Search results for "Information System"
showing 10 items of 2404 documents
The Cyberspace Threats and Cyber Security Objectives in the Cyber Security Strategies
2013
Threats in cyberspace can be classified in many ways. This is evident when you look at cyber security on a multinational level. One of the most common models is a threefold classification based on motivational factors. Most nations use this model as a foundation when creating a strategy to handle cyber security threats as it pertains to them. This paper will use the five level model: cyber activism, cybercrime, cyber espionage, cyber terrorism and cyber warfare. The National Cyber Security Strategy defines articulates the overall aim and objectives of the nation's cyber security policy and sets out the strategic priorities that the national government will pursue to achieve these objectives…
Executives' Commitment to Information Security
2020
Two aspects of decision-making on information security spending, executives' varying preferences for how proposals should be presented and the framing of the proposals, are developed. The proposed model of executives' commitment to information security is an interaction model (in addition to the cost of a security solution, and the risk and the potential loss of a security threat) consisting of the interaction between an executive's preferred subordinate influence approach (PSIA), rational or inspirational, and the framing, positive or negative, of a security proposal. The interaction of these two constructs affects the executive's commitment to an information security proposal. The model i…
Time-Frequency Filtering for Seismic Waves Clustering
2014
This paper introduces a new technique for clustering seismic events based on processing, in time-frequency domain, the waveforms recorded by seismographs. The detection of clusters of waveforms is performed by a k-means like algorithm which analyzes, at each iteration, the time-frequency content of the signals in order to optimally remove the non discriminant components which should compromise the grouping of waveforms. This step is followed by the allocation and by the computation of the cluster centroids on the basis of the filtered signals. The effectiveness of the method is shown on a real dataset of seismic waveforms.
Adding sensor-free intention-based affective support to an Intelligent Tutoring System
2017
Abstract Emotional factors considerably influence learning and academic performance. In this paper, we validate the hypothesis that learning platforms can adjust their response to have an effect on the learner’s pleasure, arousal and/or dominance, without using a specific emotion detection system during operation. To this end, we have enriched an existing Intelligent Tutoring System (ITS) by designing a module that is able to regulate the level of help provided to maximize valence, arousal or autonomy as desired. The design of this module followed a two-stage methodology. In the first stage, the ITS was adapted to collect data from several groups of students in primary education, by providi…
The effects of self-efficacy on computer usage
1995
Abstract This paper examines the effect of self-efficacy, belief in one's capabilities of using a computer in the accomplishment of specific tasks, on computer usage. It introduces an extended technology acceptance model (TAM) that explicitly incorporates self-efficacy and its determinants (experience and organizational support) as factors affecting computer anxiety, perceived ease of use, perceived usefulness and the use of computer technology. A survey of 450 microcomputer users in Finland found strong support for the conceptual model. In accordance with TAM, perceived usefulness had a strong direct effect on usage, while perceived ease of use had indirect effect on usage through perceive…
Self-organizing maps could improve the classification of Spanish mutual funds
2006
In this paper, we apply nonlinear techniques (Self-Organizing Maps, k-nearest neighbors and the k-means algorithm) to evaluate the official Spanish mutual funds classification. The methodology that we propose allows us to identify which mutual funds are misclassified in the sense that they have historical performances which do not conform to the investment objectives established in their official category. According to this, we conclude that, on average, over 40% of mutual funds could be misclassified. Then, we propose an alternative classification, based on a double-step methodology, and we find that it achieves a significantly lower rate of misclassifications. The portfolios obtained from…
A Layered Architecture for Sentiment Classification of Products Reviews in Italian Language
2017
The paper illustrates a system for the automatic classification of the sentiment orientation expressed into reviews written in Italian language. A proper stratification of linguistic resources is adopted in order to solve the lacking of an opinion lexicon specifically suited for the Italian language. Experiments show that the proposed system can be applied to a wide range of domains.
Compressive biological sequence analysis and archival in the era of high-throughput sequencing technologies
2013
High-throughput sequencing technologies produce large collections of data, mainly DNA sequences with additional information, requiring the design of efficient and effective methodologies for both their compression and storage. In this context, we first provide a classification of the main techniques that have been proposed, according to three specific research directions that have emerged from the literature and, for each, we provide an overview of the current techniques. Finally, to make this review useful to researchers and technicians applying the existing software and tools, we include a synopsis of the main characteristics of the described approaches, including details on their impleme…
Positionless aspect based sentiment analysis using attention mechanism.
2021
Abstract Aspect-based sentiment analysis (ABSA) aims at identifying fine-grained polarity of opinion associated with a given aspect word. Several existing articles demonstrated promising ABSA accuracy using positional embedding to show the relationship between an aspect word and its context. In most cases, the positional embedding depends on the distance between the aspect word and the remaining words in the context, known as the position index sequence. However, these techniques usually employ both complex preprocessing approaches with additional trainable positional embedding and complex architectures to obtain the state-of-the-art performance. In this paper, we simplify preprocessing by …
Healthcare trajectory mining by combining multidimensional component and itemsets
2012
Sequential pattern mining is aimed at extracting correlations among temporal data. Many different methods were proposed to either enumerate sequences of set valued data (i.e., itemsets) or sequences containing multidimensional items. However, in real-world scenarios, data sequences are described as events of both multidimensional items and set valued information. These rich heterogeneous descriptions cannot be exploited by traditional approaches. For example, in healthcare domain, hospitalizations are defined as sequences of multi-dimensional attributes (e.g. Hospital or Diagnosis) associated with two sets, set of medical procedures (e.g. $ \lbrace $ Radiography, Appendectomy $\rbrace$) and…