Location-Aware Computing, Virtual Networks

This issue includes four works in process on issues and applications in location-aware computing: letting users set and control privacy policies when they use location-aware applications, cold-starting recommender systems for mobile location-aware services, aggregating contextual information for location-based applications, and applying location-based services to public transportation environments. The department also includes a report on lightweight virtualization of low-power wireless personal area networks.     

Multi-oriented touching text character segmentation in graphical documents using dynamic programming

The touching character segmentation problem becomes complex when touching strings are multi-oriented. Moreover in graphical documents sometimes characters in a single-touching string have different orientations. Segmentation of such complex touching is more challenging. In this paper, we present a scheme towards the segmentation of English multi-oriented touching strings into individual characters. When two or more characters touch, they generate a big cavity region in the background portion. Based on the convex hull information, at first, we use this background information to find some initial points for segmentation of a touching string into possible primitives (a primitive consists of a single character or part of a character). Next, the primitives are merged to get optimum segmentation. A dynamic programming algorithm is applied for this purpose using the total likelihood of characters as the objective function. A SVM classifier is used to find the likelihood of a character. To consider multi-oriented touching strings the features used in the SVM are invariant to character orientation. Experiments were performed in different databases of real and synthetic touching characters and the results show that the method is efficient in segmenting touching characters of arbitrary orientations and sizes.     

Effect of nano CuO addition on the tribo-mechanical behavior of alumina ceramics in non-conformal contact

Sintering of alumina from 1500°C to 1650°C and tribo-mechanical properties at room temperature had been investigated using nano CuO as a sintering aid. Bulk density gradually increases with sintering temperature from 1500°C to 1600°C and is optimized at 1600°C, beyond this, bulk density does not significantly increase at 1650°C. The addition of 2 wt% CuO showed the best result on densification. Densification of about 97.74% was attained at 1600°C with the incorporation of 2 wt% CuO. Nano CuO at grain boundaries forms CuAl₂O₄ liquid which modifies the morphology of the grain and improves mechanical properties. The formation of self-lubricating tribo-film on the wear track results in a low coefficient of friction <0.2 and reduces specific wear rate. 4 wt% CuO addition increases contact tensile stress (σ_max) by 51.2% and high Hertzian contact pressure (P_max≈1.51 GPa) causes plastic deformation of wear track. The re-solidified strengthening bond phase on the wear track simultaneously increases in friction coefficient and wear resistance with CuO addition. The optimizing effect of CuO addition shows that 2 wt% significantly decreases wear rate, and increases hardness and fracture toughness.     

Thermal modeling of a controlled environment greenhouse cum solar distillation for composite and warm humid climates of India

The present study is concerned with the analysis of solar desalination system combined with a greenhouse for both composite and warm humid climate of India. Analytical expressions for water temperature, greenhouse room air temperature, glass cover temperature, flowing water mass over the glass cover, hourly yield of fresh water and thermal efficiency have been derived in terms of design and climatic parameters for a typical day of summer and winter period. Temperature rise of flowing water mass with respect to distance and time in solar still unit has also been incorporated in the mathematical modeling. The effects of various still and design parameters on its performances have been discussed in detail. The yield of fresh water was found to be higher in warm humid climate than composite climate.     

Hybrid reactor for priority pollutant nitrobenzene removal

The performance of a hybrid reactor, comprising of trickling filter and activated sludge process, in treating nitrobenzene wastewater was investigated. Acetate induced cells of mixed consortia was acclimatized with gradual increase of nitrobenzene concentration up to 90 mg/l in 100 days using sodium acetate as co-substrate and considering COD and nitrobenzene concentration as paramount parameters for assessing the growth of biofilm and acclimation. A removal of 60-95.80% COD and 80-90.23% nitrobenzene was observed during acclimation. During hydraulic retention time (HRT) studies, the optimum HRT was found to be 29.55 h at which a maximum of 95.83% COD and 97.93% nitrobenzene removal was observed. Other studies included optimization of C:N ratio, substrate:co-substrate ratio, effect of shock loading and estimation of volatilization losses. The optimum C:N ratio was found to be 100:20 at which maximum 97.93% removal of nitrobenzene was observed. At optimum HRT (29.55 h) and optimum C:N ratio (100:20) optimum substrate:co-substrate ratio was found to be 1:33. From the shock load studies it can be concluded that the system can withstand shock load up to two times of usual nitrobenzene concentration. A loss of 9.44% nitrobenzene was observed due to volatilization and mass balance gave an efficiency of 87.49% biological removal of nitrobenzene.     

Failure Analysis of Stacker-cum-Reclaimer in Ore Handling Plant

A catastrophic failure of a Stacker-cum-Reclaimer led to loss of several days of service in one ore handling plant in India. The failure was severe enough to initiate an investigation into the possible causes of failure and estimation of the residual life for other units of Stacker-cum-Reclaimer of the same design and age, working in the plant. The failure analysis included a visual inspection of the failed structure, metallographic studies, static stress and stability analysis under normal operating conditions, stress analysis for a possible impact load on the structure, experimental stress analysis, and fatigue life cycle analysis. The results obtained indicate that the failure could be caused by an impact load arising out of some operational conditions resulting from the conditions of the rail track on which the machine travels. The material properties, the physical conditions of the material, and a fatigue analysis indicate that the existing system can work for several more decades, provided some checkpoints are planned and instituted to monitor the health of the structure at regular intervals.     

Effect of grain size on the tensile behaviour and fracture toughness of Ti-10V-4.5Fe-3Al beta titanium alloy

The tensile and fracture toughness behaviour of Ti-10V-4.5Fe-3Al alloy in the beta solution treated condition was investigated as a function of β grain size and the behaviour was compared with that of Ti-10V-2Fe-3Al alloy. It was found that this alloy, unlike the Ti-10V-2Fe-3Al alloy, did not exhibit any stress induced martensitic transformation during tensile testing. This was attributed to the higher stability of the β phase in this alloy as compared to that in Ti-10V-2Fe-3Al alloy because of the higher iron content. The yield strength, ultimate tensile strength, total elongation and fracture toughness in this alloy were found to decrease with increase in grain size. The yield strength of this alloy was found to obey the Hall-Petch relationship with grain size, similar to the observation in Ti-10V-2Fe-3Al alloy. However, the σ_i value was higher and k value lower than that observed in Ti-10V-2Fe-3Al alloy. The fracture toughness in Ti-10V-4.5Fe-3Al alloy was also found to increase linearly with inverse square root of grain size; however, the slope was significantly less than that observed in Ti-10V-2Fe-3Al alloy.     

A consistent nonparametric Bayesian procedure for estimating autoregressive conditional densities

This article proposes a Bayesian infinite mixture model for the estimation of the conditional density of an ergodic time series. A nonparametric prior on the conditional density is described through the Dirichlet process. In the mixture model, a kernel is used leading to a dynamic nonlinear autoregressive model. This model can approximate any linear autoregressive model arbitrarily closely while imposing no constraint on parameters to ensure stationarity. We establish sufficient conditions for posterior consistency in two different topologies. The proposed method is compared with the mixture of autoregressive model [Wong and Li, 2000. On a mixture autoregressive model. J. Roy. Statist. Soc. Ser. B 62(1), 91-115] and the double-kernel local linear approach [Fan et al., 1996. Estimation of conditional densities and sensitivity measures in nonlinear dynamical systems. Biometrika 83, 189-206] by simulations and real examples. Our method shows excellent performances in these studies.