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Recommendation technique is a personalized search used to assist a user access information/services that are related to his preferences and interests, or to the preferences and interests of similar users. The main challenge of personalized Information Retrieval is the modeling and the integration of user profiles. In this paper, we propose a generic model of user profiles based on the search history...
The popularity of mobile devices and the opportunity to learn regardless of time and place make mobile learning an important method in lifelong learning. However, acceptance of mobile learning by learners is crucial to the success of mobile learning. The objective of this study is to investigate main determinants of mobile learning acceptance in higher education in China. Based on the unified theory...
An increasing number of attacks use advanced tactics, techniques and methods to compromise target systems and environments. Such multi-step attacks are often able to bypass existing prevention and detection systems, such as Intrusion Detection Systems (IDSs), firewalls and anti-virus solutions. These security systems either use an anomaly-based or a signature-based detection approach. For systems...
Quality of Experience (QoE) becomes a topic of utmost eminence for service providers and the major factor in the success of multimedia services. Thus, it is challenging to investigate thoroughly the human side of QoE in order to find out the impact of factors that affect user satisfaction. In this paper, we provide a structured way to build an accurate and objective QoE model. In order to serve this...
Human behavior prediction is critical to studying how healthy behavior can spread through a social network. In this work we present a novel user representation based human behavior prediction model, the User Representation-based Socialized Gaussian Process model (UrSGP). First, we present the Deep Interaction Representation Learning (Deep Interaction) model for learning latent representations of interaction...
In this paper, we present a deep learning based disease named entity recognition architecture. First, the word-level embedding, character-level embedding and lexicon feature embedding are concatenated as input. Then multiple convolutional layers are stacked over the input to extract useful features automatically. Finally, multiple label strategy, which is firstly introduced, is applied to the output...
Virtualisation encourages users to procure, relin-quish and scale resources frequently. Such fluid deployments require continuous performance assessment to inform resource allocation. In current systems Tick Accounting, Load Average, and Memory Usage are used to judge system performance and to trigger resource scaling. We argue that the readily available Context Switch (CS) counter is also an effective...
Construction workers' Workplace Deviant Behavior(WDB) has significant impact on project success. However, existing researches on its occurrence mechanism are mainly focused on personal and organizational factors. Psychological ownership, which has been proved to be a critical variable affecting behavior decision making, has not been considered in the occurrence of construction workers' WDB. This paper...
The exploration of a data set consists in grouping similar data. The classical statistical methods often fail when there is is no minimal assumption on the clusters. Our approach is based on the links between data, but the pairwise comparison between data and the importance of the links depend heavily on context where data lies. We propose to analyze a dataset through methods of the social choice...
The aim of this study was to investigate the impact of the cultural factors on the acquisition of second language from the subjects, selected from registered students in university of science and technology. The subjects in this study were selected from the registered students in English learning courses in university of science and technology. Sixty-nine (69) undergraduates were made up two in-tact...
A Hyperspectral (HS) image provides observational powers beyond human vision capability but represents more than 100 times data compared to a traditional image. To transmit and store the huge volume of an HS image, we argue that a fundamental shift is required from the existing "original pixel intensity"-based coding approaches using traditional image coders (e.g. JPEG) to the "residual"...
Frame rate up conversion (FRUC) has been playing an important role in the recent development of advanced television systems due to its benefits on both increasing the viewing quality experiences and reducing the cost of video transmission. However, with the increasing of video resolutions, notably from Standard Definition (SD) to High Definition (HD), FRUC is now asked to provide not only better interpolated...
The paper describes a heuristic method for the ultra-short-term computation of prediction intervals (PIs) for photovoltaic (PV) power generation. The method allows for directly forecasting the AC active power output of a PV system by simply extracting information from past time series. Two main approaches are investigated. The former relies on experimentally observed correlations between the time...
Previous empirical studies have analyzed emotional responses to form and color, across a variety of contexts and across cultures. Recently Amare and Manning proposed a systematic model that identifies a spectrum of emotional quality (agitation-amusement-focus) generally parallel to the familiar color spectrum (red-yellow-blue) and a spectrum of form (contrast-variety-pattern). For example, both the...
In this paper, we present a generic model to enrich user profiles by means of contextual and temporal information. This reflecting the current interests of these users in every period of time defined by a search session, and infers data freshness. We argue that the annotation of resources gives more transparency on users' needs. Based on this idea, we integrate social tagging in order to exploit part...
For the protection of critical infrastructures against complex virus attacks, automated network traffic analysis and deep packet inspection are unavoidable. However, even with the use of network intrusion detection systems, the number of alerts is still too large to analyze manually. In addition, the discovery of domain-specific multi stage viruses (e.g., Advanced Persistent Threats) are typically...
In previous studies, no consensus has been reached on the existence of significant correlation between perception and production. A large number of empirical studies have been done upon first and second languages from different language families. However, few studies were carried out on the perception-production relation of Chinese English learners. Therefore, in the current study, under the theoretical...
Information overload is one of the most important problems in context of personalized document retrieval systems. In this paper we propose to use ontology-based user profile. Ontological structures are appropriate to represent relations between concepts in user profile. We present a method for determining user profile based on his current activities. Results obtained in experimental evaluation are...
In this study we investigated the effect of mastery confidence manipulation on BCI performance and P300 amplitude. We used a 6×6 P300 speller matrix and participants spelled words containing five letters each. Using a cover story, thirty-six participants were misinformed that they would use classification algorithms of diverse difficulty in three experimental blocks (easy, medium, hard condition)...
A historically important tradition in exegesis, rooted in a number of scriptural passages, considers the Qur'an to be a self-similar text. This claim, while being sharply debated in literature, has never been independently tested. This paper proposes a strategy to measure self-similarity in classical Arabic texts, based on Leven-shtein distance, within the Self-Similar Qur'an (SSQ) project. The significance...
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