Search results for "computer.software_genre"
showing 10 items of 3858 documents
Supporting Dispute Handling in E-Commerce Transactions, a Framework and Related Methodologies
2004
An E-commerce transaction is a means to conduct particular commercial activities using the global digital E-commerce infrastructure. We concentrate here on business to customer (B-to-C) E-commerce transactions. These transactions are based on protocols offered by the global infrastructure, primarily the Internet. Using electronic means to do business can greatly improve the efficiency of the business transactions. It, however, poses some problems that were rarely considered to be important before. One class of problems is caused by the behavior of untrusted participants. For reasons such as dishonesty, disputes may arise. In the general case, when a dispute arises an untrustworthy participa…
Incremental linear model trees on massive datasets
2013
The existence of massive datasets raises the need for algorithms that make efficient use of resources like memory and computation time. Besides well-known approaches such as sampling, online algorithms are being recognized as good alternatives, as they often process datasets faster using much less memory. The important class of algorithms learning linear model trees online (incremental linear model trees or ILMTs in the following) offers interesting options for regression tasks in this sense. However, surprisingly little is known about their performance, as there exists no large-scale evaluation on massive stationary datasets under equal conditions. Therefore, this paper shows their applica…
Crowd Models for Emergency Evacuation: A Review Targeting Human-Centered Sensing
2013
Emergency evacuation of crowds is a fascinating phenomenon that has attracted researchers from various fields. Better understanding of this class of crowd behavior opens up for improving evacuation policies and smarter design of buildings, increasing safety. Recently, a new class of disruptive technology has appeared: Human-centered sensing which allows crowd behavior to be monitored in real-time, and provides the basis for real-time crowd control. The question then becomes: to what degree can previous crowd models incorporate this development, and what areas need further research? In this paper, we provide a survey that describes some widely used crowd models and discuss their advantages a…
SAUCE: A Web-Based Automated Assessment Tool for Teaching Parallel Programming
2015
Many curricula for undergraduate studies in computer science provide a lecture on the fundamentals of parallel programming like multi-threaded computation on shared memory architectures using POSIX threads or OpenMP. The complex structure of parallel programs can be challenging, especially for inexperienced students. Thus, there is a latent need for software supporting the learning process. Subsequent lectures may cover more advanced parallelization techniques such as the Message Passing Interface (MPI) and the Compute Unified Device Architecture (CUDA) languages. Unfortunately, the majority of students cannot easily access MPI clusters or modern hardware accelerators in order to effectivel…
Context-free Languages
1988
In this chapter we shall define a class of rewriting systems called context-free grammars. The left-hand side of a rule in a context-free grammar consists of a single symbol, so that symbols are rewritten “context-freely”. Context-free grammars are of central importance to us because they define the class of context-free languages, the parsing of which is the subject of this book. In this chapter we shall consider some structural properties of context-free grammars which are of importance in parsing. Also, a basic method for recognizing context-free languages will be given.
Elements of Language Theory
1988
In this chapter we shall review the mathematical and computer science background on which the presentation in this book is based. We shall discuss the elements of discrete mathematics and formal language theory, emphasizing those issues that are of importance from the point of view of context-free parsing. We shall devote a considerable part of this chapter to matters such as random access machines and computational complexity. These will be relevant later when we derive efficient algorithms for parsing theoretic problems or prove lower bounds for the complexity of these problems. In this chapter we shall also discuss a general class of formal language descriptors called “rewriting systems”…
Stability-Based Model Selection for High Throughput Genomic Data: An Algorithmic Paradigm
2012
Clustering is one of the most well known activities in scien- tific investigation and the object of research in many disciplines, ranging from Statistics to Computer Science. In this beautiful area, one of the most difficult challenges is the model selection problem, i.e., the identifi- cation of the correct number of clusters in a dataset. In the last decade, a few novel techniques for model selection, representing a sharp departure from previous ones in statistics, have been proposed and gained promi- nence for microarray data analysis. Among those, the stability-based methods are the most robust and best performing in terms of predic- tion, but the slowest in terms of time. Unfortunately…
Debates with Small Transparent Quantum Verifiers
2014
We study a model where two opposing provers debate over the membership status of a given string in a language, trying to convince a weak verifier whose coins are visible to all. We show that the incorporation of just two qubits to an otherwise classical constant-space verifier raises the class of debatable languages from at most NP to the collection of all Turing-decidable languages (recursive languages). When the verifier is further constrained to make the correct decision with probability 1, the corresponding class goes up from the regular languages up to at least E.
A Methodology to Detect Temporal Regularities in User Behavior for Anomaly Detection
2001
Network security, and intrusion detection in particular, represents an area of increased in security community over last several years. However, the majority of work in this area has been concentrated upon implementation of misuse detection systems for intrusion patterns monitoring among network traffic. In anomaly detection the classification was mainly based on statistical or sequential analysis of data often neglect ion temporal events' information as well as existing relations between them. In this paper we consider an anomaly detection problem as one of classification of user behavior in terms of incoming multiple discrete sequences. We present and approach that allows creating and mai…
One-Sided Prototype Selection on Class Imbalanced Dissimilarity Matrices
2012
In the dissimilarity representation paradigm, several prototype selection methods have been used to cope with the topic of how to select a small representation set for generating a low-dimensional dissimilarity space. In addition, these methods have also been used to reduce the size of the dissimilarity matrix. However, these approaches assume a relatively balanced class distribution, which is grossly violated in many real-life problems. Often, the ratios of prior probabilities between classes are extremely skewed. In this paper, we study the use of renowned prototype selection methods adapted to the case of learning from an imbalanced dissimilarity matrix. More specifically, we propose the…