Localized Outlying and Boundary Data Detection in Sensor Networks

Given a set of sparsely distributed sensors in the Euclidean plane, a mobile robot is required to visit all sensors to download the data and finally return to its base. The effective range of each sensor is specified by a disk, and the robot must at least reach the boundary to start communication. The primary goal of optimization in this scenario is to minimize the traveling distance by the robot. This problem can be regarded as a special case of the traveling salesman problem with neighborhoods (TSPN), which is known to be NP-hard. In this paper, we present a novel TSPN algorithm for this class of TSPN, which can yield significantly improved results compared to the latest approximation algorithm.     

A CFD study of hygro–thermal stresses distribution in PEM fuel cell during regular cell operation

A three-dimensional, multi-phase, non-isothermal computational fluid dynamics model of a proton exchange membrane fuel cell has been developed and used to investigate the displacement, deformation, and stresses inside the whole cell, which developed during the cell operation due to the changes of temperature and relative humidity. The behaviour of the fuel cell during operation has been studied and investigated under real cell operating conditions. A unique feature of the present model is to incorporate the effect of hygro and thermal stresses into actual three-dimensional fuel cell model for a complete cell with both the membrane-electrode-assembly and the gas distribution flow channels. The results show that the non-uniform distribution of stresses, caused by the temperature gradient in the cell, induces localized bending stresses, which can contribute to delaminating between the membrane and the gas diffusion layers. The non-uniform distribution of stresses can also contribute to delaminating between the gas diffusion layers and the channels, especially in the cathode side. These stresses may explain the occurrence of cracks and pinholes in the fuel cells components under steady-state loading during regular cell operation, especially in the high loading conditions.     

Effects of osmotic pretreatment and frying conditions on quality and storage stability of vacuum-fried pumpkin chips

The effects of osmotic (OP), ultrasound-assisted osmotic pretreatment (UAOP) and frying conditions on quality and storage stability of vacuum fried pumpkin chips were investigated. The pumpkin samples were pretreated in maltodextrin solution and subsequently fried at different temperatures (90–110 °C) and time periods (10–30 min). The results demonstrated that the moisture content, water activity, lightness, yellowness and carotenoid content of the fried chips decreased, while oil content, hardness and a* (dark brown colour) value increased with increasing frying temperature and time. UAOP reduced about 16.0% of oil absorption and enhanced approximately 70% of carotenoid retention in the fried chips. UAOP samples were also more stable during storage than the untreated ones, indicated by lower degradation kinetics constants of key quality parameters. The proposed pretreatment could be an effective method for food industries to develop vacuum fried pumpkin chips with improved quality and stability.     

Predictive Modeling of Spring Wheat Varieties by Cluster Analysis

Spring wheat varieties were subjected to physico-chemical, mixographic and amino acid analysis. The data obtained was subjected statistically analyzed. The cluster analysis classification based on centroid method indicated that for lysine and overall cookie scores, generally most wheat varieties fell in one group, while for total chapati score most of the wheat varieties were classified into two groups. The wheat varieties falling in same cluster group have similarities in respect of lysine, chapati and cookie quality. This indicated that wheat varieties in Pakistan have narrow ranges of spectrum in their genetic make up for their quality attributes. However, some wheat varieties were distinguished into different groups having a wide distance range especially Shahkar 95 for lysine content, LU 26 and Punjab 96 for cookie quality and Punjnad 88 in case of chapati quality. The present grouping suggests that wheat varieties in cluster group with wider range for lysine content may be used further in a hybridization program to improve the nutritional quality of wheat.     

MAGNETIC FIELD ANALYSIS AND ROUGHNESS PREDICTION IN MAGNETORHEOLOGICAL ABRASIVE HONING (MRAH)

Magnetorheological Abrasive Honing (MRAH) is a recently developed process to finish engineering surfaces. The process makes use of a magnetically stiffened abrasive-mixed magnetorheological fluid as the flexible tool and rotation-cum-reciprocation movements between the finishing medium and the workpiece surface for providing finishing action. In the present work, a finite element analysis with Mechanical/Emag module of ANSYS is performed to understand the nature of magnetic field developed in the process and verification is done with actual measurements. Considering the simulated magnetic field, a model to predict final roughness value (R _a ) is developed. The model, when applied for different work materials and various process parameters, such as magnetic flux density, process duration and workpiece rotation, yields results that are in good agreement with experimental results.     

Aflatoxins: Biosynthesis,Occurrence, Toxicity,and Remedies

Food contagion with aflatoxins is the modern concern and has received a great awareness during the last few decades. The intermittent incidence of these toxins in agricultural commodities has negative role on the economy of the affected regions where harvest and postharvest techniques for the prevention of mold growth, are seldom practiced. Aflatoxins are difuranocoumarin derivatives produced by a polyketide pathway by the fungus Aspergillus flavus and Aspergillus parasiticus via polyketide pathway which are highly hepatotoxic, hepatocarcinogenic, teratogenic, and mutagenic in nature and contaminate a wide variety of important agricultural commodities before, during, and after harvest in various environmental conditions. The production of aflatoxins in innate substrates depends upon the various factors, that is, type of substrate, fungal species, moisture contents of the substrate, minerals, humidity, temperature, and physical damage of the kernels. These toxins cause several ailments such as cancer, hepatitis, mutation abnormalities, and reproduction disorders. Minimization and inactivation of aflatoxins contaminants through proper crop management at farm level and with physical, chemical, and biological techniques are the limelight of the article.     

Exploring the Relationship between Soil Properties and Deterioration of Metallic Pipes Using Predictive Data Mining Methods

Soil corrosivity is considered to be a major factor for the deterioration of metallic water mains. Using a 10-point scoring method as suggested by the American Water Works Association, soil corrosivity potential can be estimated by five soil properties: (1) resistivity; (2) pH value; (3) redox potential; (4) sulfide; and (5) percentage of clay fines. However, the relationship between soil corrosivity and pipe deterioration is often ambiguous and not well-defined. In order to identify the direct relationship between soil properties and pipe deterioration, which is defined as the ratio of the maximum pit depth to pipe age, predictive data mining approaches are investigated in this study. Both single- and multipredictor based approaches are employed to model such relationship. The advantage of combining multiple predictors is also demonstrated. Among all approaches, rotation forest achieves the best result in terms of the prediction error to estimate pipe deterioration rate. Compared to the random forest method, which is next to the best, the normalized mean square error decreased 50%. With the proposed approaches, the assessment of pipe condition can be achieved by analyzing soil properties. This study also highlights the importance for collecting more reliable soil properties data.     

A hybrid unscented filtering and particle swarm optimization technique for harmonic analysis of nonstationary signals

This paper presents a modified unscented Kalman filter for accurate estimation of frequency and harmonic components of a time-varying signal embedded in noise with low signal-to-noise ratio. Further, the model and measurement error covariances along with the unscented Kalman filter parameters are selected using a modified particle swarm optimization algorithm. To circumvent the problem of premature convergence and local minima, a dynamically varying inertia weight based on the variance of the population fitness is used. This results in a better local and global searching ability of the particles, which improves the convergence of the velocity and better accuracy of the unscented Kalman filter parameters. Various simulation results for nonstationary sinusoidal signals with time varying amplitude, phase and harmonic content corrupted with noise, reveal significant improvement in noise rejection and speed of convergence and accuracy in comparison to the well known extended Kalman filter.