Abstract

Since many decades different ports of world's forest envirornment is getting depleted because of many other factors but major deplection due to random forest fires.

Abstract

The Doda Earthquake of 1st May 2013 at 12:27 Hrs. (IST) hit border region of two states of India (Jammu & Kashmir and Himachal Pradesh) (Mw= 5.8). This paper describes the findings of the 5-day post-earthquake reconnaissance survey undertaken in the affected areas with particular emphasis onbuilding typology, construction materials and construction practices. Post-earthquake damage assessment of the built environment suggests that recently built structures do not have adequate earthquake resistant featuresto resist severe earthquake shaking (of about IX on MSK scale) expected in the region. On the other hand, traditional constructions with good earthquake resistant features performed much better.The maximum intensity of shaking during the said event was only about VI on MSK scale, and the damage was less. But, the type of damage suggests that huge losses can be incurred in the region during a future earthquake of higher intensity, if the built environment is not retrofitted.

Abstract

Dam is one of the biggest structures built on the Earth. It is known as a life line structure, as it serves the purpose of irrigation, hydro-electric power generation, flood control, domestic and industrial water supply etc., which are important for human existence. This makes dam as a reliable structure. For this reason, dam should always be designed for highest safety, resisting worst forces of nature. India is a country with over 5,100 large dams. India is also a seismically active country with over 1,040 active faults. Earthquake events like 1988 Bihar, 1991 Uttarkashi, 1993 Killari, 1997 Jabalpur, 1999 Chamoli, 2001 Bhuj, 2002 Andaman, 2004 Sumatra, 2005 Kashmir, and 2011 Sikkim have caused enormous loss of life and property in the country. Also events like 1992 Landers, 1994 Northridge, 1995 Hyogoken-Nanbu and few other events that took place around the world proved how devastating an earthquake could be, particularly if it is near-field. Near-field ground motions could cause more damaging effects on structures, as they were observed to differ dramatically from the characteristics of their far-field counterparts. The propagation of fault rupture towards a site at very high velocity causes most of the seismic energy from the rupture to arrive in a single or multiple large long period pulse of motion, which occurs at the beginning of the record. This characteristic of near-field ground motions could cause damage to a wide range of structures including dams. Several dams that were built in India, which are in highly seismic zones are prone to near-field ground motions. In

Abstract

In this paper we consider the problem of coordinating the motion of the manipulator and the vehicle to produce stable trajectories for the combined mobile manipulator system on uneven terrain. These kinds of situations often arise in planetary exploration, where rovers equipped with a manipulator are required to navigate over general uneven terrain. Moreover the framework can also be used in situations where the mobile manipulator is required to transport objects on uneven terrain. We generate feasible trajectories for the vehicle between a given start and a goal point considering the dynamics of the manipulator. The framework proposed in the paper plans such motion profile of the manipulator that maximizes vehicle stability which is measured by a novel concept called Feasible Acceleration Count (FAC). We show that, from the point of view of motion planning of mobile manipulator on uneven terrains, FAC gives a better estimate of vehicle stability than more popular metrics like Tip-Over Stability. The trajectory planner closely resembles motion primitive based graph based planning and is combined with a novel cost function derived from FAC. The efficacy of the approach is shown through simulations of a mobile manipulator system on a 2.5D uneven terrain.

Abstract

This paper presents a novel exploration strategy for coordinated exploration between unmanned ground vehicles (UGV) and micro-air vehicles (MAV). The exploration is modeled as an Integer Programming (IP) optimization problem and the allocation of the vehicles(agents) to frontier locations is modeled using binary variables. The formulation is also studied for distributed system, where agents are divided into multiple teams using graph partitioning. Optimization seamlessly integrates several practical constraints that arise in exploration between such heterogeneous agents and provides an elegant solution for assigning task to agents. We have also presented comparison with previous methods based on distance traversed and computational time to signify advantages of presented method. We also show practical realization of such an exploration where an UGV-MAV team efficiently builds a map of an indoor environment.

Abstract

Reactive Collision avoidance for non-holonomic robots is a challenging task because of the restrictions in the space of achievable velocities. The complexity increases further when multiple non-holonomic robots are operating in tight/cluttered spaces. The present paper presents a framework specially carved out for such situations. But at the same time can be easily appended with any existing collision avoidance framework. At the crux of the methodology is the concept of non-linear time scaling which allows robots to reactively accelerate/de-accelerate without altering the geometric path. The framework introduced is completely independent of the robot kinematics and dynamics. As such it can be applied to any ground or aerial robot. Through this concept the collision avoidance is framed as a problem of choosing appropriate scaling transformations. We present a “scaled” variant of the collision cone concept which automatically induces distributiveness among robots. The efficacy of the proposed work is demonstrated through simulations of both ground as well as UAVs.

Abstract

Detecting multiple planes in images is a challenging problem, but one with many applications. Recent work such as J-Linkage and Ordered Residual Kernels have focussed on developing a domain independent approach to detect multiple structures. These multiple structure detection methods are then used for estimating multiple homographies given feature matches between two images. Features participating in the multiple homographies detected, provide us the multiple scene planes. We show that these methods provide locally optimal results and fail to merge detected planar patches to the true scene planes. These methods use only residues obtained on applying homography of one plane to another as cue for merging. In this paper, we develop additional cues such as local consistency of planes, local normals, texture etc. to perform better classification and merging. We formulate the classification as an MRF problem and use TRWS message passing algorithm to solve non metric energy terms and complex sparse graph structure. We show results on challenging dataset common in robotics navigation scenarios where our method shows accuracy of more than 85 percent on average while being close or same as the actual number of scene planes.

Abstract

When multiple virtual machines (VMs) are co scheduled on the same physical machine, they may undergo a performance degradation. The performance degradation is due to the contention for shared resources like last level cache, hard disk, network bandwidth etc. This can lead to service-level agreement violations and thereby customer dissatisfaction. The classical approach to solve the co scheduling problem involves a central authority which decides a co schedule by solving a constrained optimization problem with an objective function such as average performance degradation. In this paper, we use the theory of stable matchings to provide an alternate game theoretic perspective to the co scheduling problem wherein each VM selfishly tries to minimize its performance degradation. We show that the co scheduling problem can be formulated as a Stable Roommates Problem (SRP). Since certain instances of the SRP do not have any stable matching, we reduce the problem to the Stable Marriages Problem (SMP) via an initial approximation. Gale and Shapley proved that any instance of the SMP has a stable matching and can be found in quadratic time. From a game theoretic perspective, the SMP can be thought of as a matching game which always has a Nash equilibrium. There are distributed algorithms for both the SRP and SMP problems. A VM agent in a distributed algorithm need not reveal its preference list to any other VM. This allows each VM to have a private cost function. A principal advantage of this problem formulation is that it opens up the possibility of applying the rich theory of matching markets from game theory to address various aspects of the VM co scheduling problem such as stability, coalitions and privacy both from a theoretical and practical standpoint. We also propose a new workload characterization technique for a combination of compute and memory intensive workloads. The proposed technique uses a sentinel program and it requires only two runs per workload for characterization. VMs can use this technique in deciding their partner preference ranks in the SRP and SMP problems. The characterization technique has also been used in proposing two new centralized VM co scheduling algorithms whose performance is close to the optimal Blossom algorithm.

Abstract

The compiler optimizations we enable and the order in which we apply them on a program have a substantial impact on the program execution time. Compilers provide default optimization sequences which can give good program speedup. As the default sequences have to optimize programs with different characteristics, they embed in them multiple subsequences which can optimize different classes of programs. These multiple subsequences may falsely interact with each other and affect the potential program speedup achievable. Instead of searching for a single universally optimal sequence, we can construct a small set of good sequences such that for every program class there exists a near-optimal optimization sequence in the good sequences set. If we can construct such a good sequences set which covers all the program classes in the program space, then we can choose the best sequence for a program by trying all the sequences in the good sequences set. This approach completely circumvents the need to solve the program classification problem. Using a sequence set size of around 10 we got an average speedup up to 14% on PolyBench programs and up to 12% on MiBench programs. Our approach is quite different from either the iterative compilation or machine-learning-based prediction modeling techniques proposed in the literature so far. We use different training and test datasets for cross-validation as against the Leave-One-Out cross-validation technique.

Abstract

In this paper, we present a noise cancellation technique for common gate ultra wide band (UWB) low noise amplifiers (LNAs) which not only reduces the noise but also increases the gain. On implementing this technique in one of the existing UWB LNAs significant reduction of noise figure (NF) compared to same LNA without noise cancellation technique was observed. Noise cancellation of the most dominating thermal noise source viz. the input matching device with theoretical analysis is presented in this paper. Simulation results with TSMC 0.18 (m CMOSRF technology shows a peak gain of 28 dB and base NF of 3.16 dB for a 6.6 GHz (2.4-9 GHz) band LNA with noise cancellation when compared to peak gain of 21 dB and base NF of 4.09 dB without noise cancellation. Both theoretical analysis and simulation results are in good agreement.