Learning Symmetric Rules with SATNet

SATNet is a differentiable constraint solver with a custom backpropagation algorithm, which can be used as a layer in a deep-learning system. It is a promising proposal for bridging deep learning and logical reasoning. In fact, SATNet has been successfully applied to learn, among others, the rules of a complex logical puzzle, such as Sudoku, just from input and output pairs where inputs are given as images. In this paper, we show how to improve the learning of SATNet by exploiting symmetries in the target rules of a given but unknown logical puzzle or more generally a logical formula. We present SymSATNet, a variant of SATNet that translates the given symmetries of the target rules to a condition on the parameters of SATNet and requires that the parameters should have a particular parametric form that guarantees the condition. The requirement dramatically reduces the number of parameters to learn for the rules with enough symmetries, and makes the parameter learning of SymSATNet much easier than that of SATNet. We also describe a technique for automatically discovering symmetries of the target rules from examples. Our experiments with Sudoku and Rubik's cube show the substantial improvement of SymSATNet over the baseline SATNet.Comment: 27 pages, 10 figures, the first two authors contributed equally to this work, accepted at NeurIPS'2

Microphone Conversion: Mitigating Device Variability in Sound Event Classification

In this study, we introduce a new augmentation technique to enhance the resilience of sound event classification (SEC) systems against device variability through the use of CycleGAN. We also present a unique dataset to evaluate this method. As SEC systems become increasingly common, it is crucial that they work well with audio from diverse recording devices. Our method addresses limited device diversity in training data by enabling unpaired training to transform input spectrograms as if they are recorded on a different device. Our experiments show that our approach outperforms existing methods in generalization by 5.2% - 11.5% in weighted f1 score. Additionally, it surpasses the current methods in adaptability across diverse recording devices by achieving a 6.5% - 12.8% improvement in weighted f1 score.Comment: Accepted to ICASSP 202

On the Consideration of AI Openness: Can Good Intent Be Abused?

Openness is critical for the advancement of science. In particular, recent rapid progress in AI has been made possible only by various open-source models, datasets, and libraries. However, this openness also means that technologies can be freely used for socially harmful purposes. Can open-source models or datasets be used for malicious purposes? If so, how easy is it to adapt technology for such goals? Here, we conduct a case study in the legal domain, a realm where individual decisions can have profound social consequences. To this end, we build EVE, a dataset consisting of 200 examples of questions and corresponding answers about criminal activities based on 200 Korean precedents. We found that a widely accepted open-source LLM, which initially refuses to answer unethical questions, can be easily tuned with EVE to provide unethical and informative answers about criminal activities. This implies that although open-source technologies contribute to scientific progress, some care must be taken to mitigate possible malicious use cases. Warning: This paper contains contents that some may find unethical.Comment: 10 page

Photocatalytic Hydrogen Evolution from Sub-Stoichiometric Colloidal WO3-xNanowires

We report direct photocatalytic hydrogen evolution from substoichiometric highly reduced tungsten oxide (WOx) nanowires (NWs) using sacrificial alcohol. WOx NWs are synthesized via nonaqueous colloidal synthesis with a diameter of about 4 nm and an average length of about 250 nm. As-synthesized WOx NWs exhibit a broad absorption across the visible to infrared regions attributed to the presence of oxygen vacancies. The optical band gap is increased in these WOx NWs compared to stoichiometric bulk tungsten oxide (WO3) powders as a result of the Burstein\u2013Moss shift. As a consequence of this increase, we demonstrate direct photocatalytic hydrogen production from WOx NWs through alcohol photoreforming. The stable H2 evolution on platinized WOx NWs is observed under conditions in which platinized bulk WO3 and bulk WO2.9 powders either do not show activity or show very low rates, suggesting that increased surface area and specific exposed facets are key for the improved performance of WOx NWs. This work demonstrates that control of size and composition can lead to unexpected and beneficial changes in the photocatalytic properties of semiconductor materials

Selective context-sensitivity guided by impact pre-analysis

We present a method for selectively applying context-sensitivity during interprocedural program analysis. Our method applies context-sensitivity only when and where doing so is likely to improve the precision that matters for resolving given queries. The idea is to use a pre-analysis to estimate the impact of contextsensitivity on the main analysis’s precision, and to use this information to find out when and where the main analysis should turn on or off its context-sensitivity. We formalize this approach and prove that the analysis always benefits from the pre-analysisguided context-sensitivity. We implemented this selective method for an existing industrial-strength interval analyzer for full C. The method reduced the number of (false) alarms by 24.4%, while increasing the analysis cost by 27.8% on average.The use of the selective method is not limited to contextsensitivity. We demonstrate this generality by following the same principle and developing a selective relational analysis

Synthesis of Atomically Thin h-BN Layers Using BCl3 and NH3 by Sequential-Pulsed Chemical Vapor Deposition on Cu Foil

The chemical vapor deposition of hexagonal boron nitride layers from BCl3 and NH3 is highly beneficial for scalable synthesis with high controllability, yet multiple challenges such as corrosive reaction or by-product formation have hindered its successful demonstration. Here, we report the synthesis of polycrystalline hexagonal boron nitride (h-BN) layers on copper foil using BCl3 and NH3. The sequential pulse injection of precursors leads to the formation of atomically thin h-BN layers with a polycrystalline structure. The relationship between growth temperature and crystallinity of the h-BN film is investigated using transmission electron microscopy and Raman spectroscopy. Investigation on the initial growth mode achieved by the suppression of precursor supply revealed the formation of triangular domains and existence of preferred crystal orientations. The possible growth mechanism of h-BN in this sequential-pulsed CVD is discussed

Characteristics of fever and response to antipyretic therapy in military personnel with adenovirus-positive community-acquired pneumonia

BACKGROUND: In 2014, an outbreak of adenoviral pneumonia occurred in the Korean military training center. However, there are limited data on the characteristics of the fever and its response to antipyretic therapy in immunocompetent adults with adenovirus-positive community-acquired pneumonia (CAP). METHODS: The medical records of the patients who were admitted to the Armed Forces Chuncheon Hospital for the treatment of CAP between January 2014 and December 2016 were retrospectively analyzed. The patients were divided into three groups, namely, the adenovirus-positive (Adv) group, the adenovirus-negative (Non-Adv) group and the unknown pathogen group, according to the results of a polymerase chain reaction (PCR) test and sputum culture used to measure adenovirus and other bacteria or viruses in respiratory specimens. We evaluated and compared the demographics, clinicolaboratory findings and radiological findings upon admission between the two groups. RESULTS: Out of the 251 military personnel with CAP during the study periods, 67 were classified into the Adv group, while 134 were classified into the Non-Adv group and 50 were classified into the unknown pathogen group. The patients in the Adv group had a longer duration of fever after admission (3.2 ± 1.6 vs. 1.9 ± 1.2 vs. 2.2 ± 1.5 days, P = 0.018) and symptom onset (5.8 ± 2.2 vs. 3.9 ± 2.5 vs. 3.7 ± 2.0 days, P = 0.006) than patients in the Non-Adv and unknown pathogen groups, respectively. The patients in the Adv group had a higher mean temperature at admission (37.8 ± 0.3 vs. 37.3 ± 0.3 vs. 37.3 ± 0.3, P = 0.005), and more patients were observed over 40 and 39 to 40(14.9% vs. 2.2% vs. 4.0%, 35.8% vs. 3.7% vs. 6.0%, P <  0.001) than those in the Non-Adv and unknown pathogen groups, respectively. The Adv group more commonly had no response or exhibited adverse events after antipyretic treatment compared to the Non-Adv group (17.9% vs. 1.5%, 35.0% vs. 4.3%, P <  0.001, P = 0.05, respectively). In addition, the time from admission to overall clinical stabilization was significantly longer in the patients in the Adv group than in those in the Non-Adv group (4.3 ± 2.8 vs. 2.9 ± 1.8 days, P = 0.034, respectively). Furthermore, no significant difference in the length of hospital stay was observed between the two groups, and no patient died in either group. CONCLUSION: In this study, Adv-positive CAP in immunocompetent military personnel patients had distinct fever characteristics and responses to antipyretic treatment

Physics-Based Device Models and Progress Review for Active Piezoelectric Semiconductor Devices

Piezoelectric devices transduce mechanical energy to electrical energy by elastic deformation, which distorts local dipoles in crystalline materials. Amongst electromechanical sensors, piezoelectric devices are advantageous because of their scalability, light weight, low power consumption, and readily built-in amplification and ability for multiplexing, which are essential for wearables, medical devices, and robotics. This paper reviews recent progress in active piezoelectric devices. We classify these piezoelectric devices according to the material dimensionality and present physics-based device models to describe and quantify the piezoelectric response for one-dimensional nanowires, emerging two-dimensional materials, and three-dimensional thin films. Different transduction mechanisms and state-of-the-art devices for each type of material are reviewed. Perspectives on the future applications of active piezoelectric devices are discussed