Revisiting Self-Training with Regularized Pseudo-Labeling for Tabular Data

Recent progress in semi- and self-supervised learning has caused a rift in the long-held belief about the need for an enormous amount of labeled data for machine learning and the irrelevancy of unlabeled data. Although it has been successful in various data, there is no dominant semi- and self-supervised learning method that can be generalized for tabular data (i.e. most of the existing methods require appropriate tabular datasets and architectures). In this paper, we revisit self-training which can be applied to any kind of algorithm including the most widely used architecture, gradient boosting decision tree, and introduce curriculum pseudo-labeling (a state-of-the-art pseudo-labeling technique in image) for a tabular domain. Furthermore, existing pseudo-labeling techniques do not assure the cluster assumption when computing confidence scores of pseudo-labels generated from unlabeled data. To overcome this issue, we propose a novel pseudo-labeling approach that regularizes the confidence scores based on the likelihoods of the pseudo-labels so that more reliable pseudo-labels which lie in high density regions can be obtained. We exhaustively validate the superiority of our approaches using various models and tabular datasets.Comment: 10 pages for the main part and 8 extra pages for the appendix. 2 figures and 3 tables for the main par

SDN-based Coordination for IoT-Cloud Connectivity employing Wired/Wireless Multi-Access SmartX Boxes

Diversified Internet of Things (IoT) -related services typically require networking to the cloud/edge-cloud resources to process and store data from distributed IoT device boxes. In addition, various IoT-related services encourage leveraging different access networking, so IoT device boxes having multiple interfaces are becoming typical configuration. In order to efficiently provide IoT-cloud connectivity via multiple interfaces, multi-access networking is becoming a popular research keyword. And supporting reliable data transmission  of IoT data to the cloud is an important feature of multi-access networking. In this paper, to cope with the emerging multi-access networking, we propose SmartX miniBox and SDN-based coordination functionality. SmartX miniBox is a physical box designed to support multi-access networking with SDN-enabled wired interface and OVS-integrated WiFi interfaces. And SDN-based Coordination functionality coordinates SmartX miniBox and IoT device boxes in order to enhance reliability in data transmission. The coordination includes alternating access interfaces in IoT devices boxes and changing networking paths in multi-path wired topology when networking failures occur

CAST: Cluster-Aware Self-Training for Tabular Data

Self-training has gained attraction because of its simplicity and versatility, yet it is vulnerable to noisy pseudo-labels. Several studies have proposed successful approaches to tackle this issue, but they have diminished the advantages of self-training because they require specific modifications in self-training algorithms or model architectures. Furthermore, most of them are incompatible with gradient boosting decision trees, which dominate the tabular domain. To address this, we revisit the cluster assumption, which states that data samples that are close to each other tend to belong to the same class. Inspired by the assumption, we propose Cluster-Aware Self-Training (CAST) for tabular data. CAST is a simple and universally adaptable approach for enhancing existing self-training algorithms without significant modifications. Concretely, our method regularizes the confidence of the classifier, which represents the value of the pseudo-label, forcing the pseudo-labels in low-density regions to have lower confidence by leveraging prior knowledge for each class within the training data. Extensive empirical evaluations on up to 20 real-world datasets confirm not only the superior performance of CAST but also its robustness in various setups in self-training contexts.Comment: 17 pages with appendi

A STUDY ON THE INITIAL CHARACTERISTICS OF DOMESTIC SPENT NUCLEAR FUELS FOR LONG TERM DRY STORAGE

During the last three decades, South Korean nuclear power plants have discharged about 5,950 tons of spent fuel and the maximum bum-up reached 55 GWd/MTU in 2002. This study was performed to support the development of Korean dry spent fuel storage alternatives. First, we chose V5H-17 × 17 and KSFA-16 × 16 as representative domestic spent fuels, considering current accumulation and the future generation of the spent fuels. Examination reveals that their average burn-ups have already increased from 33 to 51 GWd/MTU and from 34.8 to 48.5 GWd/MTU, respectively. Evaluation of the fuel characteristics shows that at the average burn-up of 42 GWd/MTU, the oxide thickness, hydrogen content, and hoop stress ranged from 30 ∼ 60 μm, 250 ∼ 500 ppm, and 50 ∼ 75 MPa, respectively. But when burn-up exceeds 55 GWd/MTU, those characteristics can increase up to 100 μm, 800 ppm, and 120 MPa, respectively, depending on the power history. These results demonstrate that most Korean spent nuclear fuels are expected to remain within safe bounds during long-term dry storage, however, the excessive hoop stress and hydrogen concentration may trigger the degradation of the spent fuel integrity early during the long-term dry storage in the case of high burn-up spent fuels exceeding 45 GWd/MTU

REVIEW OF SPENT FUEL INTEGRITY EVALUATION FOR DRY STORAGE

Among the several options to solve PWR spent fuel accumulation problem in Korea, the dry storage method could be the most realistic and applicable solution in the near future. As the basic objectives of dry storage are to prevent a gross rupture of spent fuel during operation and to keep its retrievability until transportation, at the same time the importance of a spent fuel integrity evaluation that can estimate its condition at the final stage of dry storage is very high. According to the national need and technology progress, two representative nations of spent fuel dry storage, the USA and Japan, have established different system temperature criteria, which is the only controllable factor in a dry storage system. However, there are no technical criteria for this evaluation in Korea yet, it is necessary to review the previously well-organized methodologies of advanced countries and to set up our own domestic evaluation direction due to the nation's need for dry storage. To satisfy this necessity, building a domestic spent fuel test database should be the first step. Based on those data, it is highly recommended to compare domestic data range with foreign results, to build our own criteria, and to expand on evaluation work into recently issued integrity problems by using a comprehensive integrity evaluation code

Biosignal Compression Toolbox for Digital Biomarker Discovery

A critical challenge to using longitudinal wearable sensor biosignal data for healthcare applications and digital biomarker development is the exacerbation of the healthcare “data deluge,” leading to new data storage and organization challenges and costs. Data aggregation, sampling rate minimization, and effective data compression are all methods for consolidating wearable sensor data to reduce data volumes. There has been limited research on appropriate, effective, and efficient data compression methods for biosignal data. Here, we examine the application of different data compression pipelines built using combinations of algorithmic- and encoding-based methods to biosignal data from wearable sensors and explore how these implementations affect data recoverability and storage footprint. Algorithmic methods tested include singular value decomposition, the discrete cosine transform, and the biorthogonal discrete wavelet transform. Encoding methods tested include run-length encoding and Huffman encoding. We apply these methods to common wearable sensor data, including electrocardiogram (ECG), photoplethysmography (PPG), accelerometry, electrodermal activity (EDA), and skin temperature measurements. Of the methods examined in this study and in line with the characteristics of the different data types, we recommend direct data compression with Huffman encoding for ECG, and PPG, singular value decomposition with Huffman encoding for EDA and accelerometry, and the biorthogonal discrete wavelet transform with Huffman encoding for skin temperature to maximize data recoverability after compression. We also report the best methods for maximizing the compression ratio. Finally, we develop and document open-source code and data for each compression method tested here, which can be accessed through the Digital Biomarker Discovery Pipeline as the “Biosignal Data Compression Toolbox,” an open-source, accessible software platform for compressing biosignal data

Magneto-optic property measurement of bismuth substituted yttrium iron garnet films prepared by metal-organic-decomposition method at the 1310-nm and 1550-nm wavelengths

We have measured the magneto-optic (MO) properties of film-type bismuth substituted yttrium iron garnets (Bi1.5:YIG, Bi1.5Y1.5Fe5O12) prepared by using metal-organic-decomposition (MOD) method on glass substrates at the 1310-nm and 1550-nm wavelengths. The Verdet constant of the Bi1.5:YIG film in the unsaturated linear magnetization region has been experimentally determined from a sensitive measurement of the Faraday rotation of the Bi1.5:YIG films with a lock-in amplifier and an auto-balanced photoreceiver under alternating magnetic fields. The Bi:YIG films have been deposited on silica glass substrates without any buffer layer and with one of buffer layers of Bi1Y2Fe5O12 (Bi1:YIG) and Bi1Fe4Ga1Nd2O12 (Bi1:NIGG) which are used to compensate mismatch of the lattice constant and thermal expansion coefficient between the film and substrate. The maximum value of the measured Faraday rotation of the Bi1.5:YIG film was over 94.6 and 156.5 °/cm for an applied unsaturated magnetic field of 100 Gauss at wavelengths of 1310 and 1550 nm, respectively, when it was prepared at annealing temperature of 700 °C and annealing speed of 1 °C/min. The absorption coefficients of the Bi1.5:YIG films were measured to be 70 cm−1 and 330 cm−1, respectively, at each of the wavelengths, and the average Gilbert damping coefficient of the Bi1.5:YIG film with a Bi1:NIGG buffer layer was measured to be 6.42 ± 18.09 × 10−4 (with the minimum value of 0 and the maximum value of 24.51 × 10−4) from a conventional ferromagnetic resonance (FMR) measurement system. Our experimental result indicates that the magneto-optic property of the Bi:YIG films prepared by the MOD method is unstable and fluctuates from run to run although its average magnetic property may be useful for application to compact integrated optical isolators under an easy solution-based fabrication process. © 2019 Elsevier B.V.1

Modified Dynamic Physical Model of Valence Change Mechanism Memristors

© 2022 American Chemical Society.Valence change-type resistance switching behaviors in oxides can be understood by well-established physical models describing the field-driven oxygen vacancy distribution change. In those models, electroformed residual oxygen vacancy filaments are crucial as they work as an electric field concentrator and limit the oxygen vacancy movement along the vertical direction. Therefore, their movement outward by diffusion is negligible. However, this situation may not be applicable in the electroforming-free system, where the field-driven movement is less prominent, and the isotropic oxygen vacancy diffusion by concentration gradient is more significant, which has not been given much consideration in the conventional model. Here, we propose a modified physical model that considers the change in the oxygen vacancies' charged state depending on their concentrations and the resulting change in diffusivity during switching to interpret the electroforming-free device behaviors. The model suggests formation of an hourglass-shaped filament constituting a lower concentration of oxygen vacancies due to the fluid oxygen diffusion in the thin oxide. Consequently, the proposed model can explain the electroforming-free device behaviors, including the retention failure mechanism, and suggest an optimized filament configuration for improved retention characteristics. The proposed model can plausibly explain both the electroformed and the electroforming-free devices. Therefore, it can be a standard model for valence change memristors.N

An Amiable Design of Cobalt Single Atoms as the Active Sites for Oxygen Evolution Reaction in Desalinated Seawater

Green fuel from water splitting is hardcore for future generations, and the limited source of fresh water (<1%) is a bottleneck. Seawater cannot be used directly as a feedstock in current electrolyzer techniques. Until now single atom catalysts were reported by many synthetic strategies using notorious chemicals and harsh conditions. A cobalt single-atom (CoSA) intruding cobalt oxide ultrasmall nanoparticle (Co3O4 USNP)-intercalated porous carbon (PC) (CoSA-Co3O4@PC) electrocatalyst was synthesized from the waste orange peel as a single feedstock (solvent/template). The extended X-ray absorption fine structure spectroscopy (EXAFS) and theoretical fitting reveal a clear picture of the coordination environment of the CoSA sites (CoSA-Co3O4 and CoSA-N4 in PC). To impede the direct seawater corrosion and chlorine evolution the seawater has been desalinated (Dseawater) with minimal cost and the obtained PC is used as an adsorbent in this process. CoSA-Co3O4@PC shows high oxygen evolution reaction (OER) activity in transitional metal impurity-free (TMIF) 1 M KOH and alkaline Dseawater. CoSA-Co3O4@PC exhibits mass activity that is 15 times higher than the commercial RuO2. Theoretical interpretations suggest that the optimized CoSA sites in Co3O4 USNPs reduce the energy barrier for alkaline water dissociation and simultaneously trigger an excellent OER followed by an adsorbate evolution mechanism (AEM)