Contextual processing is a new emerging field based on the notion that information surrounding an event lends new meaning to the interpretation of the event. Data mining is the process of looking for patterns of knowledge embedded in a data set. The process of mining data starts with the selection of a data set. This process is often imprecise in its methods as it is difficult to know if a data set for training purposes is truly a high quality representation of the thematic event it represents. Contextual dimensions by their nature have a particularly germane relation to quality attributes about sets of data used for data mining. This paper reviews the basics of the contextual knowledge domain and then proposes a method by which context and data mining quality factors could be merged and thus mapped. It then develops a method by which the relationships among mapped contextual quality dimensions can be empirically evaluated for similarity. Finally, the developed similarity model is utilized to propose the creation of contextually based taxonomic trees. Such trees can be utilized to classify data sets utilized for data mining based on contextual quality thus enhancing data mining analysis methods and accuracy.

This chapter introduces the idiosyncrasies of managing the new paradigm of global contextual data, sets of context data and super sets of context data. It introduces some of the basic idea's behind contexts and then develops a model for management of aggregated sets of contextual data and proposes methods for dealing with the selection and retrieval of context data that is inherently ambiguous about what to retrieve for a given query. Because contexts are characterized by four dimensions, those of time, space, impact and similarity they are inherently complicated to manage.This work builds on previous work and extends that work to incorporate contexts. The original model for spatial-temporal management is presented and then analyzed to determine much coverage it can provide to the new context paradigm.

Contextual processing is a new emerging field based on the notion that information surrounding an event lends new meaning to the interpretation of the event. Data mining is the process of looking for patterns of knowledge embedded in a data set. The process of mining data starts with the selection of a data set. This process is often imprecise in its methods as it is difficult to know if a data set for training purposes is truly a high quality representation of the thematic event it represents. Contextual dimensions by their nature have a particularly germane relation to quality attributes about sets of data used for data mining. This paper reviews the basics of the contextual knowledge domain and then proposes a method by which context and data mining quality factors could be merged and thus mapped. It then develops a method by which the relationships among mapped contextual quality dimensions can be empirically evaluated for similarity. Finally, the developed similarity model is utilized to propose the creation of contextually based taxonomic trees. Such trees can be utilized to classify data sets utilized for data mining based on contextual quality thus enhancing data mining analysis methods and accuracy.

Develops a Comprehensive, Global Model for Contextually Based Processing SystemsA new perspective on global information systems operation Helping to advance a valuable paradigm shift in the next generation and processing of knowledge, Introduction to Contextual Processing: Theory and Applications provides a comprehensive model for constructing a contextually based processing system. It explores the components of this system, the interactions of the components, key mathematical foundations behind the model, and new concepts necessary for operating the system. After defining the key dimensions of a model for contextual processing, the book discusses how data is used to develop a semantic model for contexts as well as language-driven context-specific processing actions. It then applies rigorous mathematical methods to contexts, examines basic sensor data fusion theory and applies it to the contextual fusion of information, and describes the means to distribute contextual information. The authors also illustrate a new type of data repository model to manage contextual data, before concluding with the requirements of contextual security in a global environment. This seminal work presents an integrated framework for the design and operation of the next generation of IT processing. It guides the way for developing advanced IT systems and offers new models and concepts that can support advanced semantic web and cloud computing capabilities at a global scale.

Real-time information dissemination is essential for the success of key applications such as transportation management and battlefield monitoring. In these applications, relevant information should be disseminated to interested users in a timely fashion. However, it is challenging to support timely information dissemination due to the limited and even time-varying network bandwidth. Thus, a naive approach disseminating every data with no consideration of the context that describes where and when the data is acquired and how it can satisfy users may only provide poor performance and user perceived quality of service (QoS). To address the problem, we design a novel context-aware protocol to disseminate real-time data in a cost-effective manner by considering the spatio-temporal semantics associated with information. More specifically, we define (1) context attributes, (2) develop how to analyze the utility of a specific data item based on the attributes, (3) and adjust the utility based on a cost-benefit analysis for costeffective real-time information dissemination especially in the context of visual surveillance.

In this paper, we introduce a new model for global integration of disparate data about thematic events into an information context. Such a model has a context that controls the processing and derivation of knowledge from a context. The context of the information also can control the dissemination the information and the knowledge derived from it. A semantic based processing grammar is then developed that defines how processing of contextual may be contextually derived. This architectures processing model is generalized such that the specific processing actions for a given system can be mapped onto the grammar by an entity using this model as its core processing paradigm. Finally, because contextual driven processing is meant to operate at a global information sharing level, we examine and propose a novel method for determination of the level of security a context may require as is disseminated across the internet. Again this model is open architected such that the level of security is suggested but the specifics of application are tailored to the needs of an entitiy.

In this paper, we introduce a new paradigm for global computation, one in which the context of collected information drives the type of processing and dissemination the information receives as it is dispersed around the world. The creation of this model has necessitated the development of new types of methods for securing contextual information because the internet itself inherently has not have security mechanisms. Security is typically localized at the nodes on the internet that process information. There are multiple models and methods that are under development to provide security for contexts. This paper presents the basics of a model that allows context consumers to determine the level of security contextual information should have. Security levels have a direct correlation with confidence in the integrity of contextual data and thus application of its processing.

Plant form is shaped by a complex network of intrinsic and extrinsic signals. Light-directed growth of seedlings (photomorphogenesis) depends on the coordination of several hormone signals, including brassinosteroids (BRs) and auxin. Although the close relationship between BRs and auxin has been widely reported, the molecular mechanism for combinatorial control of shared target genes has remained elusive. Here we demonstrate that BRs synergistically increase seedling sensitivity to auxin and show that combined treatment with both hormones can increase the magnitude and duration of gene expression. Moreover, we describe a direct connection between the BR-regulated BIN2 kinase and ARF2, a member of the Auxin Response Factor family of transcriptional regulators. Phosphorylation by BIN2 results in loss of ARF2 DNA binding and repression activities. arf2 mutants are less sensitive to changes in endogenous BR levels, whereas a large proportion of genes affected in an arf2 background are returned to near wildtype levels by altering BR biosynthesis. Together, these data suggest a model where BIN2 increases expression of auxin-induced genes by directly inactivating repressor ARFs, leading to synergistic increases in transcription.

This paper explains a new technique that takes advantage of advancements in digital imaging technology to visually transfer large amounts of data quickly between computing machines. Rather than seeking to improve upon well developed systems already in use to move information between computers, such as data compression, broadband cable, or high-speed wireless, this paper explores the potential usefulness of devices not traditionally used to send and receive data between machines. .

The field of bioinformatics has experienced rapid development during the last few years. The volume of data generated at universities and private firms has created a new problem for the bioinformatics researcher: how to retrieve the data from several distributed, heterogeneous databases and how to ensure that the retrieved data is securely transmitted in a computationally efficient fashion. Several attempts to integrate the databases or to create a graphical user interface for constructing SQL queries have met with limited success. This paper presents a model for searching and retrieving similar genomic data from multiple data sources and transmitting the data with a low cost authentication technique referred to as BioRLE. Retrieved information is presented in a user friendly interface.

Rapid advances in internet technologies have opened gateways new types of collaborative systems and for specialized educational opportunities. These range from online distance learning for individuals as well as for those who want to learn a certain skill set, courses for which may not be offered in traditional educational institutions. Although these web-based courses have become major global education contributors in overcoming the basic education challenges of the traditional classroom environment, they do not consider the fact that each individual can learn differently. Some students are auditory learners, and some may be visual learners while others may be kinesthetic learners. Adaptive learning systems address this aspect of different learning styles and the need to customize learning instruction. However individual learners progress partly as a function of the content being developed by an instructor. Therefore there is a need for a collaborative system that can let an instructor know how learners are progressing and thus the instructor can modify and disperse near real-time course content if learners are struggling with current content. Such systems provide an innovative method of instruction that adapts to the learner’s unique learning style. A model of a novel approach to collaborative adaptive learning is presented that utilizes learning modalities of instruction tailored to individual needs. At the heart of this approach is a fuzzy neural network (FNN) that evaluates comprehension makes instructional modality selections and collaborates with an instructor in tailoring course content.

Enhanced Pretty Good Privacy (EPGP) is a new cryptosystem based on Pretty Good Privacy (PGP), used for the purpose of secure e-mail message communication over an open network. The idea of EPGP, introduced in this paper, addresses PGP's main drawback of incomplete non-repudiation service, and therefore, attempts to increase the degree of security and efficiency of e-mail message communication.