Vector Quantized Bayesian Neural Network Inference for Data Streams

Bayesian neural networks (BNN) can estimate the uncertainty in predictions, as opposed to non-Bayesian neural networks (NNs). However, BNNs have been far less widely used than non-Bayesian NNs in practice since they need iterative NN executions to predict a result for one data, and it gives rise to prohibitive computational cost. This computational burden is a critical problem when processing data streams with low-latency. To address this problem, we propose a novel model VQ-BNN, which approximates BNN inference for data streams. In order to reduce the computational burden, VQ-BNN inference predicts NN only once and compensates the result with previously memorized predictions. To be specific, VQ-BNN inference for data streams is given by temporal exponential smoothing of recent predictions. The computational cost of this model is almost the same as that of non-Bayesian NNs. Experiments including semantic segmentation on real-world data show that this model performs significantly faster than BNNs while estimating predictive results comparable to or superior to the results of BNNs.Comment: AAAI 202

Source signatures from combined isotopic analyses of PM2.5 carbonaceous and nitrogen aerosols at the peri-urban Taehwa Research Forest, South Korea in summer and fall.

Isotopes are essential tools to apportion major sources of aerosols. We measured the radiocarbon, stable carbon, and stable nitrogen isotopic composition of PM2.5 at Taehwa Research Forest (TRF) near Seoul Metropolitan Area (SMA) during August-October 2014. PM2.5, TC, and TN concentrations were 19.4 ± 10.1 μg m-3, 2.6 ± 0.8 μg C m-3, and 1.4 ± 1.4 μg N m-3, respectively. The δ13C of TC and the δ15N of TN were - 25.4 ± 0.7‰ and 14.6 ± 3.8‰, respectively. EC was dominated by fossil-fuel sources with Fff (EC) of 78 ± 7%. In contrast, contemporary sources were dominant for TC with Fc (TC) of 76 ± 7%, revealing the significant contribution of contemporary sources to OC during the growing season. The isotopic signature carries more detailed information on sources depending on air mass trajectories. The urban influence was dominant under stagnant condition, which was in reasonable agreement with the estimated δ15N of NH4+. The low δ15N (7.0 ± 0.2‰) with high TN concentration was apparent in air masses from Shandong province, indicating fossil fuel combustion as major emission source. In contrast, the high δ15N (16.1 ± 3.2‰) with enhanced TC/TN ratio reveals the impact of biomass burning in the air transported from the far eastern border region of China and Russia. Our findings highlight that the multi-isotopic composition is a useful tool to identify emission sources and to trace regional sources of carbonaceous and nitrogen aerosols

Methylsulfonylmethane Suppresses Breast Cancer Growth by Down-Regulating STAT3 and STAT5b Pathways

Breast cancer is the most aggressive form of all cancers, with high incidence and mortality rates. The purpose of the present study was to investigate the molecular mechanism by which methylsulfonylmethane (MSM) inhibits breast cancer growth in mice xenografts. MSM is an organic sulfur-containing natural compound without any toxicity. In this study, we demonstrated that MSM substantially decreased the viability of human breast cancer cells in a dose-dependent manner. MSM also suppressed the phosphorylation of STAT3, STAT5b, expression of IGF-1R, HIF-1α, VEGF, BrK, and p-IGF-1R and inhibited triple-negative receptor expression in receptor-positive cell lines. Moreover, MSM decreased the DNA-binding activities of STAT5b and STAT3, to the target gene promoters in MDA-MB 231 or co-transfected COS-7 cells. We confirmed that MSM significantly decreased the relative luciferase activities indicating crosstalk between STAT5b/IGF-1R, STAT5b/HSP90α, and STAT3/VEGF. To confirm these findings in vivo, xenografts were established in Balb/c athymic nude mice with MDA-MB 231 cells and MSM was administered for 30 days. Concurring to our in vitro analysis, these xenografts showed decreased expression of STAT3, STAT5b, IGF-1R and VEGF. Through in vitro and in vivo analysis, we confirmed that MSM can effectively regulate multiple targets including STAT3/VEGF and STAT5b/IGF-1R. These are the major molecules involved in tumor development, progression, and metastasis. Thus, we strongly recommend the use of MSM as a trial drug for treating all types of breast cancers including triple-negative cancers

Ontology/Data Engineering Based Distributed Simulation Over Service Oriented Architecture For Network Behavior Analysis

As network uses increase rapidly and high quality-of-service (QoS) is required, efficient network managing methods become important. Many previous studies and commercial tools of network management systems such as tcpdump, Ethereal, and other applications have weaknesses: limited size of files, command line execution, and large memory and huge computational power requirement. Researchers struggle to find fast and effective analyzing methods to save maintenance budgets and recover from systematic problems caused by the rapid increment of network traffic or intrusions. The main objective of this study is to propose an approach to deal with a large amount of network behaviors being quickly and efficiently analyzed. We study an ontology/data engineering methodology based network analysis system. We design a behavior, which represents network traffic activity and network packet information such as IP addresses, protocols, and packet length, based on the System Entity Structure (SES) methodology. A significant characteristic of SES, a hierarchical tree structure, enables systems to access network packet information quickly and efficiently. Also, presenting an automated system design is the secondary purpose of this study. Our approach shows adaptive awareness of pragmatic frames (contexts) and makes a network traffic analysis system with high throughput and a fast response time that is ready to respond to user applications. We build models and run simulations to evaluate specific purposes, i.e., analyzing network protocols use, evaluating network throughput, and examining intrusion detection algorithms, based on Discrete Event System Specification (DEVS) formalism. To study speed up, we apply a web-based distributed simulation methodology. DEVS/Service Oriented Architecture (DEVS/SOA) facilitates deploying workloads into multi-servers and consequently increasing overall system performance. In addition to the scalability limitations, both tcpdump and Ethereal have a security issue. As well as basic network traffic information, captured files by these tools contain secure information: user identification numbers and passwords. Therefore, captured files should not allow to be leaked out. However, network analyses need to be performed outside target networks in some cases. The distributed simulation--allocating distributing models inside networks and assigning analyzing models outside networks--also allows analysis of network behaviors out of networks while keeping important information secured

Use of the modular design and wearout parameters to improved high milage reliability of wiper motors

Thesis (M.S.)--Massachusetts Institute of Technology, Dept. of Aeronautics and Astronautics, 1996.by Theodore Taekyu Kim.M.S

Heat Dissipation of Open-Cell-Type Aluminum Foams Manufactured by Replication-Casting Process

Open-cell-type aluminum foam demonstrates excellent heat dissipation owing to interconnected pores. In this study, open-cell-type aluminum foams with various pore sizes and porosities were fabricated using the replication-casting process, which is a relatively simple process. The porosity of the manufactured foams ranged from approximately 55% to 62%. To assess the heat dissipation of the manufactured foams, an air-cooling system was designed. The device could pass a controlled amount of air through the connected pores, simultaneously measuring pressure drop ∆P and temperature changes. It was confirmed that the open-cell-type aluminum foams exhibited a very high cooling rate in the initial cooling phase, and the thermal behavior is influenced by structural characteristics. At a porosity of 62%, the initial maximum cooling rate was measured to be 1.41 ℃/s for a pore size of 0.7~1.0 mm, and it was observed to significantly increase to 3.82 ℃/s for a pore size of 2.8~3.4 mm. Furthermore, for the same pore size, an increase in porosity resulted in an increase in the initial cooling rate. Lager pore sizes and higher porosities led to lower pressure drop ∆P and improved airflow, enhancing the cooling efficiency of open-cell-type aluminum foams