strengthening effect contributed by grain refinement and thereby causing the slight decrease of yield strength.