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In cloud computing environment, an application is always composed of several service components. A collection of service components is called a service family, and we name the cloud service components as service family members. In this paper, we propose a solution named Icebreaker to assemble service components belonging to the same application without sniffing tenants' privacy. Icebreaker characterizes...
In the last years, numerous investigations have been made within the field of faults diagnosis in induction motors. Most of them use data obtained either from the time domain, through advanced techniques in the frequency domain or even by simulation tools. Some researchers have employed a considerable effort in designing sophisticated algorithms to achieve the best performance of the diagnosis system...
Bug triaging and assignment is a time-consuming task in big projects. Most research in this area examines the developers' prior development and bug-fixing activities in order to recognize their areas of expertise and assign to them relevant bug fixes. We propose a novel method that exploits a new source of evidence for the developers' expertise, namely their contributions to Q&A platforms such...
Recent years have witnessed a series of occupy protest events all over the world. Detecting and monitoring these events is an important and challenging task in social science research and also can provide reference for government's emergency management. Existing methods mainly solve this problem by document clustering techniques. This paper proposes a novel graph-based occupy protest event detection...
The registration of 3D laser scans is an important task in mapping applications. For the task of mapping with autonomous micro aerial vehicles (MAVs), we have developed a light-weight 3D laser scanner. Since the laser scanner is rotated quickly for fast omnidirectional obstacle perception, the acquired point clouds are particularly sparse and registration becomes challenging. In this paper, we present...
Recently, mobile networks employing high-speed high-capacity communications have been investigated extensively to satisfy the strong demand for the faster and larger data communication beyond 2020 as the 5th generation (5G) mobile communication system. As one of the approaches, high-SHF (6 – 30 GHz) and EHF (mainly 30 – 60 GHz) bands are the candidates to utilize the relatively wide frequency band...
Mechanical errors introduced by a planar measurement range and their effect on diagnostics applications are analyzed in this contribution. The study is based on Monte Carlo statistical analysis by means of an error simulation tool for antenna measurements and diagnostics applications. The effect of each type of error and its contribution to the final uncertainty of the system can be used to establish...
Detection, classification, and tracking of people and vehicles are fundamental processes in intelligent surveillance systems. The use of publicly available data set is the appropriate way to compare the relative merits of existing methods and to develop and assess new robust solutions. In this paper, we focus on the maritime domain and we describe the generation of boat classification data sets, containing...
With rapid advances in technology and connectivity, the capability to capture data from multiple sources has given rise to multiview learning wherein each object has multiple representations and a learned model, whether supervised or unsupervised, needs to integrate these different representations. Multiview learning has shown to yield better predictive and clustering models, it also is able to provide...
Despite the enthusiasm caused by the availability of a steadily increasing amount of openly available, structured data, first critical voices appear addressing the emerging issue of low quality in the meta data and data source of Open Data portals which is a serious risk that could disrupt the Open Data project. However, there exist no comprehensive reports about the actual quality of Open Data portals...
This work presents an approach to detect moving objects from Unmanned Aerial Vehicles (UAV). A common framework for most of the existing techniques is using image registration to warp consecutive frames as an ego-motion compensation step and applying frame differencing to detect the moving objects. Assuming a planar scene, we propose the exploitation of telemetry information available from Global...
Person re-identification is an important computer vision task with many applications in areas such as surveillance or multimedia. Approaches relying on handcrafted image features struggle with many factors (e.g. lighting, camera angle) which lead to a large variety in visual appearance for the same individual. Features based on semantic attributes of a person's appearance can help with some of these...
The IEEE 729-1983 Standard defines software quality as "the composite characteristics of software that determine the degree to which the software in use will meet the expectations of the customer." Assessing software quality in the early stages of design and development is crucial in reducing time and effort. Various metrics have been proposed for estimating software quality characteristics...
In the paper the idea of the visual self-localization of mobile robots based on the estimation of image similarity is discussed. It is assumed that a rough position of the mobile robot is known e.g. from the built-in GPS device. Assuming known orientation of the robot, the main advantage of the application of image analysis algorithms is the increase of the self-localization accuracy. The basic idea...
The recommender system is widely used in many areas in the age of information overload. Collaborative filtering (CF), as one of the most successful methods used for recommendation, recommends items based on the nearest neighbors of the target user. Thus, the performance of the recommender system depends largely on the similarity measure used for selecting neighbors. Most of the traditional similarity...
For point-wise gamut mapping, the largest challenge is how to preserve both detail and saturation with state of the art gamut mapping algorithms based on the main concepts of gamut clipping or gamut compression. Based on a combination of clipping and compression algorithms, a hybrid point-wise gamut mapping framework is proposed and evaluated in this paper. Using five standard scenes, five combination...
Considering the facts that people access to item information more easily than to user information given user privacy, and the features of items selected by the user always imply his/her preferences, we hope to utilize item features to mine user preferences besides ratings. What is more, ratings are often linguistic labels and fuzzy set is tailor-made to represent them. Therefore, we propose a novel...
Virtualized cloud systems are prone to performance anomalies due to various reasons such as resource contentions, software bugs, and hardware failures. It will be a daunting task for system administrators to manually keep track of the execution status of a large number of virtual machines all the time. Anomaly prediction is an effective approach to enhancing availability and reliability of Cloud infrastructures...
Classification is an important technique in data mining. The K-Nearest neighbor (K-NN) algorithm is a memory based algorithm and is capable of producing satisfactory results when applied on certain data but the distance measures used in this algorithm is not capable of handling the data sets containing the uncertain attribute values. Data uncertainty is common in real word applications. In this paper...
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