Catálogo de publicaciones - libros

—This paper proposes an alternative approach to software management in heterogeneous environments. It targets encapsulation and dependency management of component systems using Stanford Beer’s Viable System Model (VSM) as requirements and organizational model. VSM is expressed with meanings of Common Information Model (CIM) extensions that serve as basis for an object-oriented representation of managed components. A control-loop architecture is proposed to facilitate monitoring of heterogeneous component environments using the developed model.

People with physical disabilities have limited capabilities in moving, performing manual tasks and taking participation in some life activities. Muscular dystrophy, multiple sclerosis, spinal cord injuries, head injuries, amputations, arthritis, etc., are some causes of physical disabilities. Since that physical impairments can significantly make tedious, even in some cases quite disable using of information technology, it is required to make adaptations that will be enabling the full communication with computers by persons with this kind of disabilities. In this article, some issues about communication between computers and persons with physical impairments are discussed, and are presented a review of available assistive computer technology that make this communication possible. As information education is fundamental education in modern society, the special accent is given to the communication problematic between physically handicapped persons and computers.

Emails constitute a rich source of a company’s information, replacing fax, letters, phone and memos as the dominant form of inter- and intra-business communication. An email system is now a place where task is received, managed and delegated in a company. For small companies, the backbone of modern business, sieving and analyzing tons of business emails consume much business time. There are abundant data mining techniques that can assist email analysis. This paper describes a web-based approach to parse and mine email logs from a POP3 server for content information. The email system affords users a computer-aided tool for decision making. can be associated with diseases with improved visualizations.

We may be able to finally say that we have cracked the code to the QWERTY keyboard design by finding both a logical and symmetrical mapping of the alphabet to the keys. We distinguish letters in the alphabet that have a right boundary characteristic. We use these letters to structure a pair of matrices whose column-selected sets directly map to a collage of symmetric QWERTY keyboard patterns. These matrix-selected sets can be used for teaching the QWERTY, for combining QWERTY sets with different soft keyboards, and possibly for assisting research related to cognitive informatics.

Software piracy and tampering is a well known threat the world is faced with. There have been a lot of attempts to protect software from reverse engineering and tampering. It appears as if there is an ongoing war between software developers and crackers, both parties want to get an upper hand over each other as the time passes. Some of the ample techniques of software protection are reviewed, including multi-block hashing scheme, hardware based solutions, checksums, obfuscation, guards, software aging, cryptographic techniques and watermarking. All of these techniques play their parts imparted on them to protect the software from malicious attacks.

Association rule mining is used to find association relationships in data. Our work describes the use of association rule discovery as a basis for creating an early warning bio-terror attack system. The system establishes a baseline of “normal” behavior by mining historical emergency response (911) data. Using probabilistic models, we generate spatial and temporal statistics to correlate incident frequency and location in order to identify if a variation in future incidents carries an outbreak signature consistent with the effects of a biological warfare attack. Using three years of real emergency response data for experimentation, this work is focused on the activities relating to the processing and generation of detection rules. Preliminary results indicate that the system can provide reasonable detection rules but there is also more work to address inherent issues of both emergency response and biological warfare such as data quality during incident reporting and population mobility as it relates to outbreaks.

Index structures are frequently used to reduce search times in large databases. With index structures like the B-Tree search time grows only logarithmic with the size of a database for several types of searches. This means that the search time is almost constant for very large database systems even if their size grows significantly. Conventional index structures however do not well support searches specifying lower and/or upper bounds for more than one attribute (multidimensional range searches). Therefore R-Trees are increasingly used in this application context. A typical application domain of R-Trees are spatial database systems with two dimensional search conditions specifying upper and lower bounds for longitude and latitude values. Unfortunately R-Tree efficiency does not meet the expectations in many cases. Theoretical analysis of this problem showed, that search time grows much faster than logarithmic for two and more dimensional range searches in contrary to the one dimensional case. In this paper we prove that a logarithmic search complexity can be achieved for two dimensions, if the form of nodes is optimized relative to the form of search conditions. Based on this result, the paper investigates the form of nodes generated by different existing tree packing methods. Since existing methods fail to ensure the required form, a new tree packing method is proposed which improves the chance to meet the identified requirements.

Mining emerging patterns (EPs) in rare-class databases is one of the new and difficult problems in knowledge discovery in databases (KDD). The main challenge in this task is the limited number of rare-class instances. This scarcity limits the number of emerging patterns that can be mined for the rare class. In this paper, we propose a novel approach for mining emerging patterns in rare-class datasets. We experimentally prove that our method is capable of gaining enough knowledge from the rare class; hence, it increases the performance of EP-based classifiers.

The Success Of A Company Invariably Depends more and more on the ability of a company to recognize changes in its environment at an early stage and consider these changes timely in its competitive behavior. Flexibility, as one of the major factors, marks the ability of a company to master complex environmental situations in order to boost its chances to survive and safeguard its long-term success. This article reflects on the perspectives offered by the utilization of the service oriented paradigm for realizing the integration of a flexibility evaluation platform used for ‘near real-time’ flexibility measurement and monitoring of a manufacturing system, within the scope of a change management platform.

Nowadays, there are plenty of online websites related to news. Hence, new technologies, tools and special search engines are created for having access to the news on these websites. Online news is a special type of public information which has exclusive characteristics. These characteristics contribute news engines tasks such as discovering, collecting and searching to be different with similar tasks in traditional web search engines. Clustering plays conspicuous role in news engines tasks. In this paper we study various tasks in news engines and also focusing on clustering applications in them.