Reliable Decision from Multiple Subtasks through Threshold Optimization: Content Moderation in the Wild

Social media platforms struggle to protect users from harmful content through content moderation. These platforms have recently leveraged machine learning models to cope with the vast amount of user-generated content daily. Since moderation policies vary depending on countries and types of products, it is common to train and deploy the models per policy. However, this approach is highly inefficient, especially when the policies change, requiring dataset re-labeling and model re-training on the shifted data distribution. To alleviate this cost inefficiency, social media platforms often employ third-party content moderation services that provide prediction scores of multiple subtasks, such as predicting the existence of underage personnel, rude gestures, or weapons, instead of directly providing final moderation decisions. However, making a reliable automated moderation decision from the prediction scores of the multiple subtasks for a specific target policy has not been widely explored yet. In this study, we formulate real-world scenarios of content moderation and introduce a simple yet effective threshold optimization method that searches the optimal thresholds of the multiple subtasks to make a reliable moderation decision in a cost-effective way. Extensive experiments demonstrate that our approach shows better performance in content moderation compared to existing threshold optimization methods and heuristics.Comment: WSDM2023 (Oral Presentation

Atomic Scale Study on Growth and Heteroepitaxy of ZnO Monolayer on Graphene

Atomically thin semiconducting oxide on graphene carries a unique combination of wide band gap, high charge carrier mobility, and optical transparency, which can be widely applied for optoelectronics. However, study on the epitaxial formation and properties of oxide monolayer on graphene remains unexplored due to hydrophobic graphene surface and limits of conventional bulk deposition technique. Here, we report atomic scale study of heteroepitaxial growth and relationship of a single-atom-thick ZnO layer on graphene using atomic layer deposition. We demonstrate atom-by-atom growth of zinc and oxygen at the preferential zigzag edge of a ZnO monolayer on graphene through in situ observation. We experimentally determine that the thinnest ZnO monolayer has a wide band gap (up to 4.0 eV), due to quantum confinement and graphene-like structure, and high optical transparency. This study can lead to a new class of atomically thin two-dimensional heterostructures of semiconducting oxides formed by highly controlled epitaxial growth.ope

Investigation on Formation of Metals and Metal Oxides on Two-Dimensional Carbon Materials

Department of Materials Science and EngineeringDiscovery of low dimensional materials is attracting various interest in research filed. As a feature, surface properties and quantum size effects are dominated due to two-dimensional (2D) space constraints. These features lead to excellent electronic, optical, thermal, mechanical, and chemical properties that can be used in a wide range of nanotechnology. Particularly, graphene leads the study of 2D materials with the discovery of a method for manufacturing materials in the late 2000s. Nowadays, a lot of new 2D materials such as hexagonal boron nitride, transition metal dichalcogenide, black phosphorene, and 2D metal oxide are found and widely studied. With advancement of nanotechnology and the integration of technology, importance of research on combination of 2D materials and conventional materials is emerging. Based on this issue, this work mainly focuses on formation of thin metals and metal oxides on 2D carbon materials including graphene, graphene oxide and nanocrystalline graphene (nc-G). From study for metal formation on pristine monolayer graphene and nc-G, effect of surface structure of graphene and adsorbate on the surface on the formation of metallic materials on graphene is investigated. It is observed that the influence of the graphene surface structure on formation of metal materials is insignificant but in situ heating experiments shows behavior of deposited metals are different with substrate. By analyzing the adsorbate on graphene, I reveal that metal oxide can be formed at interface between metal and graphene, and crystallinity of the formed metal thin film is affected by amount of the adsorbates. Study of metal on graphene oxide reveals possibility of graphene oxide as solid oxygen source and substrate, simultaneously. I report the atomic-scale investigation of a novel self-formation of a ZnO monolayer from Zn metal on a graphene oxide substrate. The spontaneous oxidation of ultra-thin Zn metal occurs by reaction with oxygen supplied from the graphene oxide substrate and graphene oxide is deoxygenated by a transfer of oxygen from O-containing functional groups to zinc metal. Finally, atomically thin aluminum oxide is analyzed by deposition on graphene through atomic layer deposition. The aluminum oxide formed on graphene is in an amorphous state, but crystallization of aluminum oxide under electron beam and in situ heating experiment are observed by atomic-resolution transmission electron microscopy analysis. These studies allow us to reveal a structural, chemical changes of metal and metal oxide formation on 2D carbon materials from atomic-scale to micro-scale.clos

DSP: Distill the Knowledge Only By a Subset of Patches

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Differentiated Protection and Hot/Cold-Aware Data Placement Policies through k-Means Clustering Analysis for 3D-NAND SSDs

3D-NAND flash memory provides high capacity per unit area by stacking 2D-NAND cells having a planar structure. However, because of the nature of the lamination process, the frequency of error occurrence varies depending on each layer or physical cell location. This phenomenon becomes more pronounced as the number of flash memory write/erase (Program/Erasure) operations increases. Error correction code (ECC) is used for error correction in the majority of flash-based storage devices, such as SSDs (Solid State Drive). As this method provides a constant level of data protection for all-flash memory pages, there is a limitation in 3D-NAND flash memory, where the error rate varies depending on physical location. Consequently, in this paper, pages and layers with varying error rates are classified into clusters using the k-means machine-learning algorithm, and each cluster is assigned a different level of data protection strength. We classify pages and layers based on the number of error occurrences measured at the end of the endurance test, and for areas vulnerable to errors, it is shown as an example of providing differentiated data protection strength by adding parity data to the stripe. Furthermore, areas vulnerable to retention errors are identified based on retention error rates, and bit error rates are significantly reduced through our hot/cold-aware data placement policy. We show that the proposed differential data protection and hot/cold-aware data placement policies improve the reliability and lifespan of 3D-NAND flash memory compared with the existing ECC- or RAID-type data protection scheme

Study on microstructure and mechanical properties of boron added carbon steel joint by laser-arc hybrid welding

Boron added carbon steels show excellent properties such as hardenability. It is known that boron segregates at proeutectic austenite grain boundaries and prevent the austenite transformation to ferrite. As a result, martensitic transformation is promoted during cooling and shows high hardness than general carbon steels. Segregation behavior of boron in steel is affected by process conditions such as austenization temperature and cooling rate. It implies the welding process condition can also extremely affect to segregation behavior of boron. Among the welding processes, an arc welding and a laser welding are common in the field. The arc welding process is easy and convenient when an object is thick, but it has demerits when an object is thin because of its large fusion area. On the other hand, the laser welding process has merits of deep fusion depth and fast welding speed. Because of these merits and demerits of welding processes, industrial field tried to combine the arc and the laser welding processes as hybrid welding. The hybrid welding process has unique heat source model different from existing welding processes, it can show unpredictable results such as phase transformation and precipitation of impurities. We observed how boron and other impurities behave in carbon steels under the hybrid welding process using transmission electron microscopy and scanning electron microscopy. Finally, we analyzed mechanical properties related to the behavior of specific elements