223678
Automatic classification of digestive organs in wireless capsule endoscopy videos
Wireless Capsule Endoscopy (WCE) allows a physician to examine the entire small intestine without any surgical operation. With the miniaturization of wireless and camera technologies the ability comes to view the entire gestational track with little effort. Although WCE is a technical break-through that allows us to access the entire intestine without surgery, it is reported that a medical clinician spends one or two hours to assess a WCE video, It limits the number of examinations possible, and incur considerable amount of costs. To reduce the assessment time, it is critical to develop a technique to automatically discriminate digestive organs such as esophagus, stomach, small intestinal (i.e., duodenum, jejunum, and ileum) and colon. In this paper, we propose a novel technique to segment a WCE video into these anatomic parts based on color change pattern analysis. The basic idea is that the each digestive organ has different patterns of intestinal contractions that are quantified as the features. We present the experimental results that demonstrate the effectiveness of the proposed method.
12522566
Real Time Video Data Mining for Surveillance Video Streams
We extend our previous work [1] of the general framework for video data mining to further address the issue such as how to mine video data using motions in video streams. To extract and characterize these motions, we use an accumulation of quantized pixel differences among all frames in a video segment. As a result, the accumulated motions of segment are represented as a two dimensional matrix. Further, we develop how to capture the location of motions occurring in a segment using the same matrix generated for the calculation of the amount. We study how to cluster those segmented pieces using the features (the amount and the location of motions) we extract by the matrix above. We investigate an algorithm to find whether a segment has normal or abnormal events by clustering and modeling normal events, which occur mostly. In addition to deciding normal or abnormal, the algorithm computes Degree of Abnormality of a segment, which represents to what extent a segment is distant to the existing segments in relation with normal events. Our experimental studies indicate that the proposed techniques are promising.
26803013
Jikzi: A New Framework for Secure Publishing
We present a new way to deal with security policy on the web. Our aim is to let people build integrated publishing and e-commerce services using appropriate, simple and uniform mechanisms. Our goal is a single framework that applies equally to the publication of catalogues, music, software, public key certificates and even old fashioned books. Our prototype framework, Jikzi, supports multiple security policies – even in the same document – with a single transparent markup language.
17811625
A Graph-Based Approach for Modeling and Indexing Video Data
In this work, we propose new graph-based data model and indexing to organize and manage video data. To consider spatial and temporal characteristics of video, we introduce a new graph-based data model called spatio-temporal region graph (STRG). Unlike existing graph-based data structures which provide only spatial features, the proposed STRG further provides temporal features, which represent temporal relationships among spatial objects. The STRG is decomposed into its subgraphs object graphs (OGs) and background graphs (BGs). In addition, a new distance measure, called extended graph edit distance (EGED), is introduced in metric space for matching and indexing. Based on clustering and EGED, we propose a new indexing method STRG-index, which is faster and more accurate. We compare the STRG-Index with the M-tree, which is a popular tree-based indexing method for multimedia data. The STRG-index outperforms the M-tree in terms of cost and speed
16719880
Jikzi - a new framework for security policy, trusted publishing and electronic commerce
In this paper, we will describe a thread of research, which we have followed off and on at Cambridge for about three years. Our topic is the security of electronic documents, in the broad sense: how can we be sure of the authenticity of things that are published electronically? This started off as a relatively small project, which we thought would take only a few weeks. The goal was to help our medical informatics department publish information such as drug formularies and treatment protocols on the hospital LAN or PC diskettes, in an appropriately dependable way. It rapidly became clear that the problem was much larger and more complex; a general solution would not only cope with 'content' - text, audio, video, software, whatever - but also with objects such as public key certificates. If done properly, it would give us a systematic way to deal with security policy on the web. Our goal now is to let people build integrated publishing and e-commerce services using simple, uniform and appropriate mechanisms. Our proposed solution is a single transparent markup language that allows us to support multiple security policies, plus supporting material ranging from a test implementation to an authentication logic.
18004950
Trajectory clustering: a partition-and-group framework
Existing trajectory clustering algorithms group similar trajectories as a whole, thus discovering common trajectories. Our key observation is that clustering trajectories as a whole could miss common sub-trajectories. Discovering common sub-trajectories is very useful in many applications, especially if we have regions of special interest for analysis. In this paper, we propose a new partition-and-group framework for clustering trajectories, which partitions a trajectory into a set of line segments, and then, groups similar line segments together into a cluster. The primary advantage of this framework is to discover common sub-trajectories from a trajectory database. Based on this partition-and-group framework, we develop a trajectory clustering algorithm TRACLUS. Our algorithm consists of two phases: partitioning and grouping. For the first phase, we present a formal trajectory partitioning algorithm using the minimum description length(MDL) principle. For the second phase, we present a density-based line-segment clustering algorithm. Experimental results demonstrate that TRACLUS correctly discovers common sub-trajectories from real trajectory data.
28720432
Image coding by fitting RBF-surfaces to subimages
In this paper, an image compression method based on a novel idea of surface fitting is proposed. An image is divided into sub-images using a quad tree according to the complexity of the image surface, which is a three-dimensional surface when the pixel values are considered as heights (z-values) defined on the x-y plane. Sub-image surfaces are approximated using a radial-basis function network (RBFN), and the parameters of the RBFN are stored as compressed image representation. This method has comparable performance and quality to the JPEG image compression technique.
14329383
STeP: The Stanford Temporal Prover
We describe the Stanford Temporal Prover (STeP), a system being developed to support the computer-aided formal verification of concurrent and reactive systems based on temporal specifications. Unlike systems based on model-checking, STeP is not restricted to finite-state systems. It combines model checking and deductive methods to allow the verification of a broad class of systems, including programs with infinite data domains, N-process programs, and N-component circuit designs, for arbitrary N. In short, STeP has been designed with the objective of combining the expressiveness of deductive methods with the simplicity of model checking. The verification process is for the most part automatic. User interaction occurs mostly at the highest, most intuitive level, primarily through a graphical proof language of verification diagrams. Efficient simplification methods, decision procedures, and invariant generation techniques are then invoked automatically to prove resulting first-order verification conditions with minimal assistance. We describe the performance of the system when applied to several examples, including the N-process dining philosopher''s program, Szymanski''s N-process mutual exclusion algorithm, and a distributed N-way arbiter circuit.
28256456
Double Optimization for Design of Protein Energy Function
We propose an automated protocol for designing the energy landscape suitable for the description of a given set of protein sequences with known structures, by optimizing the parameters of the energy function. The parameters are optimized so that not only the global minimum-energy conformation becomes native-like, but also the conformations distinct from the native structure have higher energies than those close to the native one, for each protein sequence in the set. In order to achieve this goal, one has to sample protein conformations that are local minima of the energy function for given parameters. Then the parameters are optimized using linear approximation, and then local minimum conformations are searched with the new energy parameters. We develop an algorithm that repeats this process of parameter optimization based on linear approximation, and conformational optimization for the current parameters, ultimately leading to the optimization of the energy parameters. We test the feasibility of this algorithm by optimizing a coarse grained energy function, called the UNRES energy function, for a set of ten proteins.
18632465
Automatic Recovery from Disk Failure in Continuous-Media Servers
Continuous-media (CM) servers have been around for some years. Apart from server capacity, another important issue in the deployment of CM servers is reliability. This study investigates rebuild algorithms for automatically rebuilding data stored in a failed disk into a spare disk. Specifically, a block-based rebuild algorithm is studied with the rebuild time and buffer requirement modeled. A buffer-sharing scheme is then proposed to eliminate the additional buffers needed by the rebuild process. To further improve rebuild performance, a track-based rebuild algorithm that rebuilds lost data in tracks is proposed and analyzed. Results show that track-based rebuild, while it substantially outperforms block-based rebuild, requires significantly more buffers (17-135 percent more) even with buffer sharing. To tackle this problem, a novel pipelined rebuild algorithm is proposed to take advantage of the sequential property of track retrievals to pipeline the reading and writing processes. This pipelined rebuild algorithm achieves the same rebuild performance as track-based rebuild, but reduces the extra buffer requirement to insignificant levels (0.7-1.9 percent). Numerical results computed using models of five commercial disk drives demonstrate that automatic rebuild of a failed disk can be done in a reasonable amount of time, even at relatively high server utilization (e.g., less than 1.5 hours at 90 percent utilization).