The methodology used to construct tree structured rules is the focus of this monograph. Unlike many other statistical procedures, which moved from pencil and paper to calculators, this text's use of trees was unthinkable before computers. Both the practical and theoretical sides have been developed in the authors' study of tree methods. Classification and Regression Trees reflects these two sides, covering the use of trees as a data analysis method, and in a more mathematical framework, proving some of their fundamental properties.

Classification and regression trees

Co-Planar Stereotaxic Atlas of the Human Brain—3-Dimensional Proportional System: An Approach to Cerebral Imaging, J. Talairach, P. Tournoux. Georg Thieme Verlag, New York (1988), 122 pp., 130 figs. DM 268

Data Mining - Concepts and Techniques.

The primary goal of pattern recognition is supervised or unsupervised classification. Among the various frameworks in which pattern recognition has been traditionally formulated, the statistical approach has been most intensively studied and used in practice. More recently, neural network techniques and methods imported from statistical learning theory have been receiving increasing attention. The design of a recognition system requires careful attention to the following issues: definition of pattern classes, sensing environment, pattern representation, feature extraction and selection, cluster analysis, classifier design and learning, selection of training and test samples, and performance evaluation. In spite of almost 50 years of research and development in this field, the general problem of recognizing complex patterns with arbitrary orientation, location, and scale remains unsolved. New and emerging applications, such as data mining, web searching, retrieval of multimedia data, face recognition, and cursive handwriting recognition, require robust and efficient pattern recognition techniques. The objective of this review paper is to summarize and compare some of the well-known methods used in various stages of a pattern recognition system and identify research topics and applications which are at the forefront of this exciting and challenging field.

/pdf/statistical-pattern-recognition-a-review-1kz1b0tte4.pdf

Statistical pattern recognition: a review

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

Establishing correspondence of non-rigid objects using smoothness of motion

In recent years, databases have evolved from storing pure textual information to storing multimedia information -- text, audio, video, and images. With such databases comes the need for a richer set of search keys that include keywords, shapes, sounds, examples, sketches, color, texture and motion. In this paper we address the problem of image retrieval where keys are object shapes or user sketches. In our scheme, shape features are extracted from each image as it is stored. The image is first segmented and points of high curvature are extracted. Regions surrounding the points of high curvature are used to compute feature values by comparing the regions with a number of references. The references themselves are picked out from the set of orthonormal wavelet basis vectors. An ordered set of distance measures between each local region and the wavelet references form a feature vector. When a user queries the database through a sketch, the feature vectors for high curvature points on the sketch are determined. An efficient nearest neighbor search then yields a set of images which contain objects that match the user's sketch closely. The process is completely automated. Initial experimental results are presented.

Feature identification as an aid to content-based image retrieval

CASMIL aims to develop a cost‐effective and efficient approach to monitor and predict deformation during surgery, allowing accurate, and real‐time intra‐operative information to be provided reliably to the surgeon.

CASMIL: a comprehensive software/toolkit for image-guided neurosurgeries This research was supported in part by a research grant from Michigan Life Sciences Corridor (Grant No MEDC-459).

The importance of wireless cellular communication in our daily lives has grown considerably in the last decade. The smartphones are widely used nowadays, besides voice communication; the authors routinely use them to access the internet, conduct monetary transactions, send text messages and query a lot of useful information regarding the location of specific places of interest. The use of smartphones in their day-to-day communication raises many unresolved security and privacy issues. In this paper they identify relevant security attacks in Wireless Cellular Network. The authors conduct experiments in four different platforms such as Iphone, Android, Windows and Blackberry. The packets captured through Wireshark for approximately 24 minutes, giving them a lot of information regarding security and privacy issues involving the users. A lot of useful apps installed and used by the end-users have serious issues in terms of privacy and the information exposed. Which is the better platform comparing all four and what exactly do they expose from the user's information? What are the threats and countermeasures that the users should be aware of? The aim of the authors' paper is to give answers to the above questions based on the data captured by conducting real-life scenarios.

Theoretical Analysis and Experimental Study: Monitoring Data Privacy in Smartphone Communications

Establishing the identify of a signature by automatic search through a database of signatures is of interest in several areas. This paper describes a system for this purpose. The proposed identification system uses a set of geometric and topologic features to characterize each signature. By considering the spatial distribution of these features, the system maps each signature into two strings of finite symbols. A local associative indexing scheme is then used on these strings to organize the collection of signatures of known identity. When presented with a signature of unknown identity, the system uses the same indexing scheme to retrieve a candidate set of signatures. A verification process is then carried out to find the best match from the candidate set. The performance of the proposed system has been tested with a moderate database. The results obtained indicate that the proposed system is able to identify signatures with great accuracy even when a part of a signature is missing.

Ishwar K. Sethi

Papers

Establishing correspondence of non-rigid objects using smoothness of motion

Feature identification as an aid to content-based image retrieval

CASMIL: a comprehensive software/toolkit for image-guided neurosurgeries This research was supported in part by a research grant from Michigan Life Sciences Corridor (Grant No MEDC-459).

Theoretical Analysis and Experimental Study: Monitoring Data Privacy in Smartphone Communications

Signature identification via local association of features