Analysis of conduction heat transfer problems in steady, 2D regions with circular holes using a special boundary integral method

A special boundary integral method developed for two-dimensional regions containing circular holes is used to calculate temperature and heat transfer on the boundaries of several selected regions. The geometrical configuration of the region is arbitrary and convective boundary conditions are assumed. An important feature of the method is analytic representation of temperature and its normal derivative on the interior circular holes in the form of a harmonic series. This makes the application of the boundary integral method convenient and free from conditioning problems associated with small interior boundaries. Heat transfer from circular isothermal interior holes are calculated for several illustrative examples using three terms of the harmonic series representation for heat transfer at each of the circular boundaries. The results are presented and discussed.     

A Cost-Effective Thickness Measurement Technique for Engine Propellers

This paper describes the design and development of a precision calliper system to measure the surface profile of an outboard marine engine propeller blade. Several instruments that are commonly used for measuring the surface profile of a propeller blade are reviewed in this paper. These include the pitch meter, the profilometer and the computer numerical control coordinate-measuring machine (CNC-CMM). However, the operating practices and availability of different facilities in industry necessitate a more cost-effective approach. An alternative method using a precision calliper system is therefore proposed. Details of the design criteria, principles of operation and the testing and verification of the system are presented. The paper concludes that the precision calliper system is a cost-effective method for measuring the surface profile of a propeller.     

Finite-time coordination in multiagent systems using sliding mode control approach

Finite-time stability in dynamical systems theory involves systems whose trajectories converge to an equilibrium state in finite time. In this paper, we use the notion of finite-time stability to apply it to the problem of coordinated motion in multiagent systems. Specifically, we consider a group of agents described by fully actuated Euler–Lagrange dynamics along with a leader agent with an objective to reach and maintain a desired formation characterized by steady-state distances between the neighboring agents in finite time. We use graph theoretic notions to characterize communication topology in the network determined by the information flow directions and captured by the graph Laplacian matrix. Furthermore, using sliding mode control approach, we design decentralized control inputs for individual agents that use only data from the neighboring agents which directly communicate their state information to the current agent in order to drive the current agent to the desired steady state. Sliding mode control is known to drive the system states to the sliding surface in finite time. The key feature of our approach is in the design of non-smooth sliding surfaces such that, while on the sliding surface, the error states converge to the origin in finite time, thus ensuring finite-time coordination among the agents in the network. In addition, we discuss the case of switching communication topologies in multiagent systems. Finally, we show the efficacy of our theoretical results using an example of a multiagent system involving planar double integrator agents.     

Exploring album structure for face recognition in online social networks

In this paper, we propose an album-oriented face-recognition model that exploits the album structure for face recognition in online social networks. Albums, usually associated with pictures of a small group of people at a certain event or occasion, provide vital information that can be used to effectively reduce the possible list of candidate labels. We show how this intuition can be formalized into a model that expresses a prior on how albums tend to have many pictures of a small number of people. We also show how it can be extended to include other information available in a social network. Using two real-world datasets independently drawn from Facebook, we show that this model is broadly applicable and can significantly improve recognition rates.     

Real world representation of a road network for route planning in GIS

This paper addresses a methodology to properly represent a road network in the geographic information system (GIS) for network analysis. Over the years, the real world has become too complex to model properly within a given information system, such as GIS. Ideally, when the real world is represented as accurately as possible, a GIS can answer a question in its virtual world that coincides with the exact answer in the real world. However, existing methods related to impedance modeling for each segment of a road network in a route planning analysis that includes only a distance or time variable do not give proper results. Hence, this study investigates how a road network can represent the real world in a GIS and offer route planning tools. To address this, first, additional realistic variables are taken into account. These include weather, sight-seeing information, road type, and so on. Second, to combine these variables, an impedance model (IM) using the analytical hierarchical process (AHP) method is proposed. Finally, all of the models are implemented and verified with a sensitivity analysis. The models were successfully implemented in this work. All of the paths of the route planning analysis were successfully matched with the drivers’ paths that would normally be chosen in reality. It is anticipated that the use of other techniques such as analytical network process (ANP) in addition to AHP would be useful to overcome the aforementioned problem.     

SAPDS: self-healing attribute-based privacy aware data sharing in cloud

This paper addresses the issue of data governance in a cloud-based storage system. To achieve fine-grained access control over the outsourced data, we propose Self-Healing Attribute-based Privacy Aware Data Sharing in Cloud (SAPDS). The proposed system delegates the key distribution and management process to a cloud server without seeping out any confidential information. It facilitates data owner to restrain access of the user with whom data has been shared. User revocation is achieved by merely changing one attribute associated with the decryption policy, instead of modifying the entire access control policy. It enables authorized users to update their decryption keys followed by each user revocation, making it self-healing, without ever interacting with the data owner. Computation analysis of the proposed system shows that data owner can revoke n′ users with the complexity of O(n′). Besides this, legitimate users can update their decryption keys with the complexity of O(1).     

Electron Acoustic Solitons

Electron acoustic solitons in collisionless and weakly relativistic plasmas are studied. The Krylov–Bogoliubov–Mitropolsky perturbative technique is employed to obtain the nonlinear Schrodinger wave equation. We have numerically investigated modulational instability for different values of the streaming velocity. Graphs have been plotted to see the change in amplitude and inverse width by varying different plasma parameters.     

Neural networks of data inhibiting long memory pattern

We experiment with three neural network models for forecasting to better understand the performance of neural networks for the case when the data exhibits a long memory pattern. To obtain the optimum networks, the effect of network characteristics such as the training parameters, the number of hidden layers, and the testing and training percentages are simulated. The third model, which consists of a combination of individual time series forecasts, provides superior results.     

A novel finite rings based algebraic scheme of evolving secure S-boxes for images encryption

Multimedia Tools and Applications - Substitution-boxes have significant role in block ciphers as they are the only component which offers nonlinearity in the anticipated symmetric encryption...     

Fuzzy Based Hybrid Focus Value Estimation for Multi Focus Image Fusion

Due to limited depth-of-field of digital single-lens reflex cameras, the scene content within a limited distance from the imaging plane remains in focus while other objects closer to or further away from the point of focus appear as blurred (out-of-focus) in the image. Multi-Focus Image Fusion can be used to reconstruct a fully focused image from two or more partially focused images of the same scene. In this paper, a new Fuzzy Based Hybrid Focus Measure (FBHFM) for multi-focus image fusion has been proposed. Optimal block size is very critical step for multi-focus image fusion. Particle Swarm Optimization (PSO) algorithm has been used to find optimal size of the block of the images for extraction of focus measure features. After finding optimal blocks, three focus measures Sum of Modified Laplacian, Gray Level Variance and Contrast Visibility has been extracted and combined these focus measures by using intelligent fuzzy technique. Fuzzy based hybrid intelligent focus values were estimated using contrast visibility measure to generate focused image. Different sets of multi-focus images have been used in detailed experimentation and compared the results with state-of-the-art existing techniques such as Genetic Algorithm (GA), Principal Component Analysis (PCA), Laplacian Pyramid discrete wavelet transform (DWT), and aDWT for image fusion. It has been found that proposed method performs well as compare to existing methods.