Analysing the patterns of spatial contrast discontinuities in natural images for robust edge detection

Pattern Analysis and Applications - The pattern of spatial contrast discontinuities in natural images has been analysed in the present work, and based on it, a new adaptive model of the...     

Face posture estimation using eigen analysis on an IBR (image based rendered) database

In this paper, we present a novel representation of the human face for estimating the orientation of the human head in a two dimensional intensity image. The method combines the use of the much familiar eigenvalue based dissimilarity measure with image based rendering. There are two main components of the algorithm described here: the offline hierarchical image database generation and organization, and the online pose estimation stage. The synthetic images of the subject's face are automatically generated offline, for a large set of pose parameter values, using an affine coordinate based image reprojection technique. The resulting database is formally called as the IBR (or image based rendered) database. This is followed by the hierarchical organization of the database, which is driven by the eigenvalue based dissimilarity measure between any two synthetic image pair. This hierarchically organized database is a detailed, yet structured, representation of the subject's face. During the pose estimation of a subject in an image, the eigenvalue based measure is invoked again to search the synthetic (IBR) image closest to the real image. This approach provides a relatively easy first step to narrow down the search space for complex feature detection and tracking algorithms in potential applications like virtual reality and video-teleconferencing applications.     

Polygeneration performance assessments: multi-dimensional viewpoint

Performance metrics of a system with single input and single output is straight forward and is generally termed as ‘efficiency’. However, for systems with multiple outputs, defined performance metrics has to include effects of all outputs on a rational basis. For systems with both multiple inputs and outputs such definition is even more complicated. Polygeneration is the integration of multiple utility outputs with one or more inputs for better performance. The better performance may again be assessed from different aspects, e.g., thermodynamic, economic, social, etc. Performance metrics of polygeneration is not unique. It depends on type of systems as well as objective of evaluation of it. In this paper, several possible performance parameters for polygeneration are discussed. Evaluation of performance is also tested with multi-dimensional viewpoints. Simulation results of two polygeneration schemes are used to show case studies for these defined performance parameters. Relative performance of polygeneration schemes with different fuel inputs is presented to show the performance variation of these schemes with multi-dimensional viewpoints.     

Genetic evolutionary algorithm for optimal allocation of wavelength converters in WDM optical networks

In this article, a genetic evolutionary algorithm is proposed for efficient allocation of wavelength converters in WDM optical networks. Since wavelength converters are expensive, it is desirable that each node in WDM optical networks uses a minimum number of wavelength converters to achieve a near-ideal performance. The searching capability of genetic evolutionary algorithm has been exploited for this purpose. The distinguished feature of the proposed approach lies in handling the conflicting circumstances during allocation of wavelength converters considering various practical aspects (e.g., spatial problem, connectivity of a node with other nodes) rather than arbitrarily to possibly improve the overall blocking performance of WDM optical networks. The proposed algorithm is compared with a previous approach to establish its effectiveness and the results demonstrate the ability of the proposed algorithm to efficiently solve the problem of Optimal Wavelength Converters Allocation (OWCA) in practical WDM optical networks.

Hybrid NOMA for Future Radio Access: Design,Potentials and Limitations

Wireless Personal Communications - Next-generation internet of things (IoT) applications need numerous low-powered wireless mobile devices to connect with each other, having ultra-reliability and...     

Utilizing waste heat of the flue gas for post-combustion CO2 capture—A comparative study for different process layouts

The inlet flue gas entering the absorber column must be ~40°C and hence needs cooling. In this article, it is proposed that waste heat be recovered from the flue gas using a condensing heat exchanger. This recovered heat is utilized as partial supplement to subsequent heating in stripper during CO₂ capture. System layouts—one for base case and two others—have been conceptualized. ASPEN Plus^® simulation results for the other two layouts are discussed for energy savings with respect to the base case. Results show that, for the other two layouts, reboiler heat duty decreases though carbon capture efficiency also decreases.     

Like-minded communities: bringing the familiarity and similarity together

Community detection in social networks is a well-studied problem. A community in social network is commonly defined as a group of people whose interactions within the group are more than outside the group. It is believed that people’s behavior can be linked to the behavior of their social neighborhood. While shared characteristics of communities have been used to validate the communities found, to the best of authors’ knowledge, it is not demonstrated in the literature that communities found using social interaction data are like-minded, i.e., they behave similarly in terms of their interest in items (e.g., movie, products). In this paper, we experimentally demonstrate, on a social networking movie rating dataset, that people who are interested in an item are socially better connected than the overall graph. Motivated by this fact, we propose a method for finding communities wherein like-mindedness is an explicit objective. We find small tight groups with many shared interests using a frequent item set mining approach and use these as building blocks for the core of these like-minded communities. We show that these communities have higher similarity in their interests compared to communities found using only the interaction information. We also compare our method against a baseline where the weight of edges are defined based on similarity in interests between nodes and show that our approach achieves far higher level of like-mindedness amongst the communities compared to this baseline as well.     

Analysis and synthesis of laser forming process using neural networks and neuro-fuzzy inference system

To apply laser forming process in reality, it is required to know the relationships between the deformed shape and scanning paths along with heating conditions. The deformation due to laser scanning depends on various factors, namely laser power, scan speed, spot diameter, scan position, number of scans, and many others. This article presents soft computing-based methods to predict deformations for a set of heating conditions, and also to determine the heating lines and heat conditions, in order to get a desired shape (i.e., inverse analysis). A novel attempt has been made in this paper to carry out analysis and synthesis (inverse analysis) of laser forming process using both genetic-neural network (GA-NN) and genetic adaptive neuro-fuzzy inference system (GA-ANFIS). During the analysis, laser power, scan speed, spot diameter, scan position and number of scans are taken as inputs and bending angle is considered as the output. A batch mode of training has been used for both the approaches with the help of some experimental data. The performances of the developed approaches have been tested on some real experimental data. Both the approaches are found to be effective to predict the bending angles and carry out the process synthesis successfully. GA-NN approach is found to perform better than the GA-ANFIS approach in predicting the bending angles, and both the approaches are able to provide comparable predictions in inverse analysis.