Clustering biomedical and gene expression datasets with kernel density and unique neighborhood set based vein detection

It is a crucial need for a clustering technique to produce high-quality clusters from biomedical and gene expression datasets without requiring any user inputs. Therefore, in this paper we present a clustering technique called KUVClust that produces high-quality clusters when applied on biomedical and gene expression datasets without requiring any user inputs. The KUVClust algorithm uses three concepts namely multivariate kernel density estimation, unique closest neighborhood set and vein-based clustering. Although these concepts are known in the literature, KUVClust combines the concepts in a novel manner to achieve high-quality clustering results. The performance of KUVClust is compared with established clustering techniques on real-world biomedical and gene expression datasets. The comparisons were evaluated in terms of three criteria (purity, entropy, and sum of squared error (SSE)). Experimental results demonstrated the superiority of the proposed technique over the existing techniques for clustering both the low dimensional biomedical and high dimensional gene expressions datasets used in the experiments.     

Systematic packaging design tools integrating functional and environmental consequences on product life cycle: Case studies on laundry detergent and milk

This study presents systematic packaging design tools integrating functional and environmental consequences on product life cycle. To design packaging for sustainability, the trade-offs between functional and environmental aspects of packaging throughout the product life cycle should be considered. However, it is difficult for packaging designers to understand the overall trade-offs because the extent of the design consequences on the entire life cycle of packaging and its contents is unclear. We developed two tools for packaging design: the Life Cycle Association Matrix (LCAM) and the Function Network Diagram (FND). The following three steps, based on literature reviews and interviews with industrial experts, were applied. Firstly, we listed the product functions and design variables related to the functions as the attributes allocated to the product life cycle. Secondly, the attributes were connected appropriately based on causal relationships. Lastly, we identified the factors to support decision making in the packaging design procedure. As a result, the LCAM depicts the design consequences on the life cycle, and the FND determines the stakeholders affected by the design consequences. Two case studies were demonstrated to analyze the trade-offs by using our tools. In the case studies, a liquid laundry detergent bottle and a milk carton were redesigned. The tools identified the design consequences and stakeholders affected by the redesign of the usability and protective function for the detergent and milk cases, respectively. The results showed the significance of understanding the design consequences on the product life cycle by integrating the functional and environmental aspects.     

Sensor fault estimation of PEM fuel cells using Takagi Sugeno fuzzy model

This paper presents a sensor fault estimation scheme for polymer electrolyte membrane (PEM) fuel cells using Takagi Sugeno (TS) fuzzy model. First, PEM fuel cell systems with sensor faults are modelled by TS fuzzy model. Next, by adding a first order filter, an augmented TS fuzzy system with actuator fault is obtained. Then, for the augmented system, an unknown input observer (UIO) and a fault estimator are developed. The UIO gains are computed by solving linear matrix equalities (LMEs) and linear matrix inequalities (LMIs). The UIO convergence and stability are analyzed and the performances of the proposed fault estimation scheme is demonstrated by numerical simulations for a PEM fuel cell system with return manifold pressure and hydrogen mass sensors.     

Anti‐Sway Crane Control Considering Wind Disturbance and Container Mass

A method for estimating the sway angle using an observer has already been proposed. The state observer estimates the sway angle accurately and must use the detected sway angle value. However, the estimated sway angle has an error owing to rope length error, friction force, and wind. Moreover, the container mass cannot be determined, and therefore the observer parameter is not suitable. We already proposed robust antisway control for overcoming rope length error without adding a new sensor. Further, we designed a friction disturbance observer to cancel out the influence of the friction force. In this paper, we first propose a container mass estimation method when a crane system performs rolling up control. The observer parameter can be selected using the estimated mass value. Second, in crane parallel shift control, we propose a robust antisway control even when there is a wind disturbance. We design a wind disturbance observer and propose a wind disturbance estimator to separate the friction observer output from the wind disturbance observer output. We confirm through experiments that the proposed method can reduce vibration.     

Active packaging solution to prolong the shelf life of rocket salad

The best packaging conditions for rocket salad were assessed by subsequent experimental trials. In the first step, a preliminary screening of different packaging materials was performed and two micro‐perforated oriented polypropylene films with different micro‐hole diameters (90 and 110 μm) were selected as best packaging solutions. In the subsequent experimental step, modified headspace conditions were applied without any improvement on product quality. In the last step, the effects of an ethylene adsorbent were analysed. Rocket salad packaged in both films with the ethylene adsorbent recorded a shelf life of about 16 days, compared to the control samples that remained acceptable for 13 days. During storage, the microbial quality (mesophilic and psychrotrophic bacteria, pseudomonadaceae, lactic acid bacteria, yeasts, total coliforms and enterobacteriacae), the pH, the colour changes and the main sensory parameters were also monitored.     

Power system state estimation using a direct non-iterative method

This paper describes a new method for state estimation of a non-linear AC power system in a non-iterative manner. This method is based on the Kipnis–Shamir relinearization technique that is used to solve over-defined sets of polynomial equations. The technique transforms the equations to a higher dimensional linear space which allows the states to be solved in a non-iterative manner. Given accurate measurements, this new state estimation method provides the same results as traditional iterative state estimation methods, and the proposed method does not require an initial guess of system states nor does it have issues with convergence.     

Effect of chitosan on Bacillus cereus inhibition and quality of cooked rice during storage

Improper cooling of cooked rice at an inappropriate temperature or leaving cooked rice at room temperature can cause food poisoning attributed to Bacillus cereus. Natural food preservative of either squid or crab polymer chitosan solution was added to examine their antibacterial properties against Bacillus cereus in cooked rice during storage at 37 and 4 °C. Both types of chitosan could retard the growth of B. cereus and total aerobic counts in cooked rice stored at 37 °C up to 1 day. In addition, the effect of chitosans on the physical and textural properties of cooked rice during storage was studied. Both chitosans slightly increased the moisture content of cooked rice. However, chitosans had no effect on the whiteness and hardness of cooked rice during storage (P > 0.05). Therefore, both chitosans have a potential to be used as food preservative for cooked rice with no negative effects on rice quality.     

Robust energy-to-peak sideslip angle estimation with applications to ground vehicles

In this paper, the observer design problem for the sideslip angle of ground vehicles is investigated. The sideslip angle is an important signal for the vehicle lateral stability, which is not measurable by using an affordable physical sensor. Therefore, we aim to estimate the sideslip angle with the yaw rate measurements by employing the vehicle dynamics. The nonlinear lateral dynamics is modeled firstly. As the tyre model is nonlinear and the road adhesive coefficient is subject to a large variation, the nonlinear lateral dynamics is transformed into an uncertain model. Considering the variation of longitudinal velocity, an uncertain linear-parameter-varying (LPV) system is obtained. Based on the LPV model, a gain-scheduling observer is proposed and the observer gain can be determined with off-line computation and on-line computation. The off-line computation includes the calculation of a set of linear matrix inequalities and the on-line computation contains several algebraic operations. The proposed design methodology is applied to a four-wheel-independent-drive electric vehicle in simulation. It infers from different maneuvers that the designed observer has a good performance on estimating the sideslip angle.     

定子扇形片复合模设计

分析零件自身的特点和成形难点,针对成形难点制定相应的解决对策,结合类似模具在以往设计、加工、组装、使用和维护过程中遇到的问题,对定子扇形片复合模设计难点的解决方法及相关注意事项分别进行了介绍,模具经多次调试已顺利投入生产,对类似零件的模具设计具有一定的参考作用。     

Backtesting portfolio value-at-risk with estimated portfolio weights

This article theoretically and empirically analyzes backtesting portfolio value-at-risk (VaR) with estimation risk in an intrinsically multi-variate framework. It particularly takes into account the estimation of portfolio weights in forecasting portfolio VaR and its impact on backtesting. It shows that the estimation risk from estimating portfolio weights and that from estimating the multi-variate dynamic model make the existing methods in a univariate framework inapplicable. It proposes a general theory to quantify estimation risk applicable to the present problem and suggests practitioners a simple but effective way to implement valid inference to overcome the effect of estimation risk in backtesting portfolio VaR. In particular, we apply our theory to the efficient mean-variance-skewness portfolio for a multi-variate generalized autoregressive conditional heteroscedasticity model with multi-variate general hyperbolic distributed innovations. Some Monte Carlo simulations and an empirical application demonstrate the merits of our method.