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Remote health monitoring BASNs promise substantive improvements in the quality of healthcare by providing access to diagnostically rich patient data in real-time. However, adoption is hindered by the threat of compromise of the diagnostic quality of the data by faults. Simultaneously, unresolved issues exist with the secure sharing of the sensitive medical data measured by automated BASNs, stemming...
Similarity has been widely used in finding similar objects among complex and large scale information networks. Most of the current similarity comparison methods are the distance-based, link-based, neighborhood based similarity or the reference based similarity, and so on. They mainly make the similarity comparison with some kind of metrics but are lack of the measurement of the objects' semantics...
Recently, mobile social networking in proximity (MSNP) has gained tremendous attentions, which refers to the social interactions among physically proximate mobile users directly through the Bluetooth/WiFi interfaces on their Smartphones or other mobile devices. MSNP applications can provide users more opportunities to discover and make new social interactions within proximity area, e.g., Airports,...
We present a solution to a specific version of one of the most fundamental computer science problem - the nearest neighbour problem (NN). The new, proposed variant of the NN problem is the multispace, dynamic, fixed-radius, all nearest neighbours problem, where the NN data structure handles queries that concern different subsets of input dimensions. In other words, solutions to this problem allow...
Coastal marine ecosystems are highly productive and diverse, but biodiversity of underwater habitats is poorly described due to logistical and financial limitations of diving and submersible operations. Imagery is a promising way to address this challenge, but the complexity of diverse organisms thwarts simple automated analysis. We consider the problem of automated annotation of complex communities...
An increasing number of organisations want to migrate their existing applications to cloud environments to benefit from the increased scalability, flexibility, and cost reduction. Additionally, systems migrated to cloud environments have to fulfil their functional requirements, satisfy their users' requirements, and meet the organisation's criteria for cloud migration. All these different dimensions...
underlying cloud computing feature, outsourcing of resources, makes the Service Level Agreement (SLA) is a critical factor for Quality of Service (QoS), and many researchers have addressed the question of how a SLA can be evaluated. Lately, security-SLAs have also received much attention with the Security-as-a-Service mode in cloud computing. The quantitative measurement of security metrics is a considerably...
Building on the intuition behind Nearly Decomposable systems, we propose NCDREC, a top-N recommendation framework designed to exploit the innately hierarchical structure of the item space to alleviate Sparsity, and the limitations it imposes to the quality of recommendations. We decompose the item space to define blocks of closely related elements and we introduce corresponding indirect proximity...
To access the Internet, companies define a Service Level Agreement (SLA) with Internet Service Providers (ISPs). Nevertheless, the current Internet does not assure Quality of Service (QoS), what points toward the concept of virtual networks (VNs) and software defined network (SDN) to support the Future Internet. Moreover, the VN and SDN approaches can be mixed creating the Virtual Software Defined...
This paper presents the application of Na??ve Bayesian classifier to automatic classification of webpage. The key point in this article is that massive empirical data derives from the real traffic data collected from the backbone network of certain province in China, and we apply cumulative probability to determine the optimal size of feature vector adaptively. It's proved that the adaptive method...
Topic modeling is a popular research topic and is widely used in text mining based applications. Many researchers realize that the learned topics in the LDA model, each as a multinomial distribution on the word vocabulary space, are often not intuitive in term of human recognition and communication. Based on our observation, given a topic, the most frequent words in it are usually less important than...
Sentence similarity methods are used to assess the degree of likelihood between phrases. Many natural language applications such as text summarization, information retrieval, text categorization, and machine translation employ measures of sentence similarity. The existing approaches for this problem represent sentences as vectors of bag of words or the syntactic information of the words in the phrase...
We present a hardware architecture for real-time digital video stabilization in high-performance embedded systems. The stabilization algorithm analyzes the current and past video frames and obtains a motion estimation vector, which is then filtered to isolate unwanted camera movements from intentional panning. The vector is then used to correct the output video frame. We designed a hardware architecture...
The rapid development of online social networks (OSN) renders them a powerful tool for information diffusion. Understanding the temporal behavior of OSN users is critical in studying the diffusion process. While there is much work on building various diffusion models to characterize the information propagation process, the diversity of OSN users' behavior patterns is seldom addressed in these models...
Correctly interpreting human instructions is the first step to human-robot interaction. Previous approaches to semantically parsing the instructions relied on large numbers of training examples with annotation to widely cover all words in a domain. Annotating large enough instructions with semantic forms needs exhaustive engineering efforts. Hence, we propose propagating the semantic lexicon to learn...
We propose an approximate logic synthesis heuristic for synthesizing a 2-SPP circuit under a given error rate threshold. 2-SPP circuits are three-level EXOR-AND-OR forms with EXOR gates restricted to fan-in 2. They represent a direct generalization of SOP forms, obtained generalizing cubes to "2-pseudocubes" where literals in cubes may be replaced by 2-EXOR factors in 2-pseudocubes. We discuss...
In this paper we address the problem of predicting SPARQL query performance. We use machine learning techniques to learn SPARQL query performance from previously executed queries. Traditional approaches for estimating SPARQL query cost are based on statistics about the underlying data. However, in many use-cases involving querying Linked Data, statistics about the underlying data are often missing...
We present a novel framework for semisupervised labeling of regions in remote sensing image datasets. Our approach works by decomposing the image into irregular patches or superpixels and derives novel features based on intensity histograms, geometry, corner density, and scale of tessellation. Our classification pipeline uses either k-nearest neighbors or SVM to obtain a preliminary classification...
Thanks to the use of lexical and syntactic information, Word Graphs (WG) have shown to provide a competitive Precision-Recall performance, along with fast lookup times, in comparison to other techniques used for Key-Word Spotting (KWS) in handwritten text images. However, a problem of WG approaches is that they assign a null score to any keyword that was not part of the training data, i.e. Out-of-Vocabulary...
The projection surface of a 3D line in a non-central camera is a ruled surface, containing the complete information of the 3D line. The resulting line-image is a curve which contains the 4 degrees of freedom of the 3D line. In this paper we investigate the properties of the line-image in conical catadioptric systems. This curve is a particular quartic that can be described by only six homogeneous...
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