GPS-GLASS: Learning Nighttime Semantic Segmentation Using Daytime Video and GPS data

Semantic segmentation for autonomous driving should be robust against various in-the-wild environments. Nighttime semantic segmentation is especially challenging due to a lack of annotated nighttime images and a large domain gap from daytime images with sufficient annotation. In this paper, we propose a novel GPS-based training framework for nighttime semantic segmentation. Given GPS-aligned pairs of daytime and nighttime images, we perform cross-domain correspondence matching to obtain pixel-level pseudo supervision. Moreover, we conduct flow estimation between daytime video frames and apply GPS-based scaling to acquire another pixel-level pseudo supervision. Using these pseudo supervisions with a confidence map, we train a nighttime semantic segmentation network without any annotation from nighttime images. Experimental results demonstrate the effectiveness of the proposed method on several nighttime semantic segmentation datasets. Our source code is available at https://github.com/jimmy9704/GPS-GLASS.Comment: ICCVW 202

On Monotonic Aggregation for Open-domain QA

Question answering (QA) is a critical task for speech-based retrieval from knowledge sources, by sifting only the answers without requiring to read supporting documents. Specifically, open-domain QA aims to answer user questions on unrestricted knowledge sources. Ideally, adding a source should not decrease the accuracy, but we find this property (denoted as "monotonicity") does not hold for current state-of-the-art methods. We identify the cause, and based on that we propose Judge-Specialist framework. Our framework consists of (1) specialist retrievers/readers to cover individual sources, and (2) judge, a dedicated language model to select the final answer. Our experiments show that our framework not only ensures monotonicity, but also outperforms state-of-the-art multi-source QA methods on Natural Questions. Additionally, we show that our models robustly preserve the monotonicity against noise from speech recognition. We publicly release our code and setting.Comment: INTERSPEECH 2023 Camera Read

Efficient Conversion Method from Arithmetic to Boolean Masking in Constrained Devices

A common technique employed for preventing a side channel analysis is boolean masking. However, the application of this scheme is not so straightforward when it comes to block ciphers based on Addition-Rotation-Xor structure. In order to address this issue, since 2000, scholars have investigated schemes for converting Arithmetic to Boolean (AtoB) masking and Boolean to Arithmetic (BtoA) masking schemes. However, these solutions have certain limitations. The time performance of the AtoB scheme is extremely unsatisfactory because of the high complexity of $\mathcal{O}(k)$ where $k$ is the size of addition bit. At the FSE 2015, an improved algorithm with time complexity $\mathcal{O}(\log k)$ based on the Kogge-Stone carry look-ahead adder was suggested. Despite its efficiency, this algorithm cannot consider for constrained environments. Although the original algorithm naturally extends to low-resource devices, there is no advantage in time performance; we call this variant as the generic variant. In this study, we suggest an enhanced variant algorithm to apply to constrained devices. Our solution is based on the principle of the Kogge-Stone carry look-ahead adder, and it uses a divide and conquer approach. In addition, we prove the security of our new algorithm against first-order attack. In implementation results, when $k=64$ and the register bit size of a chip is $8$, $16$ or $32$, we obtain $58$\%, $72$\%, or $68$\% improvement, respectively, over the results obtained using the generic variant. When applying those algorithms to first-order SPECK, we also achieve about $40$\% improvement. Moreover, our proposal extends to higher-order countermeasures as previous study

Integrative Literature Review on the Antecedents of Informal Learning in the Workplace: A Conceptual Framework for Future Research

Despite the explosion of interest in informal learning in the workplace, few attempts have been made to synthesize the current literature. This article provides an integrative and analytical review of prior empirical studies, particularly focusing on what factors have been identified as antecedents of informal learning in organizations and how informal learning has been conceptualized and measured. It then suggests future avenues for theory building, research, and practice. The authors propose a conceptual framework for understanding informal learning activities using three dimensions: learning competence, intentionality, and developmental relatedness. Implications for human resource development research and practice are also discussed

The Rhizome Mixture of Anemarrhena asphodeloides

We investigated the effect of DWac on the gut microbiota composition in mice with 2,3,6-trinitrobenzenesulfonic acid- (TNBS-) induced colitis. Treatment with DWac restored TNBS-disturbed gut microbiota composition and attenuated TNBS-induced colitis. Moreover, we examined the effect of DWac in mice with mesalazine-resistant colitis (MRC). Intrarectal injection of TNBS in MRC mice caused severe colitis, as well as colon shortening, edema, and increased myeloperoxidase activity. Treatment with mesalazine (30 mg/kg) did not attenuate TNBS-induced colitis in MRC mice, whereas treatment with DWac (30 mg/kg) significantly attenuated TNBS-induced colitis. Moreover, treatment with the mixture of mesalazine (15 mg/kg) and DWac (15 mg/kg) additively attenuated colitis in MRC mice. Treatment with DWac and its mixture with mesalazine inhibited TNBS-induced activation of NF-κB and expression of M1 macrophage markers but increased TNBS-suppressed expression of M2 macrophage markers. Furthermore, these inhibited TNBS-induced T-bet, RORγt, TNF-α, and IL-17 expression but increased TNBS-suppressed Foxp3 and IL-10 expression. However, Th2 cell differentiation and GATA3 and IL-5 expression were not affected. These findings suggest that DWac can ameliorate MRC by increasing the polarization of M2 macrophage and correcting the disturbance of gut microbiota and Th1/Th17/Treg, as well as additively attenuating MRC along with mesalazine

Biodegradable, flexible silicon nanomembrane-based NO x gas sensor system with record-high performance for transient environmental monitors and medical implants

Abstract: A novel transient electronics technology that is capable of completely dissolving or decomposing in certain conditions after a period of operation offers unprecedented opportunities for medical implants, environmental sensors, and other applications. Here, we describe a biodegradable, flexible silicon-based electronic system that detects NO species with a record-breaking sensitivity of 136 Rs (5 ppm, NO2) and 100-fold selectivity for NO species over other substances with a fast response (~30 s) and recovery (~60 s). The exceptional features primarily depend on not only materials, dimensions, and design layouts but also temperatures and electrical operations. Large-scale sensor arrays in a mechanically pliable configuration exhibit negligible deterioration in performance under various modes of applied loads, consistent with mechanics modeling. In vitro evaluations demonstrate the capability and stability of integrated NOx devices in severe wet environments for biomedical applications

Young age: an independent risk factor for disease-free survival in women with operable breast cancer

BACKGROUND: The incidence of breast cancer in young women (age < 35) is low. The biology of the disease in this age group is poorly understood, and there are conflicting data regarding the prognosis for these women compared to older patients. METHODS: We retrospectively analyzed 2040 consecutive primary invasive breast cancer patients who underwent surgical procedures at our institution between 1990 and 1999. The younger age group was defined as patients aged <35 years at the time of diagnosis. The clinicopathological characteristics and treatment outcomes were compared between younger and older age groups. RESULTS: A total of 256 (12.5%) patients were aged <35. There was a significantly higher incidence of nuclear grade 3 and medullary histological-type tumors in younger patients compared to older patients. Axillary lymph node status, T stage, histological grade, c-erbB2 expression and estrogen receptor status did not differ significantly between the two age groups. Younger patients had a greater probability of recurrence and death at all time periods. Although there was no significant difference in disease-free survival between the two age groups in lymph node-negative patients, the younger group showed worse prognosis among lymph node-positive patients (p < 0.001). In multivariate analysis, young age remained a significant predictor of recurrence (p = 0.010). CONCLUSION: Young age (<35) is an independent risk factor for relapse in operable breast cancer patients