Abstract

The exact determination of settlement and the time required to complete that settlement is very important from the safety point of view. There are several methods available to find the rate of consolidation that is highly dependent on the settlement versus time curve. Here, it has been attempted to identify the suitable method for the determination of the rate of consolidation of coal ash. After analyzing the value of the coefficient of consolidation (Cv) estimated from various methods, the rectangular hyperbola method (RH method) is found to be in best linear correlation between the measured Cv and calculated Cv. The coal ash shows an increment in Cv with the increase in effective pressure. The Cv obtained from the RH method is higher than the Cv obtained from Taylor’s and Casagrande method that helps in close approximation with field Cv. The precise determination of Cv helps in better prediction of the time required for the consolidation settlement that will increase the performance of the structure.

Abstract

The emergence of vehicle connectivity technologies and associated applications have paved the way for increased consumer interest in connected vehicles. These modern day vehicles are now capable of sending/receiving vast amounts of data and offloading computation (which is one possible service) to servers thereby improving safety, comfort, driving experience, etc. In the early stages of connectivity, all the data communication and computation offloading happened between the cloud server and the vehicles. However, this is not feasible in scenarios having strict timing requirements and bandwidth cost constraints. Vehicular Edge Computing (VEC) demonstrated an efficient way to tackle the above problem. In order to optimally utilize the resources of the edge servers for data delivery, an efficient edge resource allocation framework needs to be developed. In a recent work, data/service delivery to connected vehicles assumed a worst-case scenario that all vehicles with routes passing through an edge appear in the edge coverage region simultaneously. However, this worst-case scenario is very pessimistic, which results in overestimation of edge resources. We address this by precisely computing the set of vehicles which simultaneously appear in the coverage region of an edge (which we call textit{vehicle overlaps}). In this work, we first propose an optimization framework for edge resource allocation that minimizes the bandwidth cost of data delivery to connected vehicles while considering the traffic flow and vehicle overlaps. Then, we propose an efficient heuristic to deliver data based on minimizing global edge bandwidth cost gradient under vehicle overlaps. We demonstrate the improvement in resource allocation considering vehicle overlaps. Using real world traffic data, we also demonstrate reduction in data delivery times using the proposed heuristic.

Abstract

In recent years, semi-transparent building-integrated photovoltaics (BIPV) technology has attracted attention for its renewable energy utilization. This research aims to develop a methodology for assessing the energy-saving potential of semi-transparent photovoltaic (STPV) window, which has a complex relationship with daylighting and air conditioning (AC) electricity consumption. A case study has been developed for the composite climate of Hyderabad, India. The study examines four commercially available single and double pane STPV windows and similar non-photovoltaic windows. For evaluation, an automated parametric simulation tool was developed to compute the net electricity consumption (NEC) for a representative model building with different window systems, and several window-to-wall ratios (WWR) and orientations. The result shows benefit in adopting the STPV window system across all directions and higher optimal WWR in STPV window as compared to normal window with the same opto-thermal characteristics.

Abstract

In this paper, we propose a predictive and cooperative optimal control based autonomous navigation and collision avoidance for multiple fixed-wing aircraft (FWA) that also takes into account the physical constraints of the aircraft. The proposed method is implemented in a cooperative framework, analogous to the Reciprocal Velocity Obstacle (RVO) framework for autonomous navigation and collision avoidance for FWA swarm moving in a three dimensional (3D) space. Also, the change in performance with respect to varying prediction horizon is analyzed through numerical simulations. As a result of predictive optimal control and cooperation, we get less conservative maneuvers, reduced path lengths, and less deviation from the shortest path when compared to the conventional method without prediction and cooperation. Simulation results are provided, highlighting the advantages of the proposed method when compared to a popular method (Optimal reciprocal collision avoidance) for collision avoidance in 3D for FWA swarm and also against FGA algorithm (Fast geometric avoidance algorithm).

Abstract

India Meteorological Department (IMD) has started block-level level agromet advisory (AA) service from the year 2015 and is currently operating in a few blocks of each state across India. In a block-level AA service, on every Tuesday and Friday, AA is being prepared for each block based on the block-level Medium Range weather Forecast (MRF). In this paper, we propose a framework to improve the preparation of block- level AA by modeling a weather situation as “Category-based Weather Condition (CWC)” and exploiting both “temporal reuse” and “spatial reuse” of AA based on the similarity among CWCs. The weather data analysis for 12 blocks of Telangana by considering the phenophase-specific CWCs of Rice crop showed that there is a scope to improve the efficiency of block-level AA bulletin preparation process by exploiting reuse

Abstract

here are certain dynamics which although are non-Markovian but never show information backflow. We show that if two such dynamical maps are considered in a scenario where the order of application of these two dynamical maps are not definite, then the effective channel can manifest information backflow. In particular, we use quantum SWITCH to activate such channels. In contrast, those channels can never be activated even if we use many copy of such channels in series or parallel action. We then investigate the actual cause and dynamics behind the quantum SWITCH experiment and find out that after the action of quantum SWITCH both the CP (Complete Positive)- divisiblity and P (Positive)- divisibility of the channel breaks down, triggering the information backflow. Our investigations shed new light on the fundamental cause of the advantages of quantum SWITCH

Abstract

Directions of arrival (DOA) estimation or localization of sources is an important problem in many applications for which numerous algorithms have been proposed. Most lo- calization methods use block-level processing that combines multiple data snapshots to estimate DOA within a block. The DOAs are assumed to be constant within the block duration. However, these assumptions are often violated due to source motion. In this paper, we propose a signal model that cap- tures the linear variations in DOA within a block. We applied conventional beamforming (CBF) algorithm to this model to estimate linear DOA trajectories. Further, we formulate the proposed signal model as a block sparse model and sub- sequently derive sparse Bayesian learning (SBL) algorithm. Our simulation results show that this linear parametric DOA model and corresponding algorithms capture the DOA tra- jectories for moving sources more accurately than traditional signal models and methods.

Abstract

This work proposes a tractable estimation of the maximum a posteriori (MAP) threshold of various families of sparse-graph code ensembles, by using an approximation for the extended belief propagation generalized extrinsic information transfer (EBP-GEXIT) function, first proposed by M ́easson et al. We consider the transmission over non-binary complex-input additive white Gaussian noise channel and extend the existing results to obtain an expression for the GEXIT function. We estimate the MAP threshold by applying the Maxwell construction to the obtained approximate EBP-GEXIT charts for various families of low-density parity-check (LDPC), generalized LDPC, doubly generalized LDPC, and serially concatenated turbo codes (SC-TC). When codewords of SC-TC are modulated using Gray mapping, we also explore where the spatially-coupled belief propagation (BP) threshold is located with respect to the previously computed MAP threshold. Numerical results indicate that the BP threshold of the spatially-coupled SC-TC does saturate to the MAP threshold obtained via EBP-GEXIT chart.

Abstract

The quantum speed limit indicates the maximal evolution speed of the quantum system. In this work, we determine speed limits on the informational measures, namely the von Neumann entropy, maximal information, and coherence of quantum systems evolving under dynamical processes. These speed limits ascertain the fundamental limitations on the evolution time required by the quantum systems for the changes in their informational measures. Erasing of quantum information to reset the memory for future use is crucial for quantum computing devices. We use the speed limit on the maximal information to obtain the minimum time required to erase the information of quantum systems via some quantum processes of interest.

Abstract

The normal foveal anatomy consists of the extrusion of the plexiform layers, a formed foveal pit, cone photoreceptor outer segment (OS) lengthening, and outer nuclear layer (ONL) widening relative to the parafoveal OS and ONL.1 Foveal development begins with the centrifugal displacement of the inner retinal layers, followed by the centripetal migration of the cone photoreceptors toward the incipient fovea and finally cone photoreceptor specialization (PRS) (Fig 1A–E ).2 3 , 4 Foveal pit formation begins midgestation and continues postnatally characterized by pit deepening and widening. Simultaneously, outer retinal specialization occurs at a rapid rate in the first 2 years of life, but ONL widening continues up to the age of 13 years.4 Lengthening of the OS layer represents cone PRS and reflects peak cone photoreceptor density.5 The maturation of the human fovea is a complex process and is critical for visual function.4 Many genes are involved in the development of the retina. Pathogenic variants in these genes often cause disruption to the foveal developmental process, resulting in foveal hypoplasia (FH), which describes the underdevelopment of the fovea.Foveal hypoplasia is characterized by the continuation of inner retinal layers posterior to the foveola, and progressive loss of these foveal elements is represented by increasing grades of FH. Three key foveal development stages form the basis of the Leicester Grading System for FH, developed by Thomas et al1 (Fig 1F–H). The Leicester Grading System is divided into 4 grades of typical FH (grades 1–4) and 1 grade of atypical FH, which is associated with photoreceptor degeneration. The Leicester Grading System can be applied to a diverse range of genetic disorders, including albinism, achromatopsia, and those caused by pathogenic variants in PAX6, SLC38A8, FRMD7, and AHR. In addition to providing insight into the degree of foveal development, identifying the grade of FH has diagnostic and prognostic implications.1 ,7 Rufai et al7 reported that identifying the grade of FH can predict future visual acuity (VA) in preverbal children with nystagmus. The introduction of OCT has revolutionized ophthalmic diagnosis with the ability to promptly visualize retinal morphology in a high-resolution, noninvasive manner.8 ,9 Furthermore, the advent of handheld OCT has facilitated the foveal examination of pediatric patients.10 OCT is now available in most ophthalmology clinics and subsequently has rapidly become part of routine ophthalmic assessment.8 Thus, the necessary technology to identify foveal developmental abnormalities is now accessible in most centers. The phenotypic spectrum of albinism has been reported, including the variance in degree of arrested retinal development.11 ,12 Furthermore, high grades of FH (grades 3 and 4) have recently been consistently associated with SLC38A8 variants13 ; however, to date, the full spectrum of FH linked with variants of known genes involved in retinal development has not been investigated. Thus, it is unclear whether variants of certain genes known to be related to FH and nystagmus are associated with a more underdeveloped foveal morphology. We performed a comparative study to investigate and characterize the genotypic and phenotypic spectrum of FH in albinism, achromatopsia, PAX6, SLC38A8, FRMD7, and AHR variants.