New satellite constellations to provide high-resolution atmospheric observations from microwave (MW) sounders operating in low-Earth orbit are now coming online and are providing operationally useful data. The first of these missions, the NASA Time-Resolved Observations of Precipitation structure and storm Intensity with a Constellation of Smallsats (TROPICS) Earth Venture (EVI-3) mission, was successfully launched into orbit on May 7 and 25, 2023 (Eastern Daylight Time, two CubeSats in each of the two launches). TROPICS is now providing nearly all-weather observations of 3-D temperature and humidity, as well as cloud ice and precipitation horizontal structure, at high temporal resolution to conduct high-value science investigations of tropical cyclones (TCs). TROPICS is providing rapid-refresh MW measurements (median refresh rate of better than 60 min early in the mission with four functional CubeSats, and now approximately 70–90 min with three functional CubeSats) over the tropics that can be used to observe the thermodynamics of the troposphere and precipitation structure for storm systems at the mesoscale and synoptic scale over the entire storm lifecycle. Hundreds of high-resolution images of TCs have been captured thus far by the TROPICS mission, revealing the detailed structure of the eyewall and surrounding rain bands. The new 205-GHz channel in particular (together with a traditional channel near 92 GHz) is providing new information on the inner storm structure, and, coupled with the relatively frequent revisit and low downlink latency, is already informing TC analysis at operational centers. Here, we present an overview of the TROPICS mission after two years of successful science operations with a focus on the suite of geophysical (Level 2) products (atmospheric vertical temperature and moisture profiles, instantaneous surface rain rate, and TC intensity) and the science investigations that have been enabled by these new measurements.

The goal of dynamic signed network embedding (DSNE) is to represent the nodes in a dynamic signed network (DSN) as embeddings that preserve the evolving nature of conflicting relationships between nodes. While existing DSNE methods are useful for understanding polarization between users in diverse domains, they fail to consider the concept of a community boundary that contributes to network-wide polarization and lack inductive ability due to their reliance on homophily bias. To address these limitations, we propose a novel DSNE method, named PolarDSN, which learns the evolution of network POLARization and enhances inductive ability for Dynamic Signed Networks. It leverages node-level community boundaries as well as structural characteristics of nodes such as structural isomorphism and temporal transitivity. Experiments on four real-world DSN datasets demonstrate that PolarDSN consistently and significantly outperforms 12 state-of-the-art methods, achieving up to 31.6% and 21.1% improvement in macro-F1 for transductive and inductive settings, respectively. The code is available at https://github.com/kmj0792/PolarDSN.

The four NASA TROPICS Earth Venture (EVI-3) CubeSat constellation satellites were successfully launched into orbit on May 8 and May 26, 2023 (NZST) – two satellites were deployed in each launch. TROPICS is now providing nearly all-weather observations of 3-D temperature and humidity, as well as cloud ice and precipitation horizontal structure, at a median refresh rate of approximately 60 minutes to conduct high-value science investigations of tropical cyclones. TROPICS provides microwave measurements in twelve channels spanning 90-205 GHz over the tropics that can be used to observe the thermodynamics of the troposphere and precipitation structure for storm systems at the mesoscale and synoptic scale over the entire storm lifecycle. Hundreds of high-resolution images of tropical cyclones have been captured thus far by the TROPICS mission, revealing detailed structure of the eyewall and surrounding rain bands. The new 205-GHz channel in particular (together with a traditional channel near 91.65 GHz) is providing new information on the inner storm structure, and, coupled with the relatively frequent revisit and low downlink latency, is informing tropical cyclone analysis at operational centers. In this paper, the radiance and geophysical performance of Pathfinder and the constellation satellites is presented, showing that the mission is on track to meet its baseline requirements.

The problem of representing nodes in a signed network as low-dimensional vectors, known as signed network embedding (SNE), has garnered considerable attention in recent years. While several SNE methods based on graph convolutional networks (GCNs) have been proposed for this problem, we point out that they significantly rely on the assumption that the decades-old balance theory always holds in the real-world. To address this limitation, we propose a novel GCN-based SNE approach, named as TrustSGCN, which corrects for incorrect embedding propagation in GCN by utilizing the trustworthiness on edge signs for high-order relationships inferred by the balance theory. The proposed approach consists of three modules: (M1) generation of each node’s extended ego-network; (M2) measurement of trustworthiness on edge signs; and (M3) trustworthiness-aware propagation of embeddings. Specifically, TrustSGCN leverages topological information to measure trustworthiness on edge sign for high-order relationships inferred by balance theory. It then considers structural properties inherent to an input network, such as the ratio of triads, to correct for incorrect embedding propagation. Furthermore, TrustSGCN learns the node embeddings by leveraging two well-known social theories, i.e., balance and status, to jointly preserve the edge sign and direction between nodes connected by existing edges in the embedding space. The experiments on six real-world signed network datasets demonstrate that TrustSGCN consistently outperforms six state-of-the-art GCN-based SNE methods. The code is available at https://github.com/kmj0792/TrustSGCN .

The problem of signed network embedding (SNE) aims to represent nodes in a given signed network as low-dimensional vectors. While several SNE methods based on graph convolutional networks (GCN) have been proposed, we point out that they significantly rely on the assumption that the decades-old balance theory always holds in the real world. To address this limitation, we propose a novel GCN-based SNE approach, named as TrustSGCN, which measures the trustworthiness on edge signs for high-order relationships inferred by balance theory and corrects incorrect embedding propagation based on the trustworthiness. The experiments on four real-world signed network datasets demonstrate that TrustSGCN consistently outperforms five state-of-the-art GCN-based SNE methods. The code is available at https://github.com/kmj0792/TrustSGCN.

Recent mobile phones known as smartphones offer a variety of applications, such as Web browsing, entertainment tools, and personal calendar and contact management applications of the type that traditionally run on desktop computers. Some of the reasons why smartphones became popular rapidly in Korea may be related to the adoption by the type of user known as the early adopter. Because the early adopter group played a more crucial role in the area of mass consumption and because the mass market is changing more rapidly than before, this study examines mobile phone purchase and usage behaviours of early adopter groups in Korea in order to gain vital insights into establishing marketing strategies for early adopter groups. In this study, segmentation by means of a factor analysis and cluster analysis is conducted to classify early adopter groups in accordance with their activities, interests, and opinion. Specifically, factor analysis is employed to identify the common characteristics among lifestyle variables, and cluster analysis is then adopted for those factors to classify early adopter groups according to their lifestyles. In addition, we analyse the mobile phone purchase and usage behaviours of early adopter groups in Korea. The results of this study can contribute to the effort to classify early adopter groups while also having implications pertaining to mobile phone vendors and mobile service providers who target early adopters depending on their different characteristics.

In this paper, we introduced real renewal examples of KTF's mobile data service. At the time of development, we focused on user analysis and tried to improve the existing mobile data service based on user's opinion. After the new mobile data service was launched based on user experience analysis, the customers were satisfied with the newly developed mobile data service. We expect that new mobile data service would make continuous revenue streams and contribute to image up the company.

This study analyzes passive and active microwave measurements during the 2003 Wakasa Bay field experiment for understanding of the electromagnetic characteristics of frozen hydrometeors at millimeter-wave frequencies. Based on these understandings, parameterizations of the electromagnetic scattering properties of snow at millimeter-wave frequencies are developed and applied to the hydrometeor profiles obtained by airborne radar measurements. Calculated brightness temperatures and radar reflectivity are compared with the millimeter-wave measurements.

Snowfall is an important component of the Earth's precipitation and hydrological cycle. Remote measurements of frozen hydrometeor properties have been limited because coincident measurements of microphysical and electromagnetic properties of snowfall have not been available. Snowfall measurement from space has been suggested as a solution to overcome this limitation. The precipitating clouds contain a sufficient density of ice water equivalent from snow crystals, graupel, or both, when brightness temperature is at 85 GHz. The NOAA Advanced Microwave Sounding Unit (AMSU) has been used to derive snowfall over land using millimeter-wave radiometry. This study analyzes the millimeter-wave radiometric measurements of frozen hydrometeors during the field experiment that was held in Wakasa bay of Japan in January 29, 2003. It was found that a lognormal distribution represents the snow PSD during the field experiments. The MM5 cloud simulation is employed to provide temperature and humidity profiles for the radiative transfer calculations. This study seeks to derive characteristics of snow whose electromagnetic properties are consistent with microwave brightness temperature at several frequencies provided by the MIR sensors and the radar reflectivity measured by PR-2 (Precipitation Radar) and ACR (Airborne Cloud Radar).

Physical approaches in microwave remote sensing to measure nonspherical frozen hydrometeors are frequently parameterized as spherical particles, assuming either dielectric mixing approximation or equivalent spheres, to make Mie-theory applicable. However, the applicability of those simplified approximations in millimeter-wave radar and radiometric remote sensing of frozen hydrometeors need to be evaluated. To seek a parameterization to represent the electromagnetic (EM) properties of frozen hydrometeors at millimeter-wave frequencies, this study analyzes the Discrete Dipole Approximation (DDA) method calculated single scattering from nonspherical snow crystals at millimeter-wave frequencies (95, 140, 183, 220, and 340 GHz). Sizes, shapes, density, and refractive indices for five snow crystal models (hexagonal column, hexagonal plate, sector plate, planar rosette:, and spatial rosette) employed in this study are described in Kim et al. (2004). The results shown in this study assume that all particles are randomly oriented. By comparing with the DDA calculated single scattering properties, this study evaluates fast parameterization methods to represent the EM properties of snow at millimeter-wave frequencies. Dielectric mixing theory, which is widely used by the microwave remote sensing community, and the equivalent sphere approach, which is commonly used by infrared (IR) and ultraviolet (UV) remote sensing community are considered. In addition, equivalent cylinders and equivalent ellipsoids are also tested to examine how much the single scattering properties depend on the detailed shapes of ice crystals.

The development of physical model to retrieve snowfall from millimeter-wave measurements require the calculation of scattering and emission properties which can generate brightness temperatures (Tbs) and/or radar reflectivities that are consistent with observations. Frozen hydrometeors have various sizes, shapes, orientations, phase, and density so that it is difficult to parameterize their electromagnetic (EM) properties. For many physical approaches in remote sensing, non-spherical frozen hydrometeors are parameterized as spherical particles and Mie-theory is employed because it is faster than more rigorous analyses of scattering by nonspherical particles. However, the applicability of those simplified approximations in millimeter-wave radar and radiometer remote sensing of frozen hydrometeors has not yet been proved. To seek a parameterization to represent the EM properties of frozen hydrometeors at millimeter-wave frequencies, this study employs the Discrete Dipole Approximation (DDA) method Drain and Flatau (2003) and analyzes the calculated single scattering from nonspherical snow crystals at millimeter-wave frequencies (95, 140, 183, 220, and 340 GHz). Various assumptions, which were made in previous studies, for the snow microphysical properties, such as density, dimension, and particle size distribution are applied to these comparisons. The uncertainty range of EM property caused by various snow habits, density, and particle size distribution are presented.

This study analyzes the performance at millimeter-wave frequencies of five radiative transfer models, i.e., the Eddington second-order approximation with and without /spl delta/-scaling, the Neumann iterative method with and without geometric series approximation, and the Monte Carlo method. Three winter time precipitation profiles are employed. The brightness temperatures calculated by the Monte Carlo method, which considers all scattering angles, are considered as benchmarks in this study. Brightness temperature differences generated by the other models and sources of those differences are examined. In addition, computation speeds of the radiative transfer calculations are also compared. Results show that the required number of quadrature angles to generate brightness temperatures consistent with the Monte Carlo method within 0.5 K varies between two and six. At least second to 15th orders of multiple scattering, depending on the significance of scattering, are required for the Neumann iterative method to represent accurately the inhomogeneous vertical structure of the scattering and absorbing components of precipitating clouds at millimeter-wave frequencies. The /spl delta/-scaling in the Eddington second-order approximation improves brightness temperatures significantly at nadir for cloud profiles that contain snow due to the correction for strong scattering, while it did not make any difference at 53/spl deg/ off-nadir. The computational time comparisons show that the Neumann iterative method generates accurate brightness temperatures with better computational efficiency than the Monte Carlo method for cloud profiles with weak scattering. However, it can consume computational time that is even greater than the Monte Carlo method for some millimeter-wave frequencies and cloud profiles with strong scattering. A geometric series approximation can improve computational efficiency of the Neumann iterative method for those profiles. In view of the ease of introducing scaled parameters into the Eddington second-order approximation, good computational time efficiency, and better than within 2 K accuracy when compared with the Monte Carlo method, we recommend its use for brightness temperature calculations at millimeter-waves in precipitating atmospheres.

Falling snow is an important component of global precipitation in extratropical regions. This paper describes the methodology and results of physically based retrievals of snow falling over land surfaces. Because microwave brightness temperatures emitted by snow-covered surfaces are highly variable, precipitating snow above such surfaces is difficult to observe using window channels that occur at low frequencies (/spl nu/100 GHz) where water vapor screens the surface emission, and sensitivity to frozen hydrometeors is significant. However, the scattering effect of snowfall in the atmosphere at those higher frequencies is also impacted by water vapor in the upper atmosphere. The theory of scattering by randomly oriented dry snow particles at high microwave frequencies appears to be better described by regarding snow as a concatenation of "equivalent" ice spheres rather than as a sphere with the effective dielectric constant of an air-ice mixture. An equivalent sphere snow scattering model was validated against high-frequency attenuation measurements. Satellite-based high-frequency observations from an Advanced Microwave Sounding Unit (AMSU-B) instrument during the March 5-6, 2001 New England blizzard were used to retrieve snowfall over land. Vertical distributions of snow, temperature, and relative humidity profiles were derived from the Mesoscale Model (MM5) cloud model. Those data were applied and modified in a radiative transfer model that derived brightness temperatures consistent with the AMSU-B observations. The retrieved snowfall distribution was validated with radar reflectivity measurements obtained from a ground-based radar network.

This study analyzes the performance of the Eddington second-order approximation with and without /spl delta/-scaling, the Neumann iterative method, and the Monte Carlo method at millimeter-wave frequencies. The reliability and consistency of these radiative transfer models is identified and the differences and source of those differences in brightness temperatures that may originate in the forward computations are examined. In addition, computation speeds of the radiative transfer calculations are also compared for evaluation.

A physically based retrieval algorithm was developed to estimate snowfall over land. The retrieval algorithm relies on the MM5 model that generates the vertical structure of a snow cloud, including snow mass, snow particle effective diameter, and water vapor. The MM5 cloud simulation was used to provide statistics for generating the cloud characteristics. The snow cloud profile and surface emissivity were then used in radiative transfer calculations that were optimized against AMSU-B observations at 89, 150 and 183.3/spl plusmn/7, /spl plusmn/3, and /spl plusmn/1 GHz. The multi-parameter cloud model that produced brightness temperatures that best fit the AMSU-B observations was selected as the retrieved profile. The retrieved snowfall distribution was validated with radar reflectivity measurements obtained from the operational NWS radar network.

This paper describes the traffic engineering required for the next generation mobile communication systems. The next generation mobile communication systems will offer a variety of services (e.g., voice, data, video) to the mobile users (MUs) with different mobility behavior (e.g., stationary, pedestrian, vehicular) in both public and private environments. The traffic engineering presented in this paper considers all the above mentioned features. We introduce the handover rate and the time it takes a user to leave a cell area as the effects of user mobility, and the use of different traffic engineering models for a variety of services. We apply these models to a real mobile network and compare them with the existing models with respect to the network efficiency.

In the initial stage of PCS, large cells are provided for low density area and the high density areas are covered by the minimum cells. As the number of PCS subscribers becomes larger, it requires enormous demands for additional radio network capacity, which must evolve from extended cells to microcells in a given area. In this paper, we formulate the problem of finding an optimal expansion strategy of PCS radio network, mainly cells, over a planning horizon and develop a heuristic algorithm for the problem. The heuristic algorithm developed here uses a backward approach from the final time of the planning horizon and can be efficiently implemented for splitting the cells.