Detection of Sensor Attack and Resilient State Estimation for Uniformly Observable Nonlinear Systems having Redundant Sensors

This paper presents a detection algorithm for sensor attacks and a resilient state estimation scheme for a class of uniformly observable nonlinear systems. An adversary is supposed to corrupt a subset of sensors with the possibly unbounded signals, while the system has sensor redundancy. We design an individual high-gain observer for each measurement output so that only the observable portion of the system state is obtained. Then, a nonlinear error correcting problem is solved by collecting all the information from those partial observers and exploiting redundancy. A computationally efficient, on-line monitoring scheme is presented for attack detection. Based on the attack detection scheme, an algorithm for resilient state estimation is provided. The simulation results demonstrate the effectiveness of the proposed algorithm

Acid Sphingomyelinase Regulates the Localization and Trafficking of Palmitoylated Proteins

In human, loss of Acid Sphingomeylinase (ASM/SMPD1) causes Niemann-Pick Disease, type A. ASM hydrolyzes sphingomyelins to produce ceramides but protein targets of ASM remain largely unclear. ... See full text for complete abstract

Association of Dietary Total Antioxidant Capacity with Bone Mass and Osteoporosis Risk in Korean Women: Analysis of the Korea National Health and Nutrition Examination Survey 2008-2011

Antioxidant intake has been suggested to be associated with a reduced osteoporosis risk, but the effect of dietary total antioxidant capacity (TAC) on bone health and the risk of osteoporosis remains unclear. We aimed to assess the hypothesis that dietary TAC is positively associated with bone mass and negatively related to the risk of osteoporosis in Korean women. This cross-sectional study was performed using data from the Korea National Health and Nutrition Examination Survey. Dietary TAC was estimated using task automation and an algorithm with 24-h recall data. In total, 8230 pre-and postmenopausal women were divided into four groups according to quartiles of dietary TAC. Dietary TAC was negatively associated with the risk of osteoporosis (odds ratio, 0.73; 95% confidence interval, 0.54–0.99; p-value = 0.045) in postmenopausal women, but not in premenopausal women. Dietary TAC was positively associated with bone mineral content (BMC) and bone mineral density of the femoral neck and lumbar spine in postmenopausal women and BMC of the total femur and lumbar spine in premenopausal women. Our study suggests that dietary TAC is inversely associated with the risk of osteoporosis in postmenopausal women and positively associated with bone mass in both pre-and postmenopausal women

Dynamic Vehicular Route Guidance Using Traffic Prediction Information

We propose a dynamic vehicular routing algorithm with traffic prediction for improved routing performance. The primary idea of our algorithm is to use real-time as well as predictive traffic information provided by a central routing controller. In order to evaluate the performance, we develop a microtraffic simulator that provides road networks created from real maps, routing algorithms, and vehicles that travel from origins to destinations depending on traffic conditions. The performance is evaluated by newly defined metric that reveals travel time distributions more accurately than a commonly used metric of mean travel time. Our simulation results show that our dynamic routing algorithm with prediction outperforms both Static and Dynamic without prediction routing algorithms under various traffic conditions and road configurations. We also include traffic scenarios where not all vehicles comply with our dynamic routing with prediction strategy, and the results suggest that more than half the benefit of the new routing algorithm is realized even when only 30% of the vehicles comply

A Novel Mitigation Method for Noise-Induced Temperature Error in CPU Thermal Control

It has been reported that in the thermal control of real-time computing systems, zero-mean thermal sensor noise can induce a significant steady-state error between the target and actual temperatures of a CPU. Unlike the usual case of zero-mean sensor noise resulting in zero-mean temperature fluctuations around the target value, this noise-induced temperature error manifests in the form of a bias, i.e., the mean of the error is not zero. Existing work has analyzed the main cause of this error and produced a solution, known as TCUB-VS. However, this existing solution has a few drawbacks: the transient response is sluggish, and the exact value of the noise standard deviation is necessary in the design stage. In this paper, we propose a novel method of avoiding noise-induced temperature error while overcoming the limitations of the existing work. The proposed method uses an estimated CPU temperature for the part of the controller that is sensitive to noise while using actual measurements for the other part of the controller. In this way, our proposed method eliminates noise-induced temperature error and overcomes the drawbacks of the existing work. To show the efficacy of our proposed method, theoretical results are obtained using a stochastic averaging approach, and experimental results are presented along with simulations.1

Continuous productivity improvement using ioe data for fault monitoring: An automotive parts production line case study

This paper presents a case study of continuous productivity improvement of an automotive parts production line using Internet of Everything (IoE) data for fault monitoring. Continuous productivity improvement denotes an iterative process of analyzing and updating the production line configuration for productivity improvement based on measured data. Analysis for continuous improvement of a production system requires a set of data (machine uptime, downtime, cycle-time) that are not typically monitored by a conventional fault monitoring system. Although productivity improvement is a critical aspect for a manufacturing site, not many production systems are equipped with a dedicated data recording system towards continuous improvement. In this paper, we study the problem of how to derive the dataset required for continuous improvement from the measurement by a conventional fault monitoring system. In particular, we provide a case study of an automotive parts production line. Based on the data measured by the existing fault monitoring system, we model the production system and derive the dataset required for continuous improvement. Our approach provides the expected amount of improvement to operation managers in a numerical manner to help them make a decision on whether they should modify the line configuration or not. © 2021 by the authors. Licensee MDPI, Basel, Switzerland.1

Association between diet and gallstones of cholesterol and pigment among patients with cholecystectomy: a case-control study in Korea

Background: The prevalence of cholesterol gallstones is high in Western populations, while pigment gallstones are common in Asian populations. Dietary factors are suggested to be associated with gallstone risk, but their relationship with gallstone type has not been evaluated. This study investigated the association between diet and risk of cholesterol gallstone or pigment gallstone in a Korean population whose dietary pattern and type of gallstone were changed during the last 30 years. Methods: Patients with cholesterol (n = 40) and pigment (n = 59) gallstones were recruited after laparoscopic cholecystectomy and were compared with those of age- and sex-matched controls without gallstones (n = 99). Dietary intakes were assessed by trained dietitians using a semi-quantitative food frequency questionnaire. Multinomial logistic regression analysis was performed to calculate odds ratios and 95% confidence intervals to examine the associations between diet and risk for type of gallstones adjusted by potential confounders. Results: Patients with cholesterol gallstone consumed more lipid, animal lipid, beef, pork, and fried food than those with pigment gallstones and control, while patients with pigment gallstone consumed more carbohydrate and noodles than patients with cholesterol gallstone and control. In multinomial logistic regression analysis using control as reference group, dietary pattern with high consumption of beef, pork, and fried food was associated with risk of cholesterol gallstones, while there was no association between the risk of pigment gallstone and dietary pattern. In addition, control consumed more alcohol than patients with cholesterol and pigment gallstones. Conclusions: The present study suggested consumption of fat from meat and fried foods increased the risk of cholesterol gallstone, and intake of carbohydrate from noodles increased the risk of pigment gallstone