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Background: Software defect models can help software quality assurance teams to allocate testing or code review resources. A variety of techniques have been used to build defect prediction models, including supervised and unsupervised methods. Recently, Yang et al. [1] surprisingly find that unsupervised models can perform statistically significantly better than supervised models in effort-aware change-level...
Parkinson's disease is a debilitating and chronic disease of the nervous system. Traditional Chinese Medicine (TCM) is a new way for diagnosing Parkinson, and the data of Chinese Medicine for diagnosing Parkinson is a multi-label data set. Considering that the symptoms as the labels in Parkinson data set always have correlations with each other, we can facilitate the multi-label learning process by...
Even while engaged in an attention-consuming activity such as watching TV, social media users often end up paying attention to one or more social media. This is an example of a behavioral phenomenon called Continuous Partial Attention (CPA). Quantification of user attention can be a valuable metric in understanding user behavior under scenarios where their attention is divided. In this study, we propose...
Adapted from biological sequence alignment, trace alignment is a process mining technique used to visualize and analyze workflow data. Any analysis done with this method, however, is affected by the alignment quality. The best existing trace alignment techniques use progressive guide-trees to heuristically approximate the optimal alignment in O(N2L2) time. These algorithms are heavily dependent on...
Recommender systems take inputs from user history, use an internal ranking algorithm to generate results and possibly optimize this ranking based on feedback. However, often the recommender system is unaware of the actual intent of the user and simply provides recommendations dynamically without properly understanding the thought process of the user. An intelligent recommender system is not only useful...
Given the soaring amount of data being generated daily, graph mining tasks are becoming increasingly challenging, leading to tremendous demand for summarization techniques. Feature selection is a representative approach that simplifies a dataset by choosing features that are relevant to a specific task, such as classification, prediction, and anomaly detection. Although it can be viewed as a way to...
In this article, a new method is presented in order to increase node dispersion on RRTs. This approach allows for a better environment representation, reducing the amount of nodes in the tree. The proposed RRT differs from Classic RRT by an insertion of a new node-tree connection method. The proposed affixing rule uses a tree whose edges are of variable length, which more rapidly explores the environment's...
Measurement of visual quality is of significant importance to many image processing tasks. The target of image quality assessment (IQA) is to design effective computational models in order to automatically predict the quality of images in a perceptual consistent manner. We propose a full reference (FR) IQA metric based on information-theoretic IQA framework and passive aggressive learning algorithm...
In this work, several state-of-the-art Blind Image Quality Assessment (IQA) metrics and measures are evaluated in order to verify how they behave on extreme conditions such as the ones found on pictures of metallic surfaces. This is an important research topic given that the automation of the image acquisition comprehends one of the essential steps towards the automation and autonomy in many fields...
Background: Software security has drawn immense importance in the recent years. While efforts are expected in minimizing security vulnerabilities in source code, the developers' practice of code cloning often causes multiplication of such vulnerabilities and program faults. Although previous studies examined the bug-proneness, stability, and changeability of clones against non-cloned code, the security...
Background: An increasing research effort has devoted to just-in-time (JIT) defect prediction. A recent study by Yang et al. at FSE'16 leveraged individual change metrics to build unsupervised JIT defect prediction model. They found that many unsupervised models performed similarly to or better than the state-of-the-art supervised models in effort-aware JIT defect prediction. Goal: In Yang et al.'s...
Service Assurance (SA) is a significant part of Network Function Virtualization (NFV) to enable automated and efficient service delivery from end to end (E2E). In NFV, SA should be integrated into the design and development loop from the beginning. However, it sees slower pace than other NFV management and orchestration (MANO) components. Most of present NFV-SA solutions are partial and do not provide...
This paper presents a fusion of monocular camera-based metric localization, IMU and odometry in dynamic environments of public roads. We build multiple vision-based maps and use them at the same time in localization phase. For the mapping phase, visual maps are built by employing ORB-SLAM and accurate metric positioning from LiDAR-based NDT scan matching. This external positioning is utilized to correct...
GQM+Strategies is a goal-oriented measurement approach that supports organizations in identifying goals, strategies to achieve goals, and measures to monitor strategies and goals. However, identifying proper strategies is not an easy task. This paper presents two studies performed to investigate how strategies can be established to achieve IT service goals. First, we carried out a qualitative study...
In recent years, there has been growing interest in learning to rank. We considered the current state of learning to rank in information retrieval systems. We proposed an approach for learning to rank problem based on multi-criteria optimization using the method of Pareto optimization and Genetic Algorithms. The performance of the method has been investigated on test data collections, also a comparison...
The recent enhancement of sensor devices, such as the Micro-Electro Mechanical Devices (MEMs) used for information collection and dissemination, has led to the emergence of the Internet of Things (IoT). This new paradigm overlaps with many research area such as the Wireless Sensor Networks (WSNs) where sensor nodes are deployed over an area to perform local computations based on information gathered...
We describe a “crowd measurement” project, referred to as PoQeMoN, whose main objective is to identify Quality of Service (QoS) indicators in order to predict the Quality of Experience (QoE) for HTTP YouTube content on mobile networks. Results are based on experiments on an operational network. The second contribution of this paper is to show that the proposed indicator is easy to implement in order...
In recent years, remarkable breakthrough has been achieved in person re-identification (Re-ID). However most methods are only tested in the closed-world setting where the probe person is assumed to be one of the gallery people. In this paper, we tackle a more realistic problem, open-world Re-ID, which requires to find out whether the probe person is among the gallery or not, and if so, who he is....
The popularly used subjective estimator- mean opinion score (MOS) is often biased by the testing environment, viewers mode, domain expertise, and many other factors that may actively influence on actual assessment. We therefore, devise a no- reference subjective quality assessment metric by exploiting the nature of human eye browsing on videos. The participants' eye-tracker recorded gaze-data indicate...
As transistors decrease its size due to scaling, digital circuit capabilities increase. These increases are evident in terms of area, power, and speed. Due to the small nature of these devices, introducing parallel paths further increases functionality. Certain characteristics of FPGAs provide alternatives to achieve these improvements in a similar fashion. Partial reconfiguration(PR) further improves...
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