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The modern infrastructure of electric grid known as smart grid is based on advanced communication and information technologies. The concept of data integration between heterogeneous data sources of smart grid reveals some challenges. The focus of this paper is on data integration as one of the major challenges in IT infrastructure of smart grid. In this paper, a semantic-based hierarchical integration...
Automatic sentiment information extraction of social network articles has many essential applications. Following the valence-arousal space framework, in this paper, two approaches including (1) a weighted graph (WG) and (2) a neural network (NN) model that could predict the valence-arousal ratings of words are evaluated on the Chinese valence-arousal words (CVAW) database provide by the IALP-2016...
SOS is a new model for the online in situ characterization and analysis of complex high-performance computing applications. SOS employs a data framework with distributed information management and structured query and access capabilities. The primary design objectives of SOS are flexibility, scalability, and programmability. SOS provides a complete framework that can be configured with and used directly...
Time-memory trade-off methods provide means to invert one way functions. Such attacks offer a flexible trade-off between running time and memory cost in accordance to users' computational resources. In particular, they can be applied to hash values of passwords in order to recover the plaintext. They were introduced by Martin Hellman and later improved by Philippe Oechslin with the introduction of...
Microtext is sparse and informal content typical in social media that is being widely used to study various facets of today's society. This paper proposes the use of supplemental context to counteract the limitations imposed by the sparsity and the informality of microtext on the performance of word sense disambiguation (WSD). WSD relies on the senses of words around an ambiguous word to disambiguate...
In this work, we describe the design, development, and deployment of NEREA (Named Entity Recognizer for spEcific Areas), an automatic Named Entity Recognizer and Disambiguation system, developed in collaboration with professional documentalists. The aim of NEREA is to keep accurate and current information about the entities mentioned in a local repository, and then support building appropriate infoboxes,...
In this paper, we present a novel method for predicting gene functional interactions. We study the effectiveness of various raw and derived features from neural word embedding learned from biomedical literature. Our evaluation results demonstrate that the information captured in neural word embedding is very useful and our learned classification models are capable of predicting gene functional interactions...
Nowadays, software developers often utilize existing third party libraries and make use of Application Programming Interface (API) to develop a software. However, it is not always obvious which library to use or whether the chosen library will play well with other libraries in the system. Furthermore, developers need to spend some time to understand the API to the point that they can freely use the...
During maintenance, software developers deal with numerous change requests made by the users of a software system. Studies show that the developers find it challenging to select appropriate search terms from a change request during concept location. In this paper, we propose a novel technique-QUICKAR-that automatically suggests helpful reformulations for a given query by leveraging the crowdsourced...
Security testing is a pivotal activity in engineering secure software. It consists of two phases: generating attack inputs to test the system, and assessing whether test executions expose any vulnerabilities. The latter phase is known as the security oracle problem. In this work, we present SOFIA, a Security Oracle for SQL-Injection Vulnerabilities. SOFIA is programming-language and source-code independent,...
In recent years, social networks developed in terms of diversities, capabilities and users. Therefore, researchers in different fields have been attracted to these kind of networks. Trust management between users in these kind of networks is one of the most important research topics. In this article a new model for evaluating trust between users in social networks based on subjective logic is presented...
Quality assurance is a subject that has grown dramatically in importance in recent times. In previous work, we have described how the ACM Curricula can be used to support the Quality Assurance process of educational programs, using the Computer Science program at Reykjavik University as an example. Faculty members and employers of graduates participated in the process, that resulted in providing both...
As web-based open data sources become increasingly accessible and rich, translating and repurposing this data towards an educational goal is a topic of interest. Significant challenges exist in taking this data and translating it to a form meaningful, relevant, and engaging to the learner, addressing the gap between information, knowledge, and understanding. Games provide a key medium through which...
Patterns and pattern languages are mechanisms to describe best practices and good designs to capture experience in a way that it is possible for others to reuse this experience. Similarly, pedagogical patterns try to capture expert knowledge regarding the practice of teaching and learning. Issues related to teaching and learning have been increasingly discussed and studied, particularly computational...
This research paper describes the application of linguistic analysis through scaled co-occurrence networks to create visual representations of systematic literature reviews. This approach uses currently available and free tools in this new application. Co-occurrence networks are a method for visualizing relationships between concepts within written material. The results of a co-occurrence analysis...
Spectrum databases are increasingly being used, particularly in spectrum sharing mechanisms, but also in realms such as network optimization, novel licensing regimes, and regulatory monitoring, among others. Spectrum databases are often far more effective, reactive, or sometimes even are required to operate, in conjunction with spectrum sensing — especially if their operation requires automation....
In Venezuela and other countries where it coexists public health system and a private one, we find a variety of organizations that present health services. Even though we have a strong public system, we often find that each health center uses different Electronic Medical Record systems, hindering data sharing for improved patient care. One of the strongest challenges for the integration of all databases...
Selecting the appropriate parameters for an indoor positioning system may be a difficult task due to the large number of parameter combinations. It is more complex in realistic multi-building multi-floor environments, where severe wrong building and floor errors occur but they are not highlighted in the main evaluation metric. Moreover, a selected parameter configuration, that may seem appropriate...
The main problem of rule-based information extraction technique is that the extraction rules tend to be specifically designed for specific information or document structure; hence it cannot be directly used in another without some proper modifications. Semi-structured documents like tables present another challenge to information extraction; since there are no standards on how to design it, the structure...
In this paper, we present a system to recognize text in traffic signs, along with its context based recognition result corrections that we developed. This system detects text in traffic signs region using contour detection and using KNN Classifier to recognize letters in it. The result of the recognitions that may contain errors will be corrected using Forward Reverse Dictionary that has Contextual...
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