A New Link Failure Resilient Priority Based Fair Mutual Exclusion Algorithm for Distributed Systems

This paper aims towards designing a new token-based mutual exclusion algorithm for distributed systems. In some of the earlier work, token based algorithms for mutual exclusion are proposed for the distributed environment assuming inverted tree topology. In a wireless setup, such a stable, hierarchical topology is quite unrealistic due to frequent link failures. The proposed token-based algorithm works for processes with assigned priorities on any directed graph topology with or without cycles. The proposed algorithm, in spite of considering priorities of processes, ensures liveness in terms of token requests from low priority processes. Moreover, the algorithm keeps control message traffic reasonably low. The simulation results exhibit the performance of the proposed algorithm under varied contexts besides presenting a comparative performance with other recent algorithms for mutual exclusion like FAPP (Fairness Algorithm for Priority Process).     

A Case‐Based Reasoning system for complex medical diagnosis

A Case‐Based Reasoning (CBR) system for medical diagnosis mimics the way doctors make a diagnosis. Given a new case, its accuracy in practice depends on successful retrieval of similar cases. CBR systems have had some success in dealing with simple diseases because of the robustness of their case base. However, their diagnostic accuracy suffers when dealing with complex diseases particularly those that involve multiple domains in medicine. An example of such a condition is Premenstrual syndrome (PMS) as it falls under both gynaecology and psychiatry. To address this issue, the paper proposes a CBR‐based expert system that uses the K‐nearest neighbour (KNN) algorithm to search k similar cases based on the Euclidean distance measure. The novelty of the system is in the design of a flexible auto‐set tolerance (T), which serves as a threshold to extract cases for which similarities are greater than the assigned value of T. A prototype software tool with a menu‐driven Graphical User Interface (GUI) has been developed for case input, analysis of results, and case adaptation within the system. Finally, the performance of the tool has been checked on a set of real‐world PMS cases.     

Neuro-computing based short range prediction of some meteorological parameters during the pre-monsoon season

A Feed forward multi-layered artificial neural network model is designed in this paper to estimate the maximum surface temperature and relative humidity needed for the genesis of severe thunderstorms over Calcutta (22° 32, 88° 20). The performance of the model is found to be adroit. It has, thus, been discerned that the neural network technique is of great use in forecasting the occurrence of high frequency small-scale weather systems like Severe Local Storms. Filing up the missing values and extension of time series is observed to be possible with this model. Prediction error is computed and compared for single layer network and one hidden layer neural nets. Result reveals the efficiency of the one hidden layer neural net.     

Thermal-aware task allocation and scheduling for periodic real-time applications in mesh-based heterogeneous NoCs

Real-Time Systems - With continuous technology scaling, the power density and hence the temperature of Network-on-Chip (NoC) may increase rapidly. This in-turn degrades the performance of the chip...     

Registration techniques for using imperfect and partially calibrated devices in planar multi-projector displays

Multi-projector displays today are automatically registered, both geometrically and photometrically, using cameras. Existing registration techniques assume pre-calibrated projectors and cameras that are devoid of imperfections such as lens distortion. In practice, however, these devices are usually imperfect and uncalibrated. Registration of each of these devices is often more challenging than the multi-projector display registration itself. To make tiled projection-based displays accessible to a layman user we should allow the use of uncalibrated inexpensive devices that are prone to imperfections. In this paper, we make two important advances in this direction. First, we present a new geometric registration technique that can achieve geometric alignment {\em in the presence of severe projector lens distortion} using a relatively inexpensive low-resolution camera. This is achieved via a closed-form model that relates the projectors to cameras, in planar multi-projector displays, using rational Bezier patches. This enables us to geometrically calibrate a 3000 x 2500 resolution planar multi-projector display made of 3 x 3 array of nine severely distorted projectors using a low resolution (640 x 480) VGA camera. Second, we present a photometric self-calibration technique for a projector-camera pair. This allows us to photometrically calibrate the same display made of nine projectors using a photometrically uncalibrated camera. To the best of our knowledge, this is the first work that allows geometrically imperfect projectors and photometrically uncalibrated cameras in calibrating multi-projector displays.     

Design and analysis of a video-on-demand server

The availability of high-speed networks, fast computers and improved storage technology is stimulating interest in the development of video on-demand services that provide facilities similar to a video cassette player (VCP). In this paper, we present a design of a video-on-demand (VOD) server, capable of supporting a large number of video requests with complete functionality of a remote control (as used in VCPs), for each request. In the proposed design, we have used an interleaved storage method with constrained allocation of video and audio blocks on the disk to provide continuous retrieval. Our storage scheme interleaves a movie with itself (while satisfying the constraints on video and audio block allocation. This approach minimizes the starting delay and the buffer requirement at the user end, while ensuring a jitter-free display for every request. In order to minimize the starting delay and to support more non-concurrent requests, we have proposed the use of multiple disks for the same movie. Since a disk needs to hold only one movie, an array of inexpensive disks can be used, which reduces the overall cost of the proposed system. A scheme supported by our disk storage method to provide all the functions of a remote control such as “fast-forwarding”, “rewinding” (with play “on” or “off”), “pause” and “play” has also been discussed. This scheme handles a user request independent of others and satisfies it without degrading the quality of service to other users. The server design presented in this paper achieves the multiple goals of high disk utilization, global buffer optimization, cost-effectiveness and high-quality service to the users.     

Enhancing effective depth-of-field by image fusion using mathematical morphology

Reduced depth-of-field (DOF) poses a problem in the light optical imaging system, since the objects present outside this zone appear blurry in the recorded image. The effective DOF of the sensor may be enhanced considerably without compromising the quality of the image by fusing images captured with different focused regions. This paper presents an image fusion technique suitable for combining multifocus images of a scene. The method employs morphological filters to select sharply focused regions from various images and then combines them together to reconstruct the image in which all the regions are properly focused. A performance measure based on image gradients is used to compare the results obtained by the proposed method with those obtained by other image fusion techniques.     

Autocalibration of multiprojector CAVE-like immersive environments

In this paper, we present the first method for the geometric autocalibration of multiple projectors on a set of CAVE-like immersive display surfaces including truncated domes and 4 or 5-wall CAVEs (three side walls, floor, and/or ceiling). All such surfaces can be categorized as swept surfaces and multiple projectors can be registered on them using a single uncalibrated camera without using any physical markers on the surface. Our method can also handle nonlinear distortion in the projectors, common in compact setups where a short throw lens is mounted on each projector. Further, when the whole swept surface is not visible from a single camera view, we can register the projectors using multiple pan and tilted views of the same camera. Thus, our method scales well with different size and resolution of the display. Since we recover the 3D shape of the display, we can achieve registration that is correct from any arbitrary viewpoint appropriate for head-tracked single-user virtual reality systems. We can also achieve wallpapered registration, more appropriate for multiuser collaborative explorations. Though much more immersive than common surfaces like planes and cylinders, general swept surfaces are used today only for niche display environments. Even the more popular 4 or 5-wall CAVE is treated as a piecewise planar surface for calibration purposes and hence projectors are not allowed to be overlapped across the corners. Our method opens up the possibility of using such swept surfaces to create more immersive VR systems without compromising the simplicity of having a completely automatic calibration technique. Such calibration allows completely arbitrary positioning of the projectors in a 5-wall CAVE, without respecting the corners.     

Automated cell classification and visualization for analyzing remyelination therapy

Remyelination therapy is a state-of-the-art technique for treating spinal cord injury (SCI). Demyelination—the loss of myelin sheath that insulates axons, is a prominent feature in many neurological disorders resulting in SCI. This lost myelin sheath can be replaced by remyelination. In this paper, we propose an algorithm for efficient automated cell classification and visualization to analyze the progress of remyelination therapy in SCI. Our method takes as input the images of the cells and outputs a density map of the therapeutically important oligodendrocyte-remyelinated axons (OR-axons) which is used for efficacy analysis of the therapy. Our method starts with detecting cell boundaries using a robust, shape-independent algorithm based on iso-contour analysis of the image at progressively increasing intensity levels. The detected boundaries of spatially clustered cells are then separated using the Delaunay triangulation based contour separation method. Finally, the OR-axons are identified and a density map is generated for efficacy analysis of the therapy. Our efficient automated cell classification and visualization of remyelination analysis significantly reduces error due to human subjectivity. We validate the accuracy of our results by extensive cross-verification by the domain experts.