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Big Data revolution has transformed business models of many organizations to include the usage of big data analytics. Big Data are believed to be the key basis of competition and growth in today's world whereby huge amounts of data are created daily. One of the main challenges of Big Data is not mainly about the storage of the data but how to blend the different varieties or sources of data together...
The development of Web applications has a crucial role as most organizations have their own corporate Web applications to meet the needs of their respective businesses. Different needs create different complexities which represent a new challenge to Web application development. In order to ensure the timely delivery of a project, software providers offering this service choose to use Open Sources...
We present the AP16-OL7 database which was released as the training and test data for the oriental language recognition (OLR) challenge on APSIPA 2016. Based on the database, a baseline system was constructed on the basis of the i-vector model. We report the baseline results evaluated in various metrics defined by the AP16-OLR evaluation plan and demonstrate that AP16-OL7 is a reasonable data resource...
Contrast change is a special type of image distortion which is vitally important for visual perception of image quality, while little investigates has been dedicated to the contrast-distorted images. A proper contrast change not only reduces human visual perception, instead of improving it. This characteristic determines that full-reference way cannot assess contrast-distorted images properly. In...
An organization that has a lot of personal data can create a deep neural network (DNN), which predicts sensitive attribute values such as the salary and diseases of people based on other attribute values such as age and hobbies. Moreover, by putting this data on the Cloud and providing the functionality of the DNN to other organizations, they can obtain new knowledge and can subsequently create new...
Modeling and simulation in the aviation community is characterized by specialized models built to solve specific problems. Some models are statistically-based, relying on averages and distribution functions using Monte-Carlo techniques to answer policy questions. Others are physics-based, relying on differential equations describing such phenomena as the physics of flight, communication errors and...
Although iris is known as the most accurate and face as the most accepted in biometrics, these distinct modalities encounter variability in data in real-world applications. Such limitation can be overcome by a multimodal system based on both traits. Additionally, by conditioning the multimodal fusion on quality, useful information can be extracted from lower quality measures rather than rejecting...
Automatic Vehicle Location (AVL) is becoming an important tool in Intelligent Transportation Systems (ITS) in the past few years, as it is an effective way of collecting and transmitting data regarding the vehicle's trip for real-time or future use. A methodology for analyzing the state of the art regarding the application of these systems is proposed in a form of a systematic literature review, by...
With the fast development of Geographic Information Systems, visual global localization has gained a lot of attention due to the low price of a camera and the practical implications. In this paper, we leverage Google Street View and a monocular camera to develop a refined and continuous positioning in urban environments: namely a topological visual place recognition and then a 6 DoF pose estimation...
Handwritten Character Recognition is the capability of a computer to receive and interpret handwritten input from paper documents, photographs, touch screens and other devices. In this paper we have introduced a new method for Hindi handwritten character segmentation. It consists of a novel approach segmentation line, word and character using depth first search on the distance metric of connected...
JPEG is still the most widely used image compression format. Perceptual quality assessment for JPEG images has been extensively studied for the last two centuries. While a large number of no-reference perceptual quality metrics have been proposed along the years, it is shown in this paper that on existing image quality databases, statistically, performance of many those metrics is not better than...
Regression testing is the way to ensure the current version of the program is up and running. Continuous testing throughout the development cycle leads to detecting bugs as early as possible; however, it imposes huge overhead if the entire test suite has to be run. In this paper, powered by the goal of early detection of bugs, a regression test selection technique is proposed. The proposed technique...
A multi-stage temporal pooling mechanism is proposed in this paper for improving the prediction capability of an objective quality metric for video quality assessment. The performance of the proposed pooling mechanism is evaluated along with that of traditional pooling mechanisms in terms of linear correlation coefficient and Spearman rank order correlation coefficient on four publicly available video...
Future Internet has been a hot topic for the last decade. One of the approaches put forward in order to revise the Internet architecture is LISP – Locator/ID Separation Protocol, which leverages the separation of the identifier and the locator roles of IP addresses. Contrary to the classical push model used by the BGP-based routing architecture, LISP relies on a pull model. In particular, routing...
This paper presents a metric global localization in the urban environment only with a monocular camera and the Google Street View database. We fully leverage the abundant sources from the Street View and benefits from its topo-metric structure to build a coarse-to-fine positioning, namely a topological place recognition process and then a metric pose estimation by local bundle adjustment. Our method...
In this paper, we propose a scene clustering algorithm which uses straight line features. Scenes are represented as nodes in the graph, and each connectivity between nodes is calculated by a pre-trained vocabulary tree. By applying a spectral clustering algorithm to the constructed graph, the scenes are partitioned into k groups where k is determined by the proposed estimation method. Instead of using...
Hadoop has become a popular platform for the management of big data. To provide a healthy Hadoop platform for big data application, an HMM-based approach for performance diagnosis in Hadoop clusters is proposed. We use metrics which are collected under the normal situation to train HMM (Hidden Markov Model), then use this model to detect anomaly based on the probability, which is more accurate than...
In the last few years, there is a change of backend paradigm for modern mobile applications (Apps). Traditionally, one has to develop a complete system, from the mobile front-end to the backend. This practice has evolved much with the recent introduction of the cloud-based backend to the mobile service development community. This paper discusses and studies selected Mobile-Backend-as-a-Service (mBaaS)...
Probabilistic linear discriminant analysis (PLDA) is a popular normalization approach for the i-vector model, and has delivered state-of-the-art performance in speaker recognition. A potential problem of the PLDA model, however, is that it essentially assumes Gaussian distributions over speaker vectors, which is not always true in practice. Additionally, the objective function is not directly related...
An objective blur measure is crucial for a variety of image processing applications. Traditional researches concentrate on a model estimating the amount of spatial high frequency. However, human vision detects blurriness might be influenced by the texture of image contents. To address the important issue, this paper presents a new objective metric designed as both measuring the inherent smooth texture...
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