1468385
Narrative abstraction model for story-oriented video
TV program review services, especially drama review services, are one of the most popular video on demand services on the Web. In this paper, we propose a novel video abstraction model for a review service of story-oriented video such as dramas. In a drama review service, viewers want to understand the story in a short time and service providers want to provide video abstracts at minimum cost. The proposed model enables the automatic creation of a video abstract that still allows viewers to understand the overall story of the source video. Also, the model has a flexible structure so that the duration of an abstract can be adjusted depending on the requirements given by viewers. We get clues for human understanding of a story from scenario writing rules and editorial techniques which are popularly used in the process of video producing. We have implemented the proposed model and successfully applied it to several TV dramas.
38239153
Qualitative Behavior Modeling of Information Processing Components
This paper presents qualitative behavior modeling of Information Processing Components(IPCs), which are domain-specific software components for modeling reusable functions in database management systems(DBMSs). After introducing a detailed formal syntax of IPCs, we propose their modular, qualitative behavior generation mechanism. The proposed mechanism is based on qualitative modeling and simulation, thus produces a sequence of temporal state transitions of modeled IPCs. The proposed modeling mechanism aims to facilitate the scientific measurement of
8831551
A per-object based hybrid concurrency control
Existing concurrency control algorithms do not conform well to various environments in the performance perspective. Each algorithm has some assumption on the conflict characteristic of its execution environment, and its performance degrades when the assumption fails. A per-object hybrid scheme integrating a two phase locking algorithm with a parallel validation technique is presented to solve this problem. Read and write accesses on each database object are controlled by one algorithm at a time. This controlling algorithm can alter while transactions are running, in order to enhance the overall system performance. In the simulation study, the proposed scheme with the proposed algorithm alteration strategy is shown to conform well to various execution environments, better than both the two phase locking algorithm and the parallel validation technique.
14456420
A replica control method for improving availability for read-only transactions
Data replication is often considered in distributed database systems to enhance availability and performance. The benefit of data replication, however can only be realized at the cost of maintaining the consistency of data. In particular, network partition failures make it more difficult to achieve high data availability while ensuring strong correctness criteria such as l-copy serializability. We propose a replica control method to improve the availability of data in the presence of network partition failures. Our method extends the traditional primary copy method by using the relaxed correctness criterion called insular consistency for large-scale distributed systems, where partition failures frequently occur. We focus on increasing the availability of data for read-only transactions. We introduce a version vector as a tool for guaranteeing insular consistency and present a mechanism that allows read-only transactions to be executed at any partition as long as the insular consistency is satisfied. An asynchronous update propagation mechanism is also employed to improve the performance of update operations. We also show that the proposed method is correct and give some performance considerations.
13362734
FINDIT: a fast and intelligent subspace clustering algorithm using dimension voting
Abstract The aim of this paper is to present a novel subspace clustering method named FINDIT. Clustering is the process of finding interesting patterns residing in the dataset by grouping similar data objects from dissimilar ones based on their dimensional values. Subspace clustering is a new area of clustering which achieves the clustering goal in high dimension by allowing clusters to be formed with their own correlated dimensions. In subspace clustering, selecting correct dimensions is very important because the distance between points is easily changed according to the selected dimensions. However, to select dimensions correctly is difficult, because data grouping and dimension selecting should be performed simultaneously. FINDIT determines the correlated dimensions for each cluster based on two key ideas: dimension-oriented distance measure which fully utilizes dimensional difference information, and dimension voting policy which determines important dimensions in a probabilistic way based on V nearest neighbors' information. Through various experiments on synthetic data, FINDIT is shown to be very successful in the high dimensional clustering problem. FINDIT satisfies most requirements for good clustering methods such as accuracy of results, robustness to the noise and the cluster density, and scalability to the dataset size and the dimensionality. Moreover, it is gracefully scalable to full dimension without any modification to algorithm.
591216
The HS File: A New Dynamic Signature File Method for Efficient Information Retrieval
Many works on the signature file methods have been made in the past, but they are mainly for static environments. However, many recent applications in practice require a dynamic information storage structure that effectively supports insertions, deletions and updates. Though there are a few signature file techiniques for dynamic environments, they suffer from serious performance degradation when query signature weights are light. In this paper, we propose a new dynamic signature file organization, called the hierarchical signature(HS) file, that solves the problem of light query signature weights. We perform simulation experiments by using wide range of parameter values. We show through performance comparison based on experiments that the HS file improves performance significantly in both the retrieval time and the storage over-head over the other dynamic signature file methods proposed earlier.
9259468
Classification of Multiple Cancer Types by Multicategory Support Vector Machines Using Gene Expression Data
MOTIVATION
High-density DNA microarray measures the activities of several thousand genes simultaneously and the gene expression profiles have been used for the cancer classification recently. This new approach promises to give better therapeutic measurements to cancer patients by diagnosing cancer types with improved accuracy. The Support Vector Machine (SVM) is one of the classification methods successfully applied to the cancer diagnosis problems. However, its optimal extension to more than two classes was not obvious, which might impose limitations in its application to multiple tumor types. We briefly introduce the Multicategory SVM, which is a recently proposed extension of the binary SVM, and apply it to multiclass cancer diagnosis problems.


RESULTS
Its applicability is demonstrated on the leukemia data (Golub et al., 1999) and the small round blue cell tumors of childhood data (Khan et al., 2001). Comparable classification accuracy shown in the applications and its flexibility render the MSVM a viable alternative to other classification methods.


SUPPLEMENTARY INFORMATION
http://www.stat.ohio-state.edu/~yklee/msvm.htm
46434197
Flow Control Strategy for Flexible Machining and Assembly System
Abstract In this paper an effective flow control strategy for a Flexible Machining and Assembly System is proposed using the concepts of operation-oriented and, combined push and pull control method. The proposed flow control mechanism could meet production demands with a minimum makespan while satisfying assigned due-dates and keeping a low volume of work-in-process at the same time. It also considers machine failures and rush jobs.
2973181
Sharing I/O in Strongly Partitioned Real-Time Systems
Strongly partitioned real-time systems have been adopted to provide an integrated run time environment for applications with varied criticalities. This is achieved by guaranteeing spatial as well as temporal partitioning for the applications. To enable accesses to shared I/O devices in such an environment, this paper provides an effective model that the co-existence of any application does not hinder the execution of IO operations or spatial and temporal requirements of other applications. The model utilizes a microkernel-based approach to regulate the work of drive drivers and thus integrate the device-sharing model with the microkernel.
920212
Resource scheduling in dependable integrated modular avionics
In the recent development of avionics systems, integrated modular avionics (IMA) is advocated for next generation architecture that needs integration of mixed criticality real-time applications. These integrated applications meet their own timing constraints while sharing avionics computer resources. To guarantee timing constraints and dependability of each application, an IMA-based system is equipped with the schemes for spatial and temporal partitioning. We refer the model as SP-RTS (strongly partitioned real-time system), which deals with processor partitions and communication channels as its basic scheduling entities. This paper presents a partition and channel-scheduling algorithm for the SP-RTS. The basic idea of the algorithm is to use a two-level hierarchical schedule that activates partitions (or channels) following a distance-constraints guaranteed cyclic schedule and then dispatches tasks (or messages) according to a fixed priority schedule. To enhance schedulability, we devised heuristic algorithms for deadline decomposition and channel combining. The simulation results show the schedulability analysis of the two-level scheduling algorithm and the beneficial characteristics of the proposed deadline decomposition and channel combining algorithms.
45657020
Partial convexification cuts for 0-1 mixed-integer programs
Abstract In this research, we propose a new cut generation scheme based on constructing a partial convex hull representation for a given 0–1 mixed-integer programming problem by using the reformulation–linearization technique (RLT). We derive a separation problem that projects the extended space of the RLT formulation into the original space, in order to generate a cut that deletes a current fractional solution. Naturally, the success of such a partial convexification based cutting plane scheme depends on the process used to tradeoff the strength of the cut derived and the effort expended. Accordingly, we investigate several variable selection rules for performing this convexification, along with restricted versions of the accompanying separation problems, so as to be able to derive strong cuts within a reasonable effort. We also develop a strengthening procedure that enhances the generated cut by considering the binariness of the remaining unselected 0–1 variables. Finally, we present some promising computational results that provide insights into implementing the proposed cutting plane methodology.