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Avionics systems, along with their internal hardware and software components interfaces, must be well defined and specified (e.g., unambiguous, complete, verifiable, consistent, and traceable specification). Such a specification is usually written in the form of an Interface Control Document (ICD), and represents the cornerstone of the avionics system integration activities. However, there is no commonly...
In this paper, we aimed to guide about latest development and studies about students' performance analysis and Learning Analytics in Massively Open Online Courses (MOOCs) for researchers related with the topics. For this purpose short review for usage of performance prediction and Learning Analytics in MOOCs is investigated In our study, to help readers get familiar with our topic, firstly literature...
Twitter is a source of sharing and communicate recent information, ensuing into huge size of records produces every day. Even though, a various applications of Natural Language Processing and Information Retrieval go through rigorously from an erroneous and tiny nature of tweets. We thought to implement a framework in support of segmentation of tweet by collection form, called as HybridSeg. During...
There are three main classes of modifiers that can affect the polarity of the sentiments described in natural language texts: negations, intensifiers and diminishers. In this paper, we concentrate on the study of these particular words which have a very important semantic role in any natural language description. Our study is applied on a real data set extracted from the popular Romanian Web site...
Users context is exploited by an increased number of applications, especially mobile ones, in order to provide their clients with context-oriented services. With our work we try to extend the usage context to laptop and desktop applications and environments. This paper aims analyzing user behavior on three different habitats: at work, at school and at home. The main purpose of this paper is to find...
The enormous amounts of data that are continuously recorded in electronic health record systems offer ample opportunities for data science applications to improve healthcare. There are, however, challenges involved in using such data for machine learning, such as high dimensionality and sparsity, as well as an inherent heterogeneity that does not allow the distinct types of clinical data to be treated...
In this paper, we describe different ways that data collected through gaming can be used to learn more about individual players or their groups. We also make a case, taking into consideration two massively multiplayer online games, that such data may be indiscriminately collected, given the diminishing cost of electronic storage space and the increasing need for information that government and other...
Any activity in a computer-supported cooperative working environment produces a set of traces. In a collaborative working context, such traces may be very voluminous and heterogeneous. They reflect all the interactive actions among the actors themselves and between the actors and the system. This paper examines what is required to exploit traces in the context of a collaborative working environment...
Positive emotions have been proven to be a key factor for successful learning. In modern personalized learning environments informal learning takes a prominent role and with this the use of computer-mediated communication. Communication data, like for example chat logs, can be harvested for sentiments. Most sentiment analyses operate processing only verbal information. But the messages exchanged in...
A common practice for system testing of web-based applications is to perform the test cases through a web browser. These tests are often recorded and managed by a record and replay tool, such as Selenium IDE. Mining specifications from such tests can be very useful for understanding, verifying, and debugging the system under test. This paper presents an approach to mining a behavior specification...
In the NLP field, the mainstream practice in processing a text is through the syntactic and semantic analysis of its componential sentences. However, more and more researchers have come to realize that without the help of the context, difficulties like ambiguity, ellipsis and anaphora can hardly get really solved. In this paper a new approach of context formalization is introduced — the Context Frame,...
This paper contains a method to construct context data which can help an application grasp user intention in pervasive computing environment (PCE). There are various devices in which a user is interested for the user intention (intended behavior such as entering, reading and sleeping). And the core of PCE is to provide appropriate services adapted for grasped user intention through processing context...
Pervasive computing (also referred to as ubiquitous computing or ambient intelligence) aims to create environments where computers are invisibly and seamlessly integrated and connected into our everyday environment. Pervasive computing applications are often interaction transparent, context aware, and experience capture and reuse capable. Interaction transparency means that the human user is not aware...
The emotion tendency of sentiment word is divided into two types: static emotion tendency and dynamic emotion tendency. Basic semantic lexicon is static emotion tendency, in the real context, but it is different between static emotion tendency and dynamic emotion tendency. The paper proposes a method based on degree lexicon, negative lexicon and dependence relationship of sentence elements. The experimental...
Concept lattice, the core data structure of formal context, has high time complexity when it is constructed. This problem has disturbed the further application of concept lattice in data mining. A union method is developed in this paper, which first vertically divide the formal context into distributed stations, construct concept sub-lattices independently, then union them together. The validity and...
Concept lattice is a new mathematical tool for data analysis and knowledge processing. Attribute reduction is very important in the theory of concept lattice because it can make the discovery of implicit knowledge in data easier and the representation simpler. In this paper the reduction of the concept lattice was investigated. First, we present a close-degree of concept to measure the close-degree...
Frequent pattern mining is a basic problem in data mining and knowledge discovery. The discovered patterns can be used as the input for analyzing association rules, mining sequential patterns, recognizing clusters, and so on. However, discovering frequent patterns in large scale datasets is an extremely time consuming task. Most research in the area of association rule discovery has focused on the...
Female students are in minority in most of technical institutions in India and many infrastructural facilities and services are not targeted to them. Even though Internet facilitates removal of geographical, social and cultural barriers, it does not seem to have any significant impact on academic pursuit of female students. Not many serious investigations have been conducted to study the usage pattern...
The goal of this work is develop and test of a new software archetype, to aid the competence management process in Post-Graduate of Production Engineering Courses. This system will be designed using JADE Agent Framework, to read and analyze XML data. Those technologies have been used to build an innovative environment for software building. The research methodology used in this scientific work is...
In knowledge discovery, the problem of attributes reduction aims to retain the discriminatory power of original attributes. Many algorithms have been proposed, however, quite often, these methods are computationally time-consuming. To overcome this shortcoming, we introduce two functions, which can be used to improve the process of attribute selection. Based on the proposed functions, a new attributes...
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