Data Mining - Concepts and Techniques.

Planning algorithms are impacting technical disciplines and industries around the world, including robotics, computer-aided design, manufacturing, computer graphics, aerospace applications, drug design, and protein folding. This coherent and comprehensive book unifies material from several sources, including robotics, control theory, artificial intelligence, and algorithms. The treatment is centered on robot motion planning but integrates material on planning in discrete spaces. A major part of the book is devoted to planning under uncertainty, including decision theory, Markov decision processes, and information spaces, which are the “configuration spaces” of all sensor-based planning problems. The last part of the book delves into planning under differential constraints that arise when automating the motions of virtually any mechanical system. Developed from courses taught by the author, the book is intended for students, engineers, and researchers in robotics, artificial intelligence, and control theory as well as computer graphics, algorithms, and computational biology.

Planning Algorithms: Introductory Material

From the Publisher: 
The accessible presentation of this book gives both a general view of the entire computer vision enterprise and also offers sufficient detail to be able to build useful applications. Users learn techniques that have proven to be useful by first-hand experience and a wide range of mathematical methods. A CD-ROM with every copy of the text contains source code for programming practice, color images, and illustrative movies. Comprehensive and up-to-date, this book includes essential topics that either reflect practical significance or are of theoretical importance. Topics are discussed in substantial and increasing depth. Application surveys describe numerous important application areas such as image based rendering and digital libraries. Many important algorithms broken down and illustrated in pseudo code. Appropriate for use by engineers as a comprehensive reference to the computer vision enterprise.

Computer vision : a modern approach = 计算机视觉 : 一种现代的方法

A scheme is developed for classifying the types of motion perceived by a humanlike robot. It is assumed that the robot receives visual images of the scene using a perspective system model. Equations, theorems, concepts, clues, etc., relating the objects, their positions, and their motion to their images on the focal plane are presented. >

http://ieeexplore.ieee.org/iel2/815/3148/00100651.pdf

Robot vision

We explore the effect of dimensionality on the nearest neighbor problem. We show that under a broad set of conditions (much broader than independent and identically distributed dimensions), as dimensionality increases, the distance to the nearest data point approaches the distance to the farthest data point. To provide a practical perspective, we present empirical results on both real and synthetic data sets that demonstrate that this effect can occur for as few as 10-15 dimensions. These results should not be interpreted to mean that high-dimensional indexing is never meaningful; we illustrate this point by identifying some high-dimensional workloads for which this effect does not occur. However, our results do emphasize that the methodology used almost universally in the database literature to evaluate high-dimensional indexing techniques is flawed, and should be modified. In particular, most such techniques proposed in the literature are not evaluated versus simple linear scan, and are evaluated over workloads for which nearest neighbor is not meaningful. Often, even the reported experiments, when analyzed carefully, show that linear scan would outperform the techniques being proposed on the workloads studied in high (10-15) dimensionality!.

When is nearest neighbor meaningful

Ad hoc networks, due to their improvised nature, are frequently established in insecure environments and hence become susceptible to attacks. These attacks are launched by participating malicious nodes against different network services. Routing protocols, which act as the binding force in these networks, are a common target of these nodes. A number of secure routing protocols have recently been proposed, which make use of cryptographic algorithms to secure the routes. However, in doing so, these protocols entail a number of prerequisites during both the network establishment and operation phases. In contrast, trust-based routing protocols locate trusted rather than secure routes in the network by observing the sincerity in participation by other nodes. These protocols thus permit rapid deployment along with a dynamically adaptive operation, which conforms with the current network situation. In this paper, we evaluate the performance of three trust-based reactive routing protocols in a network with varying number of malicious nodes. With the help of exhaustive simulations, we demonstrate that the performance of the three protocols varies significantly even under similar attack, traffic, and mobility conditions. However, each trust-based routing protocol has its own peculiar advantage making it suitable for application in a particular extemporized environment.

http://web2.utc.edu/~djy471/CNS-reading/comparison-trust-routing.pdf

Performance comparison of trust-based reactive routing protocols

FlexiTP is a novel TDMA protocol that offers a synchronized and loose slot structure. Nodes in the network can build, modify, or extend their scheduled number of slots during execution, based on their local information. Nodes wake up for their scheduled slots; otherwise, they switch into power-saving sleep mode. This flexible schedule allows FlexiTP to be strongly fault tolerant and highly energy efficient. FlexiTP is scalable for a large number of nodes because its depth-first-search schedule minimizes buffering, and it allows communication slots to be reused by nodes outside each other's interference range. Hence, the overall scheme of FlexiTP provides end-to-end guarantees on data delivery (throughput, fair access, and robust self-healing) while also respecting the severe energy and memory constraints of wireless sensor networks. Simulations in ns-2 show that FlexiTP ensures energy efficiency and is robust to network dynamics (faults such as dropped packets and nodes joining or leaving the network) under various network configurations (network topology and network density), providing an efficient solution for data-gathering applications. Furthermore, under high contention, FlexiTP outperforms 2-MAC in terms of energy efficiency and network performance.

/pdf/flexitp-a-flexible-schedule-based-tdma-protocol-for-fault-43axp4heke.pdf

FlexiTP: A Flexible-Schedule-Based TDMA Protocol for Fault-Tolerant and Energy-Efficient Wireless Sensor Networks

RNA pseudoknots are functional structure elements with key roles in viral and cellular processes. Prediction of a pseudoknotted minimum free energy structure is an NP-complete problem. Practical algorithms for RNA structure prediction including restricted classes of pseudoknots suffer from high runtime and poor accuracy for longer sequences. A heuristic approach is to search for promising pseudoknot candidates in a sequence and verify those. Afterwards, the detected pseudoknots can be further analysed using bioinformatics or laboratory techniques. We present a novel pseudoknot detection method called DotKnot that extracts stem regions from the secondary structure probability dot plot and assembles pseudoknot candidates in a constructive fashion. We evaluate pseudoknot free energies using novel parameters, which have recently become available. We show that the conventional probability dot plot makes a wide class of pseudoknots including those with bulged stems manageable in an explicit fashion. The energy parameters now become the limiting factor in pseudoknot prediction. DotKnot is an efficient method for long sequences, which finds pseudoknots with higher accuracy compared to other known prediction algorithms. DotKnot is accessible as a web server at http://dotknot.csse.uwa.edu.au.

/pdf/dotknot-pseudoknot-prediction-using-the-probability-dot-plot-3jv4g0wlk9.pdf

DotKnot: pseudoknot prediction using the probability dot plot under a refined energy model

A wireless network (WN) is a distributed system where each node is a small hand-held commodity device called a station. Wireless sensor networks have received increasing interest in recent years due to their usage in monitoring and data collection in a wide variety of environments like remote geographic locations, industrial plants, toxic locations or even office buildings. One of the most important issues related to a WN is its energy constraints. A station is usually powered by a battery which cannot be recharged while on a mission. Hence, any protocol run by a WN should be energy-efficient. We design energy-efficient protocols for one-to-one communication on a single channel and k-channel wireless network. Our protocols can be extended for multiple multicasting as well.

Energy-Efficient Communication Protocols for Wireless Networks

Let S be a set of n points in d-space, where d ≥ 2 is a constant, and let 1 ≤ k ≤ n be an integer. A unified approach is given for solving the problem of finding a subset of S of size k that minimizes some closeness measure, such as the diameter, perimeter or the circumradius. Moreover, data structures are given that maintain such a subset under insertions and deletions of points.

/pdf/static-and-dynamic-algorithms-for-k-point-clustering-1ilet0a85e.pdf

Amitava Datta

Papers

Performance comparison of trust-based reactive routing protocols

FlexiTP: A Flexible-Schedule-Based TDMA Protocol for Fault-Tolerant and Energy-Efficient Wireless Sensor Networks

DotKnot: pseudoknot prediction using the probability dot plot under a refined energy model

Energy-Efficient Communication Protocols for Wireless Networks

Static and Dynamic Algorithms for k-Point Clustering Problems