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The programming teaching in the primary education is a paramount necessity. However, learning computational concepts has several challenges. In this scope, this study evaluates the application of game programming teaching video classes with students of K-12 education. In this context, a case study was conducted in the second semester of 2015 with 60 students that have participated in an online game...
Code clones have both negative and positive impacts on softwares. Researchers have proposed lots of detection tools to find clones from softwares. However, the information in detection results is not enough to help developers understand and maintain clones. Therefore, we design and implement a clone analysis tool, named CloneAyz, to aid developers to analyze and understand clones. CloneAyz can parse...
Ordinal input variables are common in many supervised and unsupervised machine learning problems. We focus on ordinal classification problems, where the target variable is also categorical and ordinal. In order to represent categorical input variables for measuring distances or applying continuous mapping functions, they have to be transformed to numeric values. This paper evaluates five different...
Data is the most valuable asset companies are proud of. When its quality degrades, the consequences are unpredictable, can lead to complete wrong insights. In Big Data context, evaluating the data quality is challenging, must be done prior to any Big data analytics by providing some data quality confidence. Given the huge data size, its fast generation, it requires mechanisms, strategies to evaluate,...
Social Internet of Things (SIoT) is an evolutionary idea which combines traditional IoT models with social network paradigms. "Objects" in SIoT formulate social relationships with other "trusted objects" according to the relationships of their owners which deliver trustworthy services on request. From our trust platform concept to identify vital trust metrics, attributes, we propose...
We cast the classic problem of achieving k-anonymity for a given database as a problem in algebraic topology. Using techniques from this field of mathematics, we propose a framework for k-anonymity that brings new insights and algorithms to anonymize a database. We focus on the simpler case when the data lies in a metric space which is instrumental in introducing the main ideas and notation. Specifically,...
Optimal team decision making subject to error-prone team members with different capabilities has been studied extensively - particularly in the context of binary classification. The over-arching goal is to correctly classify an object as either being a True Target or a False Target. Each team member comes with pre-specified Type I and II error rates and is asked whether or not he determines the object...
The extensive use of cloud services by both individual users and organizations induces several security risks. The risk perception is higher when Cloud Service Providers (CSPs) do not clearly state their security policies and/or when such policies do not directly match user-defined requirements. Security-oriented Service Level Agreements (Security SLAs) represent a fundamental means to encourage the...
Deep Convolutional Neural Networks(DCNNs) have recently shown great performance in many high-level vision tasks, such as image classification, object detection and more recently outdoor semantic segmentation. However, the convolutional layer only process the local regions in the image, ignoring the global context information. To overcome this poor localization property of Convolutional Neural Networks(CNNs),...
The HEVC standard brings large gains in coding efficiency, significant increase in computational effort and a new parallel encoding structure called tiles. Tiles can be used to greatly decrease encoding time through parallel processing at the cost of coding efficiency degradation. In multi-core systems running multiple tasks, the resources available to the HEVC application may not remain constant...
In our paper we overview methods and tools within traditional, semi-automatic, and automatic approaches towards evaluation of website usability, which continues to gain in importance since the major search engines intensify its consideration it their results rankings. We note certain persisting ambiguities in usability conceptualization for quantitative measurement and a certain gap between its more...
Cloud computing is now extremely popular because of its use of elastic resources to provide optimized, cost-effective and on-demand services. However, clouds may be subject to challenges arising from cyber attacks including DoS and malware, as well as from sheer complexity problems that manifest themselves as anomalies. Anomaly detection techniques are used increasingly to improve the resilience of...
This paper presents a new method for automatically extracting smartphone users' contextual behaviors from the digital traces collected during their interactions with their devices. Our goal is in particular to understand the impact of users' context (e.g., location, time, environment, etc.) on the applications they run on their smartphones. We propose a methodology to analyze digital traces and to...
Even though Virtual Machine Managers (VMMs) are meant to be transparent, a program may still need to know what VMM is virtualizing their environment. Developers may want to ensure their software only works in particular virtual environments, and users may want to know whether they are the victim of some virtualization-based rootkit. Various methods have been developed for programs to discover whether...
Incorporating user interests evolution over time is a crucial problem in user profiling. We particularly focus on social profiling process that uses information shared on user social network to extract his/her interests. In this work, we apply our existing time-aware social profiling method on Twitter. The aim of this study is to measure the effectiveness of our approach on this kind of social network...
Intrusion detection systems (IDS) look for digital patterns mainly over the network or host traffic. Increasing complexity of todays enterprise information systems (EIS) obliges enterprises to deploy multiple but yet isolated IDSs in their IT boundaries, namely in, network (NIDS), host (HIDS), DMZs and application (appIDS). Modern exploits being able to disguise may appear innocent from an individual...
Network function visualization and software-defined networking allow services consisting of virtual network functions to be designed and implemented with great flexibility by facilitating automatic deployments, migrations, and reconfigurations for services and their components. For extended flexibility, we go beyond seeing services as a fixed chain of functions. We present a YANG model for describing...
Most challenges associated with Network Functions Virtualisation (NFV) are related to the automated and large-scale deployment of virtualised network functions (VNFs) within an operational infrastructure, as well as their availability and performance. In order to effectively face these challenges, efficient and comprehensive monitoring of NFV services is a critical aspect. This paper discusses the...
The rapid adoption of MPEG-DASH is testament to its core design principles that enable the client to make the informed decision relating to media encoding representations, based on network conditions, device type and preferences. Typically, the focus has mostly been on the different video quality representations rather than audio. However, for device types with small screens, the relative bandwidth...
This proposed research questions the assumption that strategic performance measurement systems (SPMS) define strategic goals at the individual job level, reducing role ambiguity and ensuring desired employee outcomes. Through qualitative research of both white-collar and blue-collar jobs, we seek to determine the types of jobs most amenable to SPMS guidance.
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