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Web applications rely on web servers to protect the integrity of sensitive information. However, an attacker gaining access to web servers can tamper with the data and query computation results, and thus serve corrupted web pages to the user. Violating the integrity of the web page can have serious consequences, affecting application functionality and decision-making processes. Worse yet, data integrity...
Context-awareness is a very popular method for improving the smart-phone user experience in a certain context, based on device sensor data. This paper present an application that collects data from different sensors at predefined intervals and store them in a database for further analysis. The application also has a web graphical visualizer for the data that helps analyzing the sensor values at certain...
In the actual competitive software industry, software development organizations need a better and formal estimation approaches in order to increase the success rate of software projects. However, currently the estimation approach typically employed in industry is the expert judgment ('experience-based'). Using measures and estimations that continue to be based on researchers' intuition does not contribute...
Smart home is one of the most important applications of ubiquitous computing. In this work, we propose an infrastructure of Vietnamese Smart homes as well as a training framework for activity recognition and forecast. In this framework, active learning technique is applied and a new mining algorithm is proposed. In addition to activity recognition, a forecast mechanism is also added into the smart...
Meetings are an important communication and coordination activity of teams: status is discussed, new decisions are made, alternatives are considered, details are explained, information is presented, and new ideas are generated. As such, meetings contain a large amount of rich project information that is often not formally documented. Capturing all of this informal meeting information has been a topic...
The goal of any system in which there is a large set of components that are mostly similar, but have a non-negligible set of differences, is to find the balance between a “one-size-fits-all” approach, and a “unique-per-system-and-customizable” approach. This paper discusses how the balance between these two extremes is achieved as part of the ground segment and flight segment that will support the...
The Multiple Listing Service, commonly known as the MLS, is the singularly most important database where real estate agents and brokers list real estate properties for sale. It is common that agents include textual comments pertinent to the property. Although the information content of comments varies, it is usually expressed in good faith and in many cases is helpful in shedding light on the overall...
Predictive Analytics analyze the present and the historical informations and make future predictions utilizing data mining or machine learning techniques. Predictive models usually check for some patterns and relationships leading to certain behaviours based on the dependent variables. This paper proposes a mechanism named Analysis and Prediction of Application Usage (APAU) in Android Phones for providing...
Activity clustering and recognition is one of the most important research trends about smart home. Taking place inside a sensor smart home, activities differ from each other at typical characteristics such as sensor sets triggered as well as temporal ones. In this work, we present a smart home infrastructure and propose a method of calculating neighborhood radius for clustering and recognizing in-home...
Non-rigid point set registration is a fundamental problem for many computer vision technologies. In this paper, we proposed a new non-rigid point set registration method based on coherent spatial mapping (CSM) and local geometrical constraint. Our central idea is to express each point as a weighted sum of several nearest neighbors and the same relation holds after the transformation. The registration...
In this paper, we firstly study the possible usability of two state-of-the-art no-reference image quality assessment (IQA) metrics (NIQE and BIQES) originally designed for natural image, in the context of medical ones. We also proposed a modified NIQE, called NIQE-K, inspired by some BIQES features and more adapted to medical images. This study, based on evaluating concurrently the three methods,...
Communication technologies and approaches, such as mobile applications and social media enable individuals to share information with others ubiquitously. These voluntarily created data contain geographic information as well as user generated content such as images or text. Researchers and practitioners can gain highly valuable information by analysing and combining those different types of data. Earlier...
Knowledge-intensive business services (KIBS) such as management consulting, research and development, and IT outsourcing, have become a key component of most industrialized economies. As such, there has been a growing number of empirical studies investigating the way in which KIBS providers, clients, and partners collaboratively create value. These studies provide an important opportunity to improve...
Smart homes have gained attraction for several years in people's daily lives and are still increasing. They provide a fruitful foundation for the creation of social network services as they escort habits and regular activities of people at home, along their way or even at work. Smart homes and their current development stage are not only able to support people by intelligent functionality but also...
Structuring content has a positive effect on students' metacognitive skills. Our work in designing content is to approach the use of gaze tracking techniques in adaptive learning strategy that implicates structuring a learning content that will insure the adaptability in real time, taking into account the profile of each learner in the learning process. We present in this paper a learning content...
A Unit Selection based Synthesis (USS) system selects appropriate units from the inventory based on target cost and join cost. For a syllable based USS system, it is not practically feasible to cover all possible syllables in a language with all possible contexts. Hence, some discontinuity is observed at the concatenation points in the synthesized speech due to unavailability of units with proper...
It is becoming clear that one key characteristic of 5G communication systems will be heterogeneity. Heterogeneity is important to be able to reuse equipment that is available, extract maximum capacity from what is allowed to be used in given spectrum bands and locations due to regulatory limitations, and to match capabilities to the extremely wide range of use cases of 5G. Importantly, this heterogeneity...
Learning vocabulary is both critical and boring for many EFL (English as foreign language) learners and one major difficulty is the lack of suitable context for learning new words. Although videos can provide a rich context for learning vocabulary, it often takes more time than textual media to learn. This paper presents the EVOV system which is to exploit the role of video in vocabulary learning...
In this paper, we are proposing a new semantic and contextual based document image classification framework. The framework is composed of two main modules. The first one is the text analysis module (TAM) which processes document images and extracts words from the image, and second one is the SEMCON, which is a semantic and contextual objective metric. From the list of extracted words by TAM, SEMCON...
In this paper, we address the problem of shape part recognition. For this purpose, we define a robust distance between shape parts based on geodesics in the shape space. The proposed distance uses an elastic shape matching to handle elastic deformations and compare shape parts locally. This distance is applied to shape part classification and shape part retrieval. An experimental study through the...
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